100-meter grid representing the coastal plain unconformity (in meters) beneath the inner-continental shelf offshore of Fire Island, NY (FI_CPUN, UTM Zone 18N, WGS 84, Esri Binary Grid)
The U.S. Geological Survey (USGS) mapped approximately 336 square kilometers of the lower shoreface and inner-continental shelf offshore of Fire Island, New York in 2011 using interferometric sonar and high-resolution chirp seismic-reflection systems. This report presents maps of bathymetry, acoustic backscatter, the coastal plain unconformity, the Holocene marine transgressive surface and modern sediment thickness. These spatial data support research on the Quaternary evolution of the Fire Island ... |
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10BIM03_Terrestrial_core_locations: Cat Island Terrestrial Core Locations from field activity 10BIM03
Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain. The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the ... |
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10BIM03_Terrestrial_Vibracore_Table: Cat Island Terrestrial Core Locations from field activity 10BIM03
Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain. The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the ... |
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10cct01_v2rbf_50m.tif: 50-Meter Resolution Grid of Swath Bathymetry Data Collected Offshore of Cat Island, Mississippi in March 2010
In March of 2010, the U.S. Geological Survey (USGS) conducted geophysical surveys east of Cat Island, Mississippi. The efforts were part of the USGS Gulf of Mexico Science Coordination partnership with the U. S. Army Corps of Engineers (USACE) to assist the Mississippi Coastal Improvements Program (MsCIP) and the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazards Susceptibility Project by mapping the shallow geological stratigraphic framework of the Mississippi Barrier Island Complex. The data ... |
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14CCT01_metadata: Sedimentary Data From Grand Bay, Alabama/Mississippi, 2014-2016
This data release is an archive of sedimentary field and laboratory analytical data collected in Grand Bay, Alabama/Mississippi from 2014-2016 by scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This work, a component of the SPCMSC’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, provides the necessary data to quantify sedimentation rates and sediment sources for the marsh and estuary. The SSIEES project ... |
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15CCT02_metadata: Sedimentary Data From Grand Bay, Alabama/Mississippi, 2014-2016
This data release is an archive of sedimentary field and laboratory analytical data collected in Grand Bay, Alabama/Mississippi from 2014-2016 by scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This work, a component of the SPCMSC’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, provides the necessary data to quantify sedimentation rates and sediment sources for the marsh and estuary. The SSIEES project ... |
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16CCT03_metadata: Sedimentary Data From Grand Bay, Alabama/Mississippi, 2014-2016
This data release is an archive of sedimentary field and laboratory analytical data collected in Grand Bay, Alabama/Mississippi from 2014-2016 by scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This work, a component of the SPCMSC’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, provides the necessary data to quantify sedimentation rates and sediment sources for the marsh and estuary. The SSIEES project ... |
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16CCT04_metadata: Sedimentary Data From Grand Bay, Alabama/Mississippi, 2014-2016
This data release is an archive of sedimentary field and laboratory analytical data collected in Grand Bay, Alabama/Mississippi from 2014-2016 by scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This work, a component of the SPCMSC’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, provides the necessary data to quantify sedimentation rates and sediment sources for the marsh and estuary. The SSIEES project ... |
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1998 Atlantic coast NASA/NOAA/USGS Spring ATM Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Atlantic Coast ... |
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1998 East Coast NASA/NOAA/USGS Winter ATM Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Atlantic Coast ... |
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1998 Fall Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Fall Gulf Coast ... |
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1998 MA, NY, MD, and VA USGS/NASA ATM2 Lidar-derived dune crest, toe and shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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1998 Southeast ATM Lidar-derived dune crest, toe and shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Southeast USGS/NASA ... |
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1999 Atlantic Coast NASA/NOAA/USGS ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Floyd
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1999 Atlantic Coast ... |
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1999 Fall Texas USGS/NASA/NOAA ATM Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1999 Fall Gulf Coast ... |
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1 m Digital Bathymetric Contours from NOAA Charts as Organized for the LISSGIS Library (LISBATHY)
The Long Island Sound Study (LISS) compiled data from a number of different sources, integrated new data, and assembled a comprehensive spatial database for areas of the States of Connecticut, New York, and portions of Rhode Island which border Long Island Sound. |
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1-meter backscatter imagery collected in 2012 by the U.S. Geological Survey in the Connecticut River during field activity 2012-024-FA (GeoTIFF image)
A geophysical and geological survey was conducted at the mouth of the Connecticut River from Old Saybrook to Essex, Connecticut, in September 2012. Approximately 230 linear kilometers of digital Chirp subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, riverbed photographs, and (or) video at 88 sites within the geophysical survey area. Sediment grab samples were collected at 72 of the 88 sampling sites, video ... |
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1 Minute Navigation Points for R/V ASTERIAS 90-1 (90_1NAVP)
This GIS layer contains the shiptrack navigation points collected aboard the RV ASTERIAS during a 1990 geophysical cruise to Fishers Island Sound and eastern Long Island Sound. A boomer seismic system was used to collect the subbottom data. |
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2000 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2000 U.S. Army Corps of ... |
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2001 Gulf Coast USGS/NASA ATM Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2001 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 U.S. Army Corps of ... |
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2002 NOAA/NASA/USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 Post-Hurricane Lili ... |
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2002 Post-Tropical Storm Fay University of Texas Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 University of Texas ... |
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2002 USGS Virgina and Maryland Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ... |
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2003 NOAA Oahu Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2003 NOAA Oahu lidar ... |
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2003 Pre- and Post-Hurricane Isabel USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2003 Pre- and Post ... |
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2004 Maine NOAA Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 NOAA Maine lidar ... |
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2004 Post-Hurricane Charley West Florida EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ... |
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2004 Post-Hurricane Frances USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ... |
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2004 Post-Hurricane Ivan Northern Gulf of Mexico EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 USGS Post-Ivan ... |
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2004 Post-Hurricane Jeanne USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ... |
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2004 Pre-Hurricane Ivan Eastern Gulf Coast United States Army Corps of Engineers (USACE) Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Pre-Ivan Eastern ... |
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2004 USACE Post-Ivan Florida Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 U.S. Army Corps of ... |
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2005-2006 Atlantic Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005-2006 Atlantic Coast ... |
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2005 EAARL Fire Island Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Fire Island USGS ... |
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2005 East Coast (DE, MD, NJ, NY, NC, and VA) USACE NCMP Topobathy Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2005 Padre Island USGS EAARL Lidar-derived dune crest, toe and shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Experimental ... |
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2005 Post-Hurricane Dennis Florida U.S. Army Corps of Engineers Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USACE Post-Dennis ... |
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2005 Post-Hurricane Katrina EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Post-Hurricane ... |
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2005 USGS Post-Hurricane Rita Texas and Louisiana Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USGS Post-Hurricane ... |
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2006 FEMA Oahu Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 Federal Emergency ... |
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2007 Northeast Barrier Islands USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Northeast Barrier ... |
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2007 South Florida FDEM Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Florida Division of ... |
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2007 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 U.S. Army Corps of ... |
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2008-2017 Globigerinoides ruber Sediment Trap Data Collected from the Gulf of Mexico
This data release includes results of a high-resolution (1–2 weeks) and long-term sediment trap time series collected from the northern Gulf of Mexico. This dataset allows for a detailed assessment of the seasonal distribution, size, morphological variability and geochemistry of co-occurring pink and white chromotypes of the shallow-water foraminifera, Globigerinoides ruber. The flux of both chromotypes is highly correlated, and both represent mean annual conditions in the marine surface mixed layer. ... |
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2008 Assateague Island USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Assateague Island ... |
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2008 North Carolina and Virginia NOAA/NGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Atlantic Coast ... |
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2008 Post-Hurricane Gustav Northern Gulf of Mexico USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Post-Hurricane ... |
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2008 South Louisiana USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 South Louisiana ... |
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2008 USGS Post-Hurricane Ike Texas Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 USGS Post-Hurricane ... |
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2009 Cape Canaveral USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Cape Canaveral ... |
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2009 Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Florida U.S. Army ... |
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2009 North Carolina USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 U.S. Army Corps of ... |
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2009 Post-NorIda USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Post-NorIda USGS ... |
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2009 Western Gulf of Mexico USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Western Gulf of ... |
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2010-2022 New Jersey and New York Beach Shoreline Change
This dataset defines shoreline change rates for each 10-meter (m)-wide profile calculated via endpoint rate and linear regression from Himmelstoss and others (2018). Shoreline change rates were calculated for two time periods: pre-Sandy (2010-2012) and post-Sandy (2012-2022). The profiles were derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife ... |
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2010-2022 New Jersey and New York Beach Volumes
This dataset defines the volume of sand along a 10-meter (m) wide profile between the seaward-most dune toe and the mean high water shoreline derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife Foundation (NFWF)-funded project entitled “Monitoring Hurricane Sandy Beach and Marsh Resilience in New York and New Jersey” (NFWF project ID 2300.16 ... |
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2010 Alabama and Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Alabama and Florida ... |
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2010 Assateague Island National Seashore USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Assateague Island ... |
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2010 Delaware USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Delaware U.S. Army ... |
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2010 Florida West Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Florida West Coast ... |
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2010 Louisiana and Mississippi USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Louisiana and ... |
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2010 Maryland USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Maryland U.S. Army ... |
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2010 New Jersey USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 New Jersey U.S. ... |
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2010 New York USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 New York U.S. Army ... |
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2010 Northeast Atlantic USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Northeast Atlantic ... |
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2010 Southeast Atlantic USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Southeast Atlantic ... |
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2010 Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Virginia U.S. Army ... |
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2011 East Coast New York/New Jersey NOAA/NGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 East Coast New York ... |
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2011 Northern Gulf Coast USACE Lidar-derived dune crest, toe and shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 Northern Gulf Coast ... |
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2011 USGS New York Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 Atlantic Coast ... |
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2012 Post-Hurricane Isaac USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ... |
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2012 Post-Hurricane Sandy Fire Island, New York Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ... |
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2012 Post-Hurricane Sandy Long Island, New York USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2012 Post-Hurricane Sandy New Jersey USGS EAARL-B Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ... |
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2012 Post-Hurricane Sandy Northeast Atlantic Coast USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post ... |
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2012 Post-Sandy New York and New Jersey USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Sandy New York ... |
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2012 Pre-Hurricane Sandy Fire Island National Seashore, USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ... |
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2012 Pre-Sandy New York and New Jersey USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Pre Hurricane Sandy ... |
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2013-14 Massachusetts Lidar-Derived Dune Crest Point Data
This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ... |
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2013-14 Massachusetts Lidar-Derived Dune Toe Point Data
This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ... |
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2013-2014 Northeast USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013-2014 Post� ... |
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2013 Dauphin Island USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Dauphin Island ... |
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2013 Maine USACE/NAE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Maine United States ... |
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2013 NOAA Oahu Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 National Oceanic ... |
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2013 USACE NAE Topobathy Lidar: Maine Point Cloud files with Orthometric Vertical Datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ... |
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2013 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 U.S. Army Corps of ... |
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2014 East Coast Maine USACE/NAE ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast Maine ... |
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2014 East Coast New Hampshire USACE/NAE ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast New ... |
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2014 East Coast Rhode Island NOAA/NGS ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast Rhode ... |
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2014 Mobile County, Alabama Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 Mobile County, ... |
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2014 Post-Hurricane Sandy SC to NY NOAA NGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2014 USGS CMGP Post-Sandy Long Island Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 USGS CMGP Post ... |
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2015-330-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015
From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile 1,000-shot-interval locations. |
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2015-330-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015
From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile start of trackline locations. |
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2015-330-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015
From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a line dataset of field activity number (FAN) 2015-330-FA chirp tracklines. |
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2015 Mississippi and Alabama USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2015 Mississippi and ... |
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2015 USACE Florida Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2015 U.S. Army Corps of ... |
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2016 Florida East Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2016 U.S. Army Corps of ... |
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2016 Massachusetts NOAA Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2016 USACE Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2016 U.S. Army Corps of ... |
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2016 USACE Post-Hurricane Matthew Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2017 East Coast USACE/FEMA ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Irma
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2017 Atlantic Coast ... |
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2017 Florida West Coast NOAA Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches.Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2017 Georgia through New York USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ... |
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2017 USGS Lidar: Chenier Plain, LA Point Cloud files with Orthometric Vertical Datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ... |
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2018 Alabama and Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 East Coast (NC) USACE NCMP Topobathy Lidar Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 East Coast (VA, NC, SC) USACE NCMP Post-Florence Topobathy Lidar-Derived Dune Crest, Toe, and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 Mississippi and Alabama USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 Puerto Rico USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2018 South Texas USGS Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline derived from the 2018 United States ... |
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2018 USGS Florida Panhandle Post-Michael Lidar-derived Dune Crest, Toe, and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2018 United States Army ... |
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2019-333-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2019-333-FA Offshore of the Rockaway Peninsula, New York, September–October 2019
From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a point dataset of field activity number (FAN) 2019-333-FA chirp subbottom profile 1,000-shot-interval locations. |
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2019-333-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2019-333-FA Offshore of the Rockaway Peninsula, New York, September–October 2019
From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a point dataset of field activity number (FAN) 2019-333-FA chirp subbottom profile start of trackline locations. |
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2019-333-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2019-333-FA Offshore of the Rockaway Peninsula, New York, September–October 2019
From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a line dataset of field activity number (FAN) 2019-333-FA chirp tracklines. |
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2019 North Carolina and Virginia Post-Dorian USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2019 North Carolina and Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (L=lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2020 New Jersey and New York USACE Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2020 New Jersey USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ... |
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2021-322-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2021-322-FA Offshore of Pensacola Beach, Florida, June 2021
From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a point dataset of field activity number (FAN) 2021-322-FA chirp subbottom profile 1,000-shot-interval locations collected inshore and offshore of Pensacola Beach, FL. |
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2021-322-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2021-322-FA Offshore of Pensacola Beach, Florida, June 2021
From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a point dataset of field activity number (FAN) 2021-322-FA chirp subbottom profile start of trackline locations collected inshore and offshore of Pensacola Beach, FL. |
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2021-322-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2021-322-FA Offshore of Pensacola Beach, Florida, June 2021
From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a line dataset of field activity number (FAN) 2021-322-FA chirp tracklines collected inshore and offshore of Pensacola Beach, FL. |
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2021 New York State Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ... |
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2022-309-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022
From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile 1,000-shot-interval locations. |
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2022-309-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022
From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile start of trackline locations. |
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2022-309-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022
From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a line dataset of field activity number (FAN) 2022-309-FA chirp tracklines. |
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2022-312-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, November 2022
From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile 1,000-shot-interval locations. |
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2022-312-FA _sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, June 2022
From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile start of trackline locations. |
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2022-312-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, November 2022
From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-312-FA chirp tracklines. |
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2022-328-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022
On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile 1,000-shot-interval locations. |
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2022-328-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022
On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile start of trackline locations. |
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2022-328-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022
On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a line dataset of field activity number (FAN) 2022-328-FA chirp tracklines. |
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2022-334-FA_BocaChica_Polecam_Imagery: High-resolution Geophysical and Imagery Data Collected in November 2022 Offshore of Boca Chica Key, FL
Underwater images totaling 23,948 in number were collected offshore of Boca Chica Key, the Florida Keys , during November 2022, using the Polecam system developed by the U.S. Geological Survey (USGS). The Polecam system is a single downward-looking underwater Teledyne FLIR camera with a Computar V1228-MPY lens and with a rigidly-attached Global Navigation Satellite System (GNSS) antenna mounted directly above the camera's central axis. The pole camera was attached to the gunwale of the USGS research vessel ... |
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2022-334-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022
From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile 1,000-shot-interval ... |
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2022-334-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022
From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile start of trackline ... |
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2022-334-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022
From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-334-FA chirp tracklines. |
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2022 New Jersey and New York USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline
The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ... |
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2023-310-FA_Oahu_Polecam_Imagery: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii
Underwater images totaling 78,924 in number were collected offshore Fort Hase, Marine Corps Base Hawaii (MCBH) and Coconut Island, Oahu, Hawaii, during May 2023, using the Polecam system developed by the U.S. Geological Survey (USGS). The Polecam system is a single downward-looking underwater Teledyne FLIR camera with a Computar V1228-MPY lens and with a rigidly-attached Global Navigation Satellite System (GNSS) antenna mounted above and forward of the camera's central axis. The Polecam system captured ... |
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2023-310-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023
From May 7-13, 2023, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2023-310-FA chirp subbottom ... |
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2023-310-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023
From May 7-13, 2022, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced ... |
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2023-310-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023
From May 7-13, 2022, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2023-310-FA chirp tracklines. |
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25 m GLORIA sidescan sonar mosaic detail for the Gulf of Mexico Mississippi Fan study area
This image is an enlarged, detailed area from the Gulf of Mexico GLORIA sidescan sonar mosaic. The image was co-registered with SeaMARC 1A sidescan sonar data collected during R/V FARNELLA 90-3 cruise. |
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2-meter bathymetric data collected in 2012 by the U.S. Geological Survey in the Connecticut River during field activity 2012-024-FA (bathymetry and depth-colored hillshade relief GeoTIFFs)
A geophysical and geological survey was conducted at the mouth of the Connecticut River from Old Saybrook to Essex, Connecticut, in September 2012. Approximately 230 linear kilometers of digital Chirp subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, riverbed photographs, and (or) video at 88 sites within the geophysical survey area. Sediment grab samples were collected at 72 of the 88 sampling sites, video ... |
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2-meter bathymetric data collected in 2016 by the U.S. Geological Survey off Town Neck Beach in Sandwich, Massachusetts, during field activity 2016-017-FA (GeoTIFF image)
Geophysical and geological survey data were collected off Town Neck Beach in Sandwich, Massachusetts, in May and July 2016. Approximately 130 linear kilometers of subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, sea floor photographs, and (or) video at 26 sites within the geophysical survey area. Sediment grab samples were collected at 19 of the 26 sampling sites and video and (or) photographic imagery of ... |
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3D bathymetric surfaces of low- and high-relief sites from the coral reef flat off Waiakane, Molokai
3D bathymetric surfaces of low- and high-relief sites from the coral reef flat off Waiakane, Molokai, were created using structure-from-motion (SfM) techniques. The two study sites are located approximately 640 m from shore and approximately 20 m apart in the alongshore direction. At each site, an approximate 12-meter diameter area was imaged in three passes by a swimmer using a handheld digital camera. These images were fed into Structure-from-Motion (SfM) software to produce high-resolution (fine-scale), ... |
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40-m Hillshaded relief image produced from elevation of the late-Wisconsinan regressive unconformity beneath Buzzards Bay, Massachusetts (GeoTIFF Image; UTM, Zone 19N, WGS 84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Buzzards Bay, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a result of a collaborative ... |
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50-meter grid representing the Holocene sediment thickness (in meters) on the inner-continental shelf offshore of Fire Island, NY (FI_HISO, UTM Zone 18N, WGS 84, Esri Binary Grid)
The U.S. Geological Survey (USGS) mapped approximately 336 square kilometers of the lower shoreface and inner-continental shelf offshore of Fire Island, New York in 2011 using interferometric sonar and high-resolution chirp seismic-reflection systems. This report presents maps of bathymetry, acoustic backscatter, the coastal plain unconformity, the Holocene marine transgressive surface and modern sediment thickness. These spatial data support research on the Quaternary evolution of the Fire Island ... |
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50-meter grid representing the Holocene transgressive surface (in meters) beneath the inner-continental shelf offshore of Fire Island, NY (FI_HTS, UTM Zone 18N, WGS 84, Esri Binary Grid)
The U.S. Geological Survey (USGS) mapped approximately 336 square kilometers of the lower shoreface and inner-continental shelf offshore of Fire Island, New York in 2011 using interferometric sonar and high-resolution chirp seismic-reflection systems. This report presents maps of bathymetry, acoustic backscatter, the coastal plain unconformity, the Holocene marine transgressive surface and modern sediment thickness. These spatial data support research on the Quaternary evolution of the Fire Island ... |
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5 m Bathymetric Contours for Long Island Sound (LIS1992)
This bathymetric contour data set was derived from a gridded data set obtained from URI (B.Tyce, G. Hatcher). They used the "Gridder" program to obtain the grid. This gridded data set was generated from the original NOS soundings from 9 track tape that was cleaned up and edited at URI. This work was done with the intention of producing the color poster called "Long Island Sound Estuary" (Connecticut Dept. of Environmental Protection"), 1993. The accuracy is questionable. |
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5 minute Navigation fixes for cruise R/V ASTERIAS 81-2 (81_2NAVP)
This GIS layer contains the shiptrack navigation collected aboard the RV ASTERIAS during a 1981 geophysical cruise to Block Island Sound and easternmost Long Island Sound. |
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5 Minute Navigation Points for R/V ASTERIAS 82-3 (AST82-3) (82_3NAVP)
This GIS layer contains the shiptrack navigation points collected aboard the RV ASTERIAS during a 1982 geophysical cruise to eastern Long Island Sound. A boomer seismic system was used to collect the subbottom data. |
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5 Minute Navigation Points for R/V ASTERIAS 85-8 (AST85-8) (85_8NAVP)
This GIS layer contains the shiptrack navigation points collected aboard the RV ASTERIAS during a 1985 geophysical cruise to western Long Island Sound. A boomer seismic system was used to collect the subbottom data. |
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5 Minute Navigation Points for R/V UCONN 84-1 (UCONN84-1)(84_1NAVP)
This GIS layer contains the shiptrack navigation points collected aboard the RV UCONN during a 1984 geophysical cruise to west-central Long Island Sound. A boomer seismic system was used to collect the subbottom data. |
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A bathymetric terrain model of multibeam sonar data collected between 2005 and 2018 along the Queen Charlotte Fault System in the eastern Gulf of Alaska from Cross Sound, Alaska to Queen Charlotte Sound, Canada. (30-meter resolution, 32-bit GeoTIFF, UTM 8 WGS 84, WGS 84 Ellipsoid)
This data publication is a compilation of six different multibeam surveys covering the previously unmapped Queen Charlotte Fault offshore southeast Alaska and Haida Gwaii, Canada. These data were collected between 2005 and 2018 under a cooperative agreement between the U.S. Geological Survey, Natural Resources Canada, and the National Oceanic and Atmospheric Administration. The six source surveys from different multibeam sonars are combined into one terrain model with a 30-meter resolution. A complementary ... |
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Acidification and Increasing CO2 Flux Associated with Five, Springs Coast, Florida Springs (1991-2014)
Scientists from the South West Florida Management District (SWFWMD) acquired and analyzed over 20 years of seasonally-sampled hydrochemical data from five first-order-magnitude (springs that discharge 2.83 m3 s-1 or more) coastal springs located in west-central Florida. These data were subsequently obtained by the U.S. Geological Survey (USGS) for further analyses and interpretation. The spring study sites (Chassahowitzka, Homosassa, Kings Bay, Rainbow, and Weeki Wachee), which are fed by the Floridan ... |
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Acoustic backscatter from 2013 interferometric swath bathymetry systems survey of Columbia River Mouth, Oregon and Washington
This part of the USGS data release presents acoustic backscatter data for the Columbia River Mouth, Oregon and Washington. The acoustic backscatter data of the Columbia River Mouth, Oregon and Washington were collected by the U.S. Geological Survey (USGS). Mapping was completed in 2013, using a 234-kHz SEA SWATHPlus interferometric system. These data are not intended for navigational purposes. |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during six surveys by the U.S. Geological Survey aboard the R/V Auk, May 2016 to April 2019
These data are a part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The work was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate species ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during three surveys by the U.S. Geological Survey aboard the R/V Auk, September 2020 to August 2021
These data are a part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The work was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate species ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2013-044-FA, aboard the R/V Auk, November 5, 15, and 21, 2013
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2014-015-FA, aboard the R/V Auk, May 22-23 and 29-30, 2014
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2014-055-FA, aboard the R/V Auk, September 23 and 24, 2014
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2014-066-FA, aboard the R/V Auk, November 10, 2014
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2014-070-FA, aboard the R/V Auk, December 12, 2014
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2015-017-FA, aboard the R/V Auk, May 18-19, 29, and June 3, 2015
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2015-074-FA, aboard the R/V Auk, December 1, 2015
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2016-004-FA, aboard the R/V Auk, January 28, 2016
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2016-038-FA, aboard the R/V Auk, Sept. 16 and 19, 2016
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2017-030-FA, aboard the R/V Auk, May 18-23, 2017
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2017-044-FA, aboard the R/V Auk, September 12-14, 2017
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank during U.S. Geological Survey field activity 2019-008-FA, aboard the R/V Auk, July 30, 31, and August 1, 2019
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank on U.S. Geological Survey field activity 2015-062-FA, aboard the R/V Auk, Oct. 21 and 22 and Nov. 3 and 4 2015 (PDF files)
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank on U.S. Geological Survey field activity 2017-009-FA, aboard the R/V Auk, Jan. 30, 2017
This field activity is part of the effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. This cruise was conducted in collaboration with the Stellwagen Bank National Marine Sanctuary, and the data collected will aid research on the ecology of fish and invertebrate ... |
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Acquisition and observation logs for seabed video and sediment samples from Stellwagen Bank on U.S. Geological Survey field activity 2017-043-FA, aboard the R/V Auk, Aug. 22 and 23, 2017 (PDF file)
This field activity is part of an effort to map geologic substrates of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts. The overall goal is to develop high-resolution (1:25,000-scale) interpretive maps, based on multibeam sonar data and seabed sampling, showing surficial geology and seabed sediment dynamics. The data collected in this study will aid research on the ecology of fish and invertebrate species that inhabit the region. On August 22 and 23, 2017, the U.S. Geological ... |
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Acquisition log maintained during field activity 2011-015-FA by the U.S. Geological Survey and Massachusetts Office of Coastal Zone Management offshore of Massachusetts around Cape Cod and the Islands in September 2011 (PDFs of Excel spreadsheets)
Accurate data and maps of sea-floor geology are important first steps toward protecting habitat, delineating marine resources, and assessing environmental changes due to natural or human effects. Initiated in 2003, the primary objective of the Geologic Mapping of the Massachusetts Sea Floor program is to develop regional geologic framework information for the management of coastal and marine resources. The project is focused on the inshore waters (5–30 meters deep) of Massachusetts. This dataset is from U ... |
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Acquisition log maintained during field activity 2012-035-FA by the U.S. Geological Survey and Massachusetts Office of Coastal Zone Management in Ipswich Bay and Massachusetts Bay, Massachusetts, in August 2012 (Excel spreadsheet)
Accurate data and maps of sea-floor geology are important first steps toward protecting habitat, delineating marine resources, and assessing environmental changes due to natural or human effects. Initiated in 2003, the primary objective of the Geologic Mapping of the Massachusetts Sea Floor program is to develop regional geologic framework information for the management of coastal and marine resources. The program is focused on the inshore waters (primarily 5-30 meters deep, although the region surveyed in ... |
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Acquisition log maintained in 2012 by the U.S. Geological Survey in the Connecticut River during field activity 2012-024-FA (PDF of scanned spreadsheet)
A geophysical and geological survey was conducted at the mouth of the Connecticut River from Old Saybrook to Essex, Connecticut, in September 2012. Approximately 230 linear kilometers of digital Chirp subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, riverbed photographs, and (or) video at 88 sites within the geophysical survey area. Sediment grab samples were collected at 72 of the 88 sampling sites, video ... |
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Aerial imagery from the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018
This portion of the data release presents raw aerial imagery collected during an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted in a nadir orientation using a fixed mount. Before each flight, the camera’s digital ISO, aperture, and shutter speed were adjusted for ambient light ... |
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Aerial imagery from the UAS survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01
This portion of the data release presents the raw aerial imagery collected during the unoccupied aerial system (UAS) survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. A total of six flights were conducted for the ... |
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Aerial imagery from UAS survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05
This portion of the data release presents the raw aerial imagery collected during the Unmanned Aerial System (UAS) survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA, on 2019-06-05. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. For flights F01, F02, F03, F04, and F05 the ... |
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Aerial imagery from UAS survey of the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06
This portion of the data release presents the raw aerial imagery collected during an Unmanned Aerial System (UAS) survey of the intertidal zone at Post Point, Bellingham Bay, WA, on 2019-06-06. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The UAS was flown on pre-programmed autonomous ... |
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Aerial imagery from UAS survey of the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03
This portion of the data release presents the raw aerial imagery collected during an Unmanned Aerial System (UAS) survey of the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, on 2019-06-03. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The UAS was flown on pre ... |
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Aerial imagery from UAS survey of the intertidal zone at West Whidbey Island, WA, 2019-06-04
This portion of the data release presents the raw aerial imagery collected during the unmanned aerial system (UAS) survey of the intertidal zone at West Whidbey Island, WA, on 2019-06-04. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. Flights using both a nadir camera orientation and an oblique camera orientation were conducted. For the nadir flights (F04, F05, F06, F07, and F08), the camera was mounted ... |
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Aerial imagery from UAS survey of the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23
This portion of the data release presents the raw aerial imagery collected during the Unmanned Aerial System (UAS) survey of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta on 2018-10-23. The imagery was acquired using two Department of Interior owned 3DR Solo quadcopters fitted with Ricoh GR II digital cameras featuring global shutters. The cameras were mounted using a fixed mount on the bottom of the UAS and oriented in a roughly nadir orientation. The ... |
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Aerial imagery from UAS surveys of beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017
This portion of the data release presents the raw aerial imagery collected during the uncrewed aerial system (UAS) survey conducted on the ocean beaches adjacent to the Columbia River Mouth at the Oregon-Washington border in August 2017. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The ... |
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Aerial imagery from UAS surveys of beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021
This portion of the data release presents the raw aerial imagery collected during the uncrewed aerial system (UAS) survey conducted on the ocean beaches adjacent to the Columbia River Mouth at the Oregon-Washington border in July 2021. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The ... |
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Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ... |
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Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ... |
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Aerial Imagery of the North Carolina Coast: 2019-10-11
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ... |
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Aerial Imagery of the North Carolina Coast: 2019-11-26
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ... |
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Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ... |
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Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ... |
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Aerial_Shorelines_1940_2015.shp - Dauphin Island, Alabama Shoreline Data Derived from Aerial Imagery from 1940 to 2015
Aerial_WDL_Shorelines.zip features digitized historic shorelines for the Dauphin Island coastline from October 1940 to November 2015. This dataset contains 10 Wet Dry Line (WDL) shorelines separated into 58 shoreline segments alongshore Dauphin Island, AL. The individual sections are divided according to location along the island and shoreline type: open-ocean, back-barrier, marsh shoreline. Imagery of Dauphin Island, Alabama was acquired from several sources including the United States Geological Survey ... |
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Archive of Chirp Subbottom Data Collected During USGS Cruise ORGN00005, Northeastern Gulf of Mexico, 15 February - 2 March, 2000
This DVD-ROM contains digital high-resolution seismic-reflection data collected during the USGS ORGN00005 cruise. The seismic-reflection data are stored as SEG-Y standard format which can be read and manipulated by most seismic-processing software. Much of the information specific to the data are contained in the headers of the SEG-Y format files. Software is available on this DVD-ROM for viewing and processing the individual swaths using computer systems running a UNIX operating system. |
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Archive of Chirp Subbottom Profile Data Collected in 2015 from the Northern Chandeleur Islands, Louisiana
From September 14 to 28, 2015, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales ... |
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Archive of Chirp Subbottom Profile Data Collected in 2016 from the Northern Chandeleur Islands, Louisiana
From June 10 to 19, 2016, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months to ... |
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Archive of Chirp Subbottom Profile Data Collected in 2017 from the Louisiana Chenier Plain
June 2–10 and July 2, 2017, the U.S. Geological Survey (USGS) conducted geophysical surveys offshore of the Louisiana Chenier Plain to document the changing morphology of the coastal environment. Data were collected under the Barrier Island Coastal Monitoring (BICM) program, an ongoing collaboration between the State of Louisiana Coastal Protection and Restoration Authority (CPRA), the University of New Orleans (UNO) Pontchartrain Institute for Environmental Sciences (PIES), and the USGS. Project ... |
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Archive of Chirp Subbottom Profile Data Collected in 2017 From the Northern Chandeleur Islands, Louisiana
From August 7 to 16, 2017, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months ... |
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Archive of Chirp Subbottom Profile Data Collected in 2018 from the Northern Chandeleur Islands, Louisiana
From August 16 to 21, 2018, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months ... |
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Archive of Chirp Subbottom Profile Data Collected in 2019 from Cedar Island, Virginia
From August 9 to 14, 2019, researchers from the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate shoreface morphology and geology near Cedar Island, Virginia. The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. This publication serves as an archive of high-resolution ... |
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Archive of Chirp Subbottom Profile Data Collected in June 2018 From Fire Island, New York
Researchers from the U.S. Geological Survey (USGS) conducted a long-term, coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal System Change project (https://coastal.er.usgs.gov/fire-island/) objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. From ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2015 Offshore of Dauphin Island, Alabama
From September 16 through 23, 2015, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Dauphin Island, Alabama (AL). The Alabama Barrier Island Restoration Feasibility Study project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2019 from Rockaway Peninsula, New York
From September 27 through October 5, 2019, researchers from the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate shoreface morphology and geology near the Rockaway Peninsula, New York. The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. This publication serves as an ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2021 Near Pensacola Beach, Florida
From June 2 through 9, 2021, researchers from the U.S. Geological Survey (USGS) conducted an inshore and offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Pensacola Beach, Florida (FL). The Coastal Resource Evaluation for Management Applications (CREMA) project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 from Boca Chica Key, Florida
As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey at the nearshore ledge offshore of Boca Chica Key, Florida (FL) November 8-13, 2022. The objective of the project was to collect bathymetric maps and conduct a geologic assessment of the nearshore ledge off Boca Chica Key in support ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 from Seven Mile Island, New Jersey
From April 29 through May 2, 2022, researchers from the U.S. Geological Survey (USGS) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Seven Mile Island, New Jersey (NJ). The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 Offshore of Breton Island, Louisiana
On August 5, 2022, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Breton Island, Louisiana (LA). The Breton Island Post Construction Monitoring project objective includes the investigation of nearshore geologic controls on surface morphology in addition to mapping the seafloor to evaluate coastal change. This publication (Forde and others, 2023) serves as an archive of high-resolution chirp subbottom ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in June 2022 Near Panama City, Florida
As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map back-barrier and lagoonal areas, as well as characterizing stratigraphy near Panama City, Florida (FL) in June 2022. The purpose of this study was to conduct a geologic assessment (including bathymetric mapping) of the environs ... |
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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in May 2023 from Oahu, Hawaii
As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Oahu, Hawaii (HI) May 7-13, 2023. The purpose of this study was to conduct a geologic assessment (including bathymetric mapping) near Fort Hase Beach, ... |
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Archive of Chirp Sub-Bottom Profile, Imagery, and Navigational Data Collected During USGS Field Activity Numbers 2021-326-FA and 2022-326-FA in 2021 and 2022 from Duck, North Carolina
In June/December 2021 and July 2022, the U.S. Geological Survey (USGS) and U.S. Army Corps of Engineers, Engineer Research and Development Center (USACE-ERDC) conducted repeat, nearshore geologic assessments, including bathymetric mapping, near Duck, North Carolina (NC). This work was performed in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near the USACE Field Research Facility and to measure the co-evolution of the morphology and ... |
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Archive of Chirp Sub-Bottom Profile, Imagery, and Navigational Data Collected in June and August 2023 from the Chandeleur Islands, Louisiana
As part of the 2022 Disaster Supplemental project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterize stratigraphy near the Chandeleur Islands, Louisiana (LA) in June and August 2023. The purpose of this study was to conduct a morphologic and geologic assessment of the impacts of the 2020 and 2021 hurricane seasons within part of the Breton National ... |
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Archive of Chirp Sub-Bottom Profile, Imagery, and Navigational Data Collected in June and July 2014 from Fire Island, New York
During June 15-23 and July 10-12, 2014, the U.S. Geological Survey (USGS) conducted a nearshore geologic assessment, including bathymetric mapping, along Fire Island, New York (NY). This work was conducted in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near Fire Island, NY to assess the impacts of Hurricane Sandy to the area in October 2012. Geophysical data were collected as part of the Hurricane Sandy Supplemental Project (GS2-2B). The ... |
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Archive of Digitized Analog Boomer and Minisparker Seismic Reflection Data Collected from the Northern Gulf of Mexico: 1981, 1990 and 1991
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (https:/ ... |
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Archive of digitized analog boomer seismic reflection data collected along the Louisiana Shelf, 1982–1984
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (https:/ ... |
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Archive of digitized analog boomer seismic reflection data collected during U.S. Geological S cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the ... |
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Archive of digitized analog boomer seismic reflection data collected during U.S. Geological Survey cruise Acadiana 87-2 in the northern Gulf of Mexico, June 1987
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the ... |
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Archive of Digitized Analog Boomer Seismic-Reflection Data Collected During U.S. Geological Survey Cruises Erda 92-2 and Erda 92-4 in Mississippi Sound, June and August 1992
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP) (https:/ ... |
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Archive of digitized analog boomer seismic reflection data collected during USGS Cruise Kit Jones 92-1 along the Florida Shelf, July 1992
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP; https:/ ... |
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Archive of digitized analog boomer seismic reflection data collected during USGS Cruise USFHC in Mississippi Sound and Bay St. Louis, September 1989
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP, https:/ ... |
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Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: 1982, 1985, 1986, 1989, 1991, and 1992
The U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program (CMHRP) has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program ... |
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Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: Intersea 1980
The U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program (CMHRP) has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters (m) long. As part of the National Geological and Geophysical Data Preservation ... |
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Archive of Ground Penetrating Radar and Differential Global Positioning System Data Collected in April 2016 from Fire Island, New York
Researchers from the U.S. Geological Survey (USGS) conducted a long-term, coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal Change project (https://coastal.er.usgs.gov/fire-island/) objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. In April ... |
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Archive of Sediment Data Collected around the Chandeleur Islands and Breton Island in 2007 and 1987 (Vibracore Surveys: 07SCC04, 07SCC05, and 87039)
In 2006 and 2007, the U.S. Geological Survey (USGS) and collaborators at the University of New Orleans (UNO) collected high-resolution seismic profiles and subsurface cores around the Chandeleur and Breton Islands, Louisiana. To ground-truth the acoustic seismic surveys conducted in 2006, 124 vibracores were acquired during the 07SCC04 and 07SCC05 cruises in 2007. These cores were collected within the back-barrier, nearshore, and offshore environments. The surveys were conducted as part of a post-hurricane ... |
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Archive of sediment data collected from Sandy Point to Belle Pass, Louisiana, 1983 through 2000 (Vibracore surveys: 00SCC, CR83, P86, and USACE borehole cores)
In 2000, the U.S. Geological Survey (USGS), in cooperation with the University of New Orleans (UNO) and the U.S. Army Corps of Engineers (USACE), conducted geophysical surveys in Barataria Bight from Sandy Point to Belle Pass, LA (Study Area Map). Sediment cores were collected as part of the USGS Subsidence and Coastal Change (SCC) Project, which included the Barataria Sand-Resource Study (bss) vibracore surveys (Kindinger and others, 2001). This report also contains information from other cruise data sets, ... |
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Archive of Sediment Data from Vibracores Collected in 2016 from Fire Island, New York
Researchers from the U.S. Geological Survey (USGS) conducted a long-term coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal Change project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. In April 2016, scientists from the USGS St. Petersburg ... |
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ArcInfo GRID format of the 2004 Multibeam Backscatter Data in the Northeastern Channel Islands Region, Southern California [mos.zip]
ArcInfo GRID format data generated from the 2004 multibeam sonar survey of the Northeastern Channel Islands, CA Region. The data include high-resolution, acoustic, corrected backscatter. |
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ArcInfo GRID format of the 2004 Multibeam Bathymetry Data in the Northeastern Channel Islands Region, Southern California [bathy.zip]
ArcInfo GRID format data generated from the 2004 multibeam sonar survey of the Northeastern Channel Islands, CA Region. The data include high-resolution bathymetry. |
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Army Corps Sediment Data from Maine and New Hampshire acquired in 1994 (MNHACOE shapefile)
The data in this layer are from a study that evaluated and documented the historic and projected future dredging and dredged material disposal needs of the coastal rivers and harbors of the states of Maine and New Hampshire. Documentation of historic dredging and disposal activities was accomplished through the collection of data primarily from the files of the ACOE, New England Division, in Waltham, Massachusetts, supplemented by information from the states of Maine and New Hampshire and previously ... |
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ASIS2015_HRJQ_BE_z18_n88g12B_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for Coastal Topography—Assateague Island, Maryland and Virginia, Post-Hurricane Joaquin, 26 November 2015
A digital elevation model (DEM) mosaic was produced for Assateague Island, Maryland and Virginia, post-Hurricane Joaquin, from remotely sensed, geographically referenced elevation measurements collected by Quantum Spatial using a Leica ALS70 (1064-nm wavelength) lidar sensor. |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Initial_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Initial_Elevations_N.txt)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_114_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_114_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_134_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_134_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_152_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_152_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_155_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_155_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_158_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_158_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_186_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_186_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_191_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_191_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_23_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_23_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_257_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_257_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_4_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_4_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_71_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_71_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_95_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_95_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Year_30_Elevations_N)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Year_30_Elevations_NA)
Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ... |
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Atlantic and Gulf coast sandy coastline topo-bathy profile and characteristic database
Seamless topographic-bathymetric (topo-bathy) profiles and their derived morphologic characteristics were developed for sandy coastlines along the Atlantic and Gulf coasts of the United States. As such, the rocky coasts of Maine, the coral reefs in southern Florida and the Keys, and the marsh coasts in the Mississippi Delta and the Florida Big Bend region and are not included in this dataset. Topographic light detection and ranging (lidar) data (dune crest, dune toe, and shorelines) from Doran and others ... |
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Attendee Survey Results from the April and May 2020 Gulf Islands National Seashore Workshop
In early 2020, scientists gathered to advance sediment budget modeling efforts by conducting a “Needs Assessment Workshop” for the Gulf Island National Seashore (GINS) to understand the coastal processes affecting island resiliency. The “Gulf Islands Sediment Budget Needs Assessment Workshop” was held, virtually, April 23–24 and May 27–28, 2020. The workshop series was organized by researchers from North Carolina State University in collaboration with National Park Service (NPS) and U.S. ... |
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Attenuation Factor model results for Upper Floridan aquifer vulnerability to Bromacil and Ethylene Dibromide
This dataset includes Attenuation Factor (AF; Rao and others, 1985) model results for Upper Floridan aquifer vulnerability to Bromacil and 1,2-Dibromoethane or Ethylene Dibromide (EDB). The AF value serves as an index for assessing the transport of pesticide mass from the vadose zone. The AF model setup requires the input of raster soil bulk density, soil organic carbon content, soil field capacity, soil air filled porosity, recharge to the aquifer, depth to groundwater, the pesticide sorption coefficient, ... |
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BackscatterA [8101]--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterA_8101_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., ... |
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BackscatterA [8101]--Offshore Pigeon Point, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterA_8101_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, ... |
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BackscatterA [SWATH]--Offshore Aptos, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Aptos map area, California. Backscatter data are provided as two separate grids depending on mapping system and processing method. This metadata file refers to the data included in "BackscatterA_SWATH_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., ... |
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BackscatterB [7125]--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterB_7125_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., ... |
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BackscatterB [7125]--Offshore Pigeon Point, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterB_7125_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, ... |
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BackscatterB [EM300]--Offshore Aptos, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Aptos map area, California. Backscatter data are provided as two separate grids depending on mapping system and processing method. This metadata file refers to the data included in "BackscatterB_EM300_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., ... |
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BackscatterC [SWATH]--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterC_SWATH_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., ... |
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BackscatterC [SWATH]--Offshore Pigeon Point, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterC_SWATH_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson ... |
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Backscatter imagery collected in 2016 by the U.S. Geological Survey off Town Neck Beach Sandwich, Massachusetts, during field activity 2016-017-FA (GeoTIFF image)
Geophysical and geological survey data were collected off Town Neck Beach in Sandwich, Massachusetts, in May and July 2016. Approximately 130 linear kilometers of subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, sea floor photographs, and (or) video at 26 sites within the geophysical survey area. Sediment grab samples were collected at 19 of the 26 sampling sites and video and (or) photographic imagery of ... |
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Backscatter intensity and sun-illuminated topographic imagery of the seafloor in the Stellwagen Bank National Marine Sanctuary region (bcksctter.tif)
This data set contains the sun-illuminated topographic imagery and backscatter intensity generated from a multibeam sonar survey of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts, an area of approximately 1100 square nautical miles. The Stellwagen Bank NMS Mapping Project is designed to provide detailed maps of the Stellwagen Bank region's environments and habitats and the first complete multibeam topographic and sea floor characterization maps of a significant region of the ... |
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Backscatter-Oregon OCS Floating Wind Farm Site
This Data Release contains data from the U.S. Geological Survey (USGS) survey of the Oregon outer Continental shelf (OCS) Floating Wind Farm Site in 2014. The backscatter intensity data was collected along with bathymetry data by USGS during the period from August 20 to September 1, 2014, using a Reson 7111 multibeam echosounder. The mapping mission collected bathymetry data from about 163 m to 566 m depths on the Oregon outer continental shelf. The acquisition was funded by the U.S. Bureau of Ocean Energy ... |
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Backscatter [SWATH]--Offshore Santa Cruz, California
This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Santa Cruz map area, California. Backscatter data are provided as a raster file included in "Backscatter_Swath_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, ... |
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Barrier island geomorphology and seabeach amaranth metrics at 50-m alongshore transects, and 5-m cross-shore points for 2008 — Assateague Island, MD and VA.
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as piping plover ... |
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Baseline_BackBarrier.shp - Baseline Along the Back-Barrier (North-Facing) Coast of Dauphin Island, Alabama, Generated to Calculate Shoreline Change Rates.
Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ... |
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Baseline coastal oblique aerial photographs collected at Breton Island and the Chandeleur Islands, Louisiana, January 22, 2011
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On January 22, 2011, the USGS conducted an oblique aerial photographic survey at Breton Island and the Chandeleur Islands, LA, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the beach and ... |
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Baseline coastal oblique aerial photographs collected at the Chandeleur Islands, Louisiana, and Dauphin Island, Alabama, July 24, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 24, 2010, the USGS conducted an oblique aerial photographic survey at the Chandeleur Islands, Louisiana, and Dauphin Island, Alabama, aboard a Beechcraft BE90 King Air aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from Breton Island to the Chandeleur Islands, Louisiana, September 3, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 3, 2010, the USGS conducted an oblique aerial photographic survey from Breton Island to the Chandeleur Islands, Louisiana, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ... |
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Baseline coastal oblique aerial photographs collected from Dauphin Island, Alabama, to Breton Island, Louisiana, July 26–27, 2007
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 26-27, 2007, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from Dauphin Island, Alabama, to Breton Island, Louisiana, September 26–27, 2006
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 26-27, 2006, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from Dog Island, Florida, to Breton Island, Louisiana, June 24–25, 2008
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 24–25, 2008, the USGS conducted an oblique aerial photographic survey from Dog Island, Florida, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental ... |
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Baseline coastal oblique aerial photographs collected from False Cape State Park, Virginia, to Myrtle Beach, South Carolina, May 6, 2008
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 6, 2008, the USGS conducted an oblique aerial photographic survey from False Cape State Park, Virginia, to Myrtle Beach, South Carolina, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission (08CH01) was conducted to collect data ... |
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Baseline coastal oblique aerial photographs collected from Fenwick Island State Park, Delaware, to Corolla, North Carolina, March 27, 1998
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On March 27, 1998, the USGS conducted an oblique aerial photographic survey from Fenwick Island State Park, Delaware, to Corolla, North Carolina, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline Coastal oblique aerial photographs collected from Horseshoe Beach, Florida, to East Cape, Florida, May 19-20, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 19-20, 2010, the USGS conducted an oblique aerial photographic survey from Horseshoe Beach, Florida, to East Cape, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes ... |
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Baseline coastal oblique aerial photographs collected from Navarre Beach, Florida, to Breton Island, Louisiana, September 7, 2016
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 7, 2016, the USGS conducted an oblique aerial photographic survey from Navarre Beach, Florida, to Breton Island, Louisiana, aboard a Maule MT57 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ... |
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Baseline coastal oblique aerial photographs collected from Navarre, Florida, to the Chandeleur Islands, Louisiana, and from Grand Point, Alabama, to St. Joseph Point, Mississippi, June 6, 2006
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 6, 2006, the USGS conducted an oblique aerial photographic survey from Navarre, Florida, to the Chandeleur Islands, Louisiana, and from Grand Point, Alabama, to St. Joseph Point, Mississippi, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore ... |
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Baseline coastal oblique aerial photographs collected from Ponte Vedra, Florida, to the South Carolina/North Carolina border, August 24, 2011
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On August 24, 2011, the USGS conducted an oblique aerial photographic survey from Ponte Vedra, Florida, to the South Carolina/North Carolina border, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from Tampa Bay to the Marquesas Keys, Florida, June 22–23, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 22–23, 2010, the USGS conducted an oblique aerial photographic survey from Tampa Bay to the Marquesas Keys, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in ... |
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Baseline coastal oblique aerial photographs collected from the Harney River, Everglades National Park, Florida to Anclote Key, Florida, November 14, 2006
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On November 14, 2006, the USGS conducted an oblique aerial photographic survey from the Harney River, Everglades National Park, Florida to Anclote Key, Florida, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect ... |
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Baseline coastal oblique aerial photographs collected U.S. Army Corps of Engineers Field Research Facility, Duck, North Carolina, June 9, 2017
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 09, 2017, the USGS conducted an oblique aerial photographic survey of the U.S. Army Corps of Engineers Field Research Facility (USACE FRF), located in Duck, North Carolina, aboard a Cessna 182 aircraft at an altitude of approximately 1000 feet (ft). This mission was conducted to collect data for USACE FRF ... |
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Baseline_OpenOcean.shp - Baseline Along the Open-Ocean (South-Facing) Coast of Dauphin Island, Alabama, Generated to Calculate Shoreline Change Rates.
Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ... |
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Bathymetric change map of the nearshore around Ship, Horn, and Petit Bois islands, Mississippi: 1916-1920 to 2008-2009
To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Data sets include 1916 through 1920 soundings collected by the United States Coast and ... |
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Bathymetric change map of the nearshore around Ship, Horn, and Petit Bois islands, Mississippi: 1916-1920 to 2016
To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Datasets include 1916 through 1920 soundings collected by the United States Coast and ... |
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Bathymetric change map of the nearshore around Ship, Horn, and Petit Bois islands, Mississippi: 2008-2009 to 2016
To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Data sets include 1916 through 1920 soundings collected by the United States Coast and ... |
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Bathymetric data collected in the Belfast Bay, Maine pockmark field using a SWATHplus-M interferometric sonar in 2006 and 2008, by the U.S. Geological Survey (32-bit floating point raster, UTM 19 WGS 84, MLLW)
The U.S. Geological Survey, Woods Hole Coastal and Marine Science Center in cooperation with the University of Maine mapped approximately 50 square kilometers of the seafloor within Belfast Bay, Maine. Three geophysical surveys conducted in 2006, 2008 and 2009 collected swath bathymetric (2006 and 2008) and chirp seismic reflection profile data (2006 and 2009). The project characterized the spatial, morphological and subsurface variability of the Belfast Bay, Maine pockmark field. Pockmarks are large ... |
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Bathymetric Data collected with Personal Watercraft within Bellport Bay, New York, (2014) in XYZ ASCII text file format
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ... |
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Bathymetry and acoustic backscatter of Crater Lake, Oregon from Field Activity: S-1-00-OR
ArcInfo GRID format data generated from the 2000 multibeam sonar survey of Crater Lake, Oregon. The data include high-resolution bathymetry and calibrated acoustic backscatter. Data are also available as ASCII xyz format (see data download page of https://doi.org/10.3133/ds72) |
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Bathymetry from 2013 interferometric swath bathymetry systems survey of Columbia River Mouth, Oregon and Washington
This part of the USGS data release presents bathymetry data for the Columbia River Mouth, Oregon and Washington. The bathymetry data of the Columbia River Mouth, Oregon and Washington were collected by the U.S. Geological Survey (USGS). Mapping was completed in 2013, using a 234-kHz SEA SWATHPlus interferometric system. These data are not intended for navigational purposes. |
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Bathymetry Hillshade--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the shaded-relief bathymetry map of Offshore Scott Creek, California. The raster data file is included in "BathymetryHS_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., ... |
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Bathymetry Hillshade--Offshore Pigeon Point, California
This part of DS 781 presents data for the shaded-relief bathymetry map of Offshore Pigeon Point, California. The raster data file is included in "BathymetryHS_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W ... |
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Bathymetry Hillshade-Oregon OCS Floating Wind Farm Site
This Data Release contains data from the USGS survey of the Oregon OCS Floating Wind Farm Site in 2014. The shaded-relief raster was generated from bathymetry data collected by USGS during the period from August 20 to September 1, 2014. using a Reson 7111 multibeam echosounder. The mapping mission collected bathymetry data from about 163 m to 566 m depths on the Oregon outer continental shelf. The acquisition was funded by the U.S. Bureau of Ocean Energy Management. |
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Bathymetry--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the bathymetry map of Offshore Scott Creek, California. The raster data file is included in "Bathymetry_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., ... |
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Bathymetry--Offshore Pigeon Point, California
This part of DS 781 presents data for the bathymetry map of Offshore Pigeon Point, California. The raster data file is included in "Bathymetry_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P ... |
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Bathymetry of the Hudson Canyon region (100-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
The Hudson Canyon begins on the outer continental shelf off the east coast of the United States at about 100-meters (m) water depth and extends offshore southeastward across the continental slope and rise. A multibeam survey was carried out in 2002 to map the bathymetry and backscatter intensity of the sea floor of the Hudson Canyon and adjacent slope and rise. The survey covered an area approximately 205 kilometers (km) in the offshore direction, extending from about 500 m to about 4,000 m water depth, and ... |
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Bathymetry of the Sandy Hook artificial reef (2-m resolution Esri binary grid and 32-bit GeoTIFF, Mercator, WGS 84)
The Sandy Hook artificial reef, located on the sea floor offshore of Sandy Hook, New Jersey was built to create habitat for marine life. The reef was created by the placement of heavy materials on the sea floor; ninety-five percent of the material in the Sandy Hook reef is rock. In 2000, the U.S. Geological Survey surveyed the area using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard (CCG) ship Frederick G. Creed. The purpose of this multibeam survey, done in cooperation with the ... |
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Bathymetry-Oregon OCS Floating Wind Farm Site
This Data Release contains data from the U.S. Geological Survey (USGS) survey of the Oregon outer continental shelf (OCS) Floating Wind Farm Site in 2014. The bathymetry raster was generated from bathymetry data collected by USGS during the period from August 20 to September 1, 2014, using a Reson 7111 multibeam echosounder. The mapping mission collected bathymetry data from about 163 m to 566 m depths on the Oregon outer continental shelf. The acquisition was funded by the U.S. Bureau of Ocean Energy ... |
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Bathymetry tracklines collected in the Belfast Bay, Maine pockmark field using a SWATHplus-M interferometric sonar in 2006 and 2008, by the U.S. Geological Survey (Esri polyline shapefile, WGS 84)
The U.S. Geological Survey, Woods Hole Coastal and Marine Science Center in cooperation with the University of Maine mapped approximately 50 square kilometers of the seafloor within Belfast Bay, Maine. Three geophysical surveys conducted in 2006, 2008 and 2009 collected swath bathymetric (2006 and 2008) and chirp seismic reflection profile data (2006 and 2009). The project characterized the spatial, morphological and subsurface variability of the Belfast Bay, Maine pockmark field. Pockmarks are large ... |
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Beach Profile Data Collected from Madeira Beach, Florida (April 21, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (April 21, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (April 8, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (August 21, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (August 26, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (August 31, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (December 1, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (December 18, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (December 8, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected From Madeira Beach, Florida (February 17, 2017)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (February 4, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (January 15, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (January 21, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (January 24, 2018)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (January 25, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (July 10, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (July 6, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (July 6, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (July 9, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (June 10, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (June 16, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (March 3, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (March 7, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (May 23, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (May 25, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (May 9, 2017)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (November 10, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (November 14, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (November 16, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (November 2, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (November 30, 2016)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (November 6, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (November, 9 2017)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (October 15, 2018)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (October 2, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (October 5, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (September 14, 2017)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (September 15, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (September 18, 2019)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (September 21, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (September 24, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (September 8, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Madeira Beach, Florida (September 9, 2016)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (April 1, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (August 7, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (December 7, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (February 22, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (February 3, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (January 27, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (July 21, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (July 28, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (June 7, 2022)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (May 19, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (October 17, 2018)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (October 7, 2020)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (October 8, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (September 11, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (September 19, 2019)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (September 8, 2023)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach Profile Data Collected from Sand Key Beach in Clearwater, Florida (September 9, 2021)
This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ... |
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Beach profile data collected in 2010 and 2011 in the vicinity of Arey Lagoon and Barter Island, Alaska
Beach elevation profiles were measured along 29 shore-normal transects on and around Arey and Barter Islands, Alaska in August 2010 and July 2011. Profile data are available in a single comma-delimited file and a zip file including multiple .jpg images that show a visual representation of the individual profiles. |
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Beach Topography—Fire Island, New York, Pre-Hurricane Sandy, January 2012: Ground Based Lidar (1-Meter Digital Elevation Model)
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) and the U.S. Army Corps of Engineers Field Research Facility (USACE-FRF) of Duck, North Carolina collaborated to gather alongshore ground-based lidar beach topography at Fire Island, New York. This high-resolution, elevation dataset was collected on January 30, 2012, and was funded by SPCMSC. The USGS data release containing the aforementioned dataset includes the resulting, processed elevation point data (XYZ) and ... |
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Beach Topography—Fire Island, New York, Pre-Hurricane Sandy, January 2012: Ground Based Lidar (ASCII XYZ Point Data)
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) and the U.S. Army Corps of Engineers Field Research Facility (USACE-FRF) of Duck, North Carolina collaborated to gather alongshore ground-based lidar beach topography at Fire Island, New York. This high-resolution, elevation dataset was collected on January 30, 2012, and was funded by SPCMSC. The USGS data release containing the aforementioned dataset includes the resulting, processed elevation point data (XYZ) and an ... |
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Benthic Foraminiferal Data from Surface Samples and Sedimentary Cores in the Grand Bay Estuary, Mississippi and Alabama
Microfossil (benthic foraminifera) samples were obtained from surficial grab (denoted with “G”) and push core (denoted with “M”) sediments collected in Grand Bay estuary, Mississippi and Alabama, to aid in the paleoenvironmental understanding of Grand Bay estuary. The data presented here were collected as part of the U.S. Geological Survey’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, and Barrier Island Evolution Research (BIER) project. Sampling was ... |
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Biotopes of the Oregon outer continental shelf (OCS) proposed wind farm site
This biotope raster is part of a data release of the Oregon outer continental shelf (OCS) proposed wind farm map site. The biotopes mapped in this area have been numbered to indicate combinations of seafloor hardness, ruggedness and depth associated with biotopes derived by analysis of video data as described in the accompanying Open-File Report (Cochrane and others, 2017). The map was created using video and multibeam echosounder bathymetry and backscatter data collected in 2014 and processed in 2015 ... |
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BocaChica_2022_MBES: High-resolution Geophysical and Imagery Data Collected in November 2022 Offshore of Boca Chica Key, FL
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Boca Chica Key, the Florida Keys, from November 8-13, 2022. This dataset, BocaChica_2022_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid, and the dataset BocaChica_2022_MBES_Backscatter.zip ... |
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Boston Harbor and approaches samples (WILLETT72 shapefile
Boston Harbor (and its approaches) is a glacially carved, tidally dominated estuary in western Massachusetts Bay. Characterized by low river discharge and significant human impact, the harbor is typical of many bays and estuaries along the New England coast. The sands and gravels that floor Massachusetts Bay and the Harbor approaches are relict glacial sediments. However, fine-grained sediments are accumulating in areas of lower energy. |
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Bottom sample analysis and locations in the vicinity of the Woods Hole Oceanographic Institution, Martha's Vineyard Coastal Observatory (ESRI POINT SHAPEFILE, SAMPLES)
The USGS Woods Hole Science Center conducted a nearshore geophysical survey offshore of the southern coast of Martha's Vineyard, in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO) in August 2007. This mapping program was part of a larger research effort supporting the Office of Naval Research (ONR) Ripples Directed-Research Initiative (DRI) studies at MVCO by providing data collection and modeling. The geophysical data will be used to provide initial conditions for wave and circulation ... |
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Bottom Sediments -- Cape Ann to Casco Bay (FOLGER75 shapefile)
The reconnaissance maps upon which this data set is based show the areal distribution of the major bottom sediment types covering the sea floor off eastern New England between Cape Ann and Casco Bay. The maps were intended as a guide to the future mapping of gravel, sand, silt, and clay, and because these sediments reflect the hydraulic conditions, they are also helpful for deducing the important sediment transport mechanisms. |
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Bottom Sediments of Georges Bank (WIGLEY61 shapefile)
These data were collected as part of a survey of the bottom sediments of Georges Bank. The purpose of the survey was to provide basic data for use in studying the relationships between substrate composition and the occurrence of benthic animals, especially those which are common foods of fishes. Particle size composition was the principal sediment character that was studied. |
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Boulder ridges greater than or equal to 1 m high on the sea floor of the Stellwagen Bank National Marine region (ridges1.shp)
This data set contains the locations of boulder ridges greater than or equal to 1 meter in height in the Stellwagen Bank National Marine Sanctuary Region off Boston, Massachusetts, an area of approximately 1100 nautical square miles. The Stellwagen Bank NMS Mapping Project is designed to provide detailed maps of the Stellwagen Bank region's environmental habitats and the first complete multibeam topographic and sea floor characterization maps of a significant region of the shallow EEZ. The boulder ridges ... |
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Boulder ridges less than 1 m high on the sea floor of the Stellwagen Bank National Marine Sanctuary region (ridges0.shp)
This data set contains the locations of boulder ridges that are less than 1 meter in height in the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts, an area of approximately 1100 nautical square miles. The Stellwagen Bank NMS Mapping Project is designed to provide detailed maps of the Stellwagen Bank region's environments and habitats and the first complete multibeam topographic and sea floor characterization maps of a significant region of the shallow EEZ. The boulder ridges ... |
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Bulk organic matter and carbonate content of sediment cores from the Currituck Landslide Complex and upper slope adjacent to Baltimore Canyon collected on USGS Field Activity 2012-007-FA
Twenty-four piston cores (and associated trigger cores) were collected from the source zone of the Currituck Landslide Complex and upper slope adjacent to Baltimore Canyon by the U.S. Geological Survey and the University of Rhode Island Department of Ocean Engineering during an eight-day cruise aboard the R/V Hugh R. Sharp in September/October of 2012. These cores were analyzed for evidence of seafloor mass transport processes, with an emphasis on constraining the age and shallow stratigraphy of the ... |
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Bulk organics and carbonate content of sediment cores from the New England Mud Patch collected on USGS Field Activity 2016-001-FA
Variability in sediment properties with depth and the thickness of individual sedimentary layers are critical determinants of seabed acoustic response. The New England Mud Patch (NEMP), located south of Cape Cod, is an unusual feature on the U.S. Continental Shelf in that it is composed of fine-grained sediment layers containing a relatively-homogeneous mix of sand, silt, and clay-sized particles bounded by more typical sandy shelf sediments. The unique characteristics and nature of this deposit is due to ... |
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CACO2002_EAARLA_BE_z19_n88g12B_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ... |
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CACO2002_EAARLA_BE_z19_n88g12B_mosaic_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: Bare Earth
A bare-earth topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system ... |
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CACO2002_EAARLA_FS_z19_n88g12B_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: First Surface
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ... |
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CACO2002_EAARLA_FS_z19_n88g12B_mosaic_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: First Surface
A first-surface topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging ... |
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Cape Canaveral, Florida, backscatter data collected in 2016 by Coastal Carolina University: Processed GeoTIFF Image
A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data. |
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Cape Canaveral, Florida, multibeam bathymetry collected in 2016 by Coastal Carolina University: Processed elevation point data (XYZ)
A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data. |
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Cape Canaveral, Florida, multibeam bathymetry collected in 2016 by Coastal Carolina University: Processed GeoTIFF Image
A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data. |
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Cape Canaveral, Florida, seismic chirp collected in 2016 by Coastal Carolina University
A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data. |
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Cape Canaveral, Florida side scan sonar data collected in 2016 by Coastal Carolina University: Processed GeoTIFF Image
A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data. |
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Cape Canaveral tracklines of geophysical data collected in 2016 by Coastal Carolina University
A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data. |
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Carbon isotopes data for rock samples from Von Damm vent field, Mid-Cayman Rise
This portion of the data release presents stable carbon isotopes of rock samples collected from Von Damm vent field, Mid-Cayman Rise, in the Caribbean Sea. These data were collected in 2020 (USGS Field Activity 2020-602-FA). |
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CatIsland_2010_Bathy_NAVD88_grid.tif
In September and October of 2010, the U.S. Geological Survey (USGS), in cooperation with the Army Corps of Engineers (USACE), conducted geophysical surveys around Cat Island, Miss. to collect bathymetry, acoustical backscatter, and seismic reflection data (seismic-reflection data have been published separately, Forde and others, 2012). The geophysical data along with sediment vibracore data (yet to be published) will be integrated to analyze and produce a report describing the geomorphology and geologic ... |
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CatIsland_2010_Bathy_Swath_tracklines
In September and October of 2010, the U.S. Geological Survey (USGS), in cooperation with the Army Corps of Engineers (USACE), conducted geophysical surveys around Cat Island, Miss. to collect bathymetry, acoustical backscatter, and seismic reflection data (seismic-reflection data have been published separately, Forde and others, 2012). The geophysical data along with sediment vibracore data (yet to be published) will be integrated to analyze and produce a report describing the geomorphology and geologic ... |
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CatIsland 2010 single-beam bathymetry tracklines
In September and October of 2010, the U.S. Geological Survey (USGS), in cooperation with the Army Corps of Engineers (USACE), conducted geophysical surveys around Cat Island, Miss. to collect bathymetry, acoustical backscatter, and seismic reflection data (seismic-reflection data have been published separately, Forde and others, 2012). The geophysical data along with sediment vibracore data (yet to be published) will be integrated to analyze and produce a report describing the geomorphology and geologic ... |
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Cat Island Terrestrial Core Optically Stimulated Luminescence (OSL) Data from field activity 10BIM03
Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain. The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the ... |
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CCALBATC - bathymetric contours for the central California region between Point Arena and Point Sur.
CCALBATC consists of bathymetric contours at 10-m and 50-m intervals for the area offshore of central California between Point Arena to the north and Point Sur to the south. The lines were digitized from 1:250,000-scale NOAA charts. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Monterey Bay National Marine Sanctuary Project (see this and other older Monterey Bay USGS works archived at https: ... |
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Chenier_Plain_2017_SBB_200m_DEM_metadata: Nearshore Single-Beam Bathymetry XYZ Data Collected in 2017 from the Chenier Plain, Louisiana
As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana's coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in ... |
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Chenier_Plain_2017_SBB_ITRF00_Trackline_metadata: Nearshore Single-Beam Bathymetry XYZ Data Collected in 2017 from the Chenier Plain, Louisiana
As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana’s coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described ... |
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Chenier_Plain_2017_SBB_XYZ_metadata: Nearshore Single-Beam Bathymetry XYZ Data Collected in 2017 from the Chenier Plain, Louisiana
As a part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the Chenier Plain, Louisiana from Marsh Island to Sabine Pass. The goal of the BICM program is to provide long-term data on Louisiana's coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in ... |
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Chirp seismic reflection data from the Edgetech 512i collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS field activity 2018-001-FA (shotpoints point shapefile, survey trackline shapefile, PNG profile images, and SEG-Y trace data).
The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg ... |
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Chirp seismic reflection data- shotpoints, tracklines, profile images, and SEG-Y traces for EdgeTech 3400 chirp data collected during USGS field activity 2022-001-FA (point and polyline shapefiles, CSV text, PNG Images, and SEGY data, GCS WGS 84)
In June 2022, the U.S. Geological Survey, in collaboration with the Massachusetts Office of Coastal Zone Management, collected high-resolution geophysical data, in Nantucket Sound to understand the regional geology in the vicinity of Horseshoe Shoal. This effort is part of a long-term collaboration between the USGS and the Commonwealth of Massachusetts to map the State’s waters, support research on the Quaternary evolution of coastal Massachusetts, resolve the influence of sea-level change and sediment ... |
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Chirp seismic reflection - shotpoints, tracklines, profile images, and SEG-Y traces for EdgeTech SB-424 chirp data collected during USGS field activity 2021-004-FA (point and polyline shapefiles, CSV text, PNG Images, and SEGY data, GCS WGS 84)
The U.S. Geological Survey (USGS) Woods Hole Coastal and Marine Science Center (WHCMSC) completed a bathymetric and shallow seismic-reflection survey during the period of June 9, 2021 to June 24, 2021 in water depths from 2 m to 30 m for a portion of the outer Cape Cod nearshore environment between Marconi and Nauset Beaches. The products from this survey will help to support white shark research on their shallow-water behavior in the dynamic nearshore environment at Cape Cod National Seashore (CACO). CACO ... |
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Chirp seismic reflection - shotpoints, tracklines, profile images, and SEG-Y traces for EdgeTech SB-512i chirp data collected during USGS field activity 2017-002-FA.
In spring and summer 2017, the U.S. Geological Survey’s Gas Hydrates Project conducted two cruises aboard the research vessel Hugh R. Sharp to explore the geology, chemistry, ecology, physics, and oceanography of sea-floor methane seeps and water column gas plumes on the northern U.S. Atlantic margin between the Baltimore and Keller Canyons. Split-beam and multibeam echo sounders and a chirp subbottom profiler were deployed during the cruises to map water column backscatter, sea-floor bathymetry and ... |
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Chirp seismic reflection - shotpoints, tracklines, profile images, and SEG-Y traces for EdgeTech SB-512i chirp data collected during USGS field activity 2019-002-FA (point and polyline shapefiles, CSV text, PNG Images, and SEGY data, GCS WGS 84)
Accurate data and maps of sea floor geology are important first steps toward protecting fish habitat, delineating marine resources, and assessing environmental changes due to natural or human impacts. To address these concerns the U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management (CZM), comprehensively mapped the Cape Cod Bay sea floor to characterize the surface and shallow subsurface geologic framework. Geophysical data collected include swath bathymetry, ... |
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Coastal and Marine Ecological Classifcation Standard (CMECS) geoforms of the Oregon outer continental shelf (OCS) proposed wind farm site
This polygon shapefile is part of a data release of the Oregon outer continental shelf (OCS) proposed wind farm map site. The polygons have attribute values for Coastal and Marine Ecological Classification Standard (CMECS) geoforms, substrate, and modifiers. CMECS is the U.S. government standard for marine habitat characterization and was developed by representatives from a consortium of federal agencies. The standard provides an ecologically relevant structure for biologic, geologic, chemical, and physical ... |
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Coastal bathymetry data collected between 2008 and 2009 offshore of the Mississippi and Alabama barrier islands: Processed elevation point data
During the summers of 2008 and 2009 the United States Geological Survey (USGS) conducted bathymetric surveys from West Ship Island, Mississippi, to Dauphin Island, Alabama, as part of the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility project. The survey area extended from the shoreline out to approximately two kilometers and included the adjacent passes. These findings were originally published in Dewitt and others (2012). This USGS data release includes updated elevation point ... |
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Coastal Bathymetry Data Collected in 2016 from the Chandeleur Islands, Louisiana–Interferometric Bathymetry Soundings (XYZ)
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected single beam and swath bathymetry data from the northern Chandeleur Islands, Louisiana, in June of 2016. This USGS data release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). This USGS data release provides 208-line kilometers (km) of processed interferometric bathymetry (IFB) data collected under Field Activity Number (FAN) 2016-335-FA. This FAN ... |
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Coastal Bathymetry Data Collected in 2016 from the Chandeleur Islands, Louisiana–Interpolated Digital Elevation Model
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected single beam and swath bathymetry data from the northern Chandeleur Islands, Louisiana, in June of 2016. This USGS data release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). This USGS data release provides 437-line kilometers (km) of processed single beam bathymetry (SBB) and interferometric bathymetry (IFB) data collected under Field Activity ... |
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Coastal Bathymetry Data Collected in 2016 from the Chandeleur Islands, Louisiana–Single Beam Bathymetry Soundings (XYZ)
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected single beam and swath bathymetry data from the northern Chandeleur Islands, Louisiana, in June of 2016. This USGS data release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). This USGS data release provides 229-line kilometers (km) of processed single beam bathymetry (SBB) data collected under Field Activity Number (FAN) 2016-335-FA. This FAN ... |
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Coastal Bathymetry Data Collected in 2016 nearshore from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi, U.S. Geological Survey (USGS).
The United States Geological Survey Saint Petersburg Coastal and Marine Science Center (USGS SPCMSC), in cooperation with the United States Army Corps of Engineers (USACE) conducted bathymetric surveys of the nearshore waters surrounding Ship and Horn Islands, Gulf Islands National Seashore, Mississippi (GUIS). Camille Cut separates Ship Island into East Ship Island and West Ship Island. The objective of this study was to establish base-level elevation conditions around West Ship Island, East Ship Island, ... |
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Coastal Bathymetry Data Collected in June 2018 from Fire Island, New York: Wilderness Breach and Shoreface
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, June 2?17, 2018. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach and the adjacent shoreface environment. During this study, bathymetry data were collected aboard two personal watercraft (PWC) outfitted with single-beam echosounders, as well ... |
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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ... |
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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Fabric Dataset
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ... |
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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Hazard Impact Type
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ... |
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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Maximum Change Likelihood
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ... |
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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Perpetual Hazards
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ... |
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Coastal Features Extracted from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York, 2008-2022
This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery from Delaware Bay, New Jersey (NJ) to Shinnecock Bay, New York (NY). A total of 119 images acquired between 2008 and 2022 were analyzed to produce 143 thematic land-cover raster datasets. Water, bare earth (sand), and vegetated land-cover classes were mapped using successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare ... |
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Coastal Features Extracted from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019
The data release (Bernier, 2021) associated with this metadata record serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize the effects of tidal water-level variations, 75 cloud-free, low-water images acquired between 1984 and 2019 were analyzed. Water, bare earth (sand), vegetated, and intertidal land-cover classes were mapped from Hewes Point to Palos Island using successive thresholding and masking ... |
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Coastal Groundwater Chemical Data from the North and South Shores of Long Island, New York
Groundwater data were collected in the spring and fall of 2008 from three sites representing different geological settings and biogeochemical conditions within the surficial glacial aquifer of Long Island, NY. Investigations were designed to examine the extent to which average vadose zone thickness in contributing watersheds controlled biogeochemical conditions and processes, including dissolved oxygen concentration (DO), oxidation-reduction potential (Eh), dissolved organic carbon concentration (DOC), and ... |
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Coastal Interferometric Swath Bathymetry Data Collected in 2015 from the Chandeleur Islands, Louisiana: 2015_Chand_IFB_5m_NAD83_NAVD88_GEOID09_DEM
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected swath bathymetry data offshore of the Northern Chandeleur Islands, Louisiana in September 2015. This USGS Data Release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). For further information regarding data collection and/or processing methods, refer to previously published USGS Data Series 847 and 848 (https://doi.org/10.3133/ds8487 and https:/ ... |
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Coastal Interferometric Swath Bathymetry Data Collected in 2015 from the Chandeleur Islands, Louisiana: 2015_Chand_IFB_5m_NAD83_NAVD88_GEOID09_XYZ
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected swath bathymetry data offshore of the Northern Chandeleur Islands, Louisiana in September 2015. This USGS Data Release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). For further information regarding data collection and/or processing methods, refer to previously published USGS Data Series 847 and 848 (https://doi.org/10.3133/ds8487 and https:/ ... |
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Coastal Interferometric Swath Bathymetry Data Collected in 2015 from the Chandeleur Islands, Louisiana: 2015_Chand_IFB_5m_WGS84_XYZ
The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC), collected swath bathymetry data offshore of the Northern Chandeleur Islands, Louisiana in September 2015. This USGS Data Release includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM). For further information regarding data collection and/or processing methods, refer to previously published USGS Data Series 847 and 848 (https://doi.org/10.3133/ds8487 and https:/ ... |
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Coastal Land-Cover Data Derived from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York, 2008-2022
This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery from Delaware Bay, New Jersey (NJ) to Shinnecock Bay, New York (NY). A total of 119 images acquired between 2008 and 2022 were analyzed to produce 143 thematic land-cover raster datasets. Water, bare earth (sand), and vegetated land-cover classes were mapped using successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare ... |
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Coastal Land-Cover Data Derived from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019
The data release (Bernier, 2021) associated with this metadata record serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize the effects of tidal water-level variations, 75 cloud-free, low-water images acquired between 1984 and 2019 were analyzed. Water, bare earth (sand), vegetated, and intertidal land-cover classes were mapped from Hewes Point to Palos Island using successive thresholding and masking ... |
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Coastal Marine Geology Program Video and Photograph Portal
Access to the U.S. Geological Survey (USGS) Coastal and Marine Geology Program’s (CMGP) vast collection of unique and valuable seafloor and coastal imagery is made available in the CMGP Video and Photograph Portal. The portal provides a single location for data discovery and viewing. The CMGP and our research partners invest immense resources collecting, processing, and archiving seafloor and oblique coastal video and photographs. Until the publication of the CMGP Video and Photograph Portal in 2015, only ... |
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Coastal Multibeam Bathymetry and Backscatter Data Collected in June 2021 from Rockaway Peninsula, New York
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), June 18-25, 2021. This dataset, Rockaway_2021_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid and the dataset Rockaway_2021_MBES ... |
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Coastal Multibeam Bathymetry and Backscatter Data Collected in May 2021 From Seven Mile Island, New Jersey
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore extent of Seven Mile Island, New Jersey, from May 19-23, 2021. The download file, 7Mile_2021_MBES_xyz.zip, includes processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. The download file, 7Mile_2021_MBES ... |
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Coastal Multibeam Bathymetry and Backscatter Data Collected in May 2023 from Rockaway Peninsula, New York
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), from May 6-16, 2023. This dataset, Rockaway_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid and the dataset Rockaway_2023_MBES ... |
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Coastal Multibeam Bathymetry and Backscatter Data Collected in May 2023 From Seven Mile Island, New Jersey
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore extent of Seven Mile Island, New Jersey (NJ), from May 18-27, 2023. The download file, 7Mile_2023_MBES_xyz.zip, includes processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. The download file, 7Mile_2023_MBES ... |
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Coastal Multibeam Bathymetry and Backscatter Data Collected in October 2019 from Rockaway Peninsula, New York: Leg 1
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), from October 4-6, 2019. This dataset, Rockaway_2019_MBES_Leg1_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid from the first leg of the ... |
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Coastal Multibeam Bathymetry and Backscatter Data Collected in October 2019 from Rockaway Peninsula, New York: Leg 2
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), from October 24-29, 2019. This dataset, Rockaway_2019_MBES_Leg2_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid from the second leg of ... |
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Coastal Multibeam Bathymetry Data Collected in 2018 Offshore of Seven Mile Island, New Jersey
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of Seven Mile Island, New Jersey, September 6-8, 2018 and September 21-23, 2018. This dataset, presented as Seven_Mile_Island_2018_MBES_WGS84_UTM18N_xyz.zip and Seven_Mile_Island_2018_MBES_NAD83_NAVD88_GEOID12B_xyz.zip, includes the processed elevation point data ... |
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Coastal Multibeam Bathymetry Data Collected in 2019 off of Santa Rosa Island, Florida
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of Santa Rosa Island, Florida (FL), June 15-29, 2019. This dataset, Santa_Rosa_Island_2019_MBES_UTM16N_xyz.zip, includes the processed elevation point data (XYZ) as derived from a 1-meter (m) bathymetric grid. |
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Coastal Multibeam Bathymetry Data Collected in August 2017 from the Chandeleur Islands, Louisiana
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of the Chandeleur Islands, Louisiana, August 9-12, 2017. This dataset, Chandeleur_Islands_2017_MBB_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. |
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Coastal Multibeam Bathymetry Data Collected in August 2018 from the Chandeleur Islands, Louisiana
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of the Chandeleur Islands, Louisiana, August 16-21, 2018. This dataset, Chandeleur_ Islands_2018_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. |
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Coastal Multibeam Bathymetry Data Collected in August 2019 from Cedar Island, Virginia
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), covering the nearshore, seaward of Cedar Island, Virginia, from August 14-21, 2019. This dataset, Cedar_ Island_2019_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. Additionally, the dataset Cedar_Island ... |
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Coastal Multibeam Bathymetry Data Collected in August 2022 From Breton Island, Louisiana
An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, Gulf side of Breton Island, Louisiana (LA), from August 2-5, 2022. This dataset, Breton_2022_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. |
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Coastal Single-beam Bathymetry Data Collected in 2022 From Breton Island, Louisiana
As part of the restoration monitoring component of the Deepwater Horizon early restoration project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted single-beam and multibeam bathymetry surveys around Breton Island, Louisiana (LA), from August 3-5, 2022, for Field Activity Number (FAN) 2022-328-FA. The purpose of data collection was to develop a baseline digital elevation model of the seafloor around Breton Island for comparison with both ... |
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Coastal Single-beam Bathymetry Data Collected in 2022 off Seven Mile Island, New Jersey
To determine continued change to the shoreface morphology and evolution at Seven Mile Island, New Jersey, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of Seven Mile Island, New Jersey, from April 29 - May 2, 2022. During this study, single-beam bathymetry data were collected using a personal watercraft (PWC) and a floating-towed-seismic sled. Both the PWC and the seismic sled ... |
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Coastal Single-beam Bathymetry Data Collected in August 2018 from the Chandeleur Islands, Louisiana
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS - SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of the northern Chandeleur Islands, August 17-21, 2018. During this study, bathymetry data were collected aboard the research vessel (R/V) Jabba Jaw, a 21-foot (ft) twin hulled vessel outfitted with a single-beam echosounder. |
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Coastal Single-beam Bathymetry Data Collected in August 2019 from Cedar Island, Virginia
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS - SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of Cedar Island, Virginia, August 9-15, 2019. During this study, bathymetry data were collected aboard a towed seismic sled outfitted with a single-beam echosounder. |
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Coastal Single-beam Bathymetry Data Collected in September and October 2019 from Rockaway Peninsula, New York
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS - SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of Rockaway Peninsula, New York September 27 - October 6, 2019. During this study, bathymetry data were collected aboard two personal watercraft (PWC) outfitted with single-beam echosounders, as well as a towed seismic sled with similar instrumentation. |
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Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation
Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or ‘label images’) collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial oblique and nadir imagery. Images include a diverse range of coastal environments from the U.S. Pacific, Gulf of Mexico, ... |
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CoconutIsland_2023_MBES: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii
An Ellipsoidally Referenced Survey (ERS) using a Norbit Winghead multibeam echosounder, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Coconut Island, on the island of Oahu, May 7, 2023. This dataset, CoconutIsland_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 0.25 meter (m) bathymetric grid and the dataset CoconutIsland_2023_MBES_Backscatter.zip includes the acoustic backscatter intensity ... |
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Cold-water coral metagenomes (Lophelia pertusa) from the Gulf of Mexico and Atlantic Ocean: raw data
In 2009, three unique colonies of the cold-water coral Lophelia pertusa were sampled in the western Atlantic Ocean to examine their microbial metagenomes. Nine additional samples were collected from three sites (Viosca Knoll 826, Viosca Knoll 906, and West Florida Slope) around the Gulf of Mexico in 2009 and 2010. Previous studies have examined the bacterial associates of this coral, but to date, no cold-water coral metagenomes have been published. This analysis characterized and identified microbial ... |
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Cold-water coral microbiomes (Astrangia poculata) from Narragansett Bay: sequence data
The files provided in this data release are the DNA sequence files referenced in Goldsmith and others (2019), which represent a 16S ribosomal ribonucleic acid (rRNA) gene amplicon survey of Astrangia poculata microbiomes completed using Sanger dideoxy sequencing. The coral samples were collected from Narragansett Bay at Fort Wetherill State Park, Jamestown, Rhode Island in 2015 and 2016 (Sharp and others, 2017). Sequences were obtained by first extracting DNA from a fragment of each A. poculata sample ... |
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Cold-water coral microbiomes (Lophelia pertusa) from Gulf of Mexico and Atlantic Ocean: raw data
The files in this data release are the raw deoxyribonucleic acid (DNA) sequence files referenced in the submitted journal article by Christina A. Kellogg, Dawn B. Goldsmith and Michael A. Gray entitled "Biogeographic comparison of Lophelia-associated bacterial communities in the western Atlantic reveals conserved core microbiome". They represent a 16S ribosomal ribonucleic acid (rRNA) gene amplicon survey of the coral’s microbiomes completed using Roche 454 pyrosequencing with Titanium series reagents. ... |
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Cold-water coral microbiomes (Primnoa spp.) from Gulf of Alaska, Baltimore Canyon, and Norfolk Canyon: raw data
The files in this data release are the raw DNA sequence files referenced in the journal article by Goldsmith and others (2018) entitled "Comparison of microbiomes of cold-water corals Primnoa pacifica and Primnoa resedaeformis, with possible link between microbiome composition and host genotype". They represent a 16S ribosomal ribonucleic acid (rRNA) gene amplicon survey of the corals’ microbiomes (Primnoa spp.) completed using Roche 454 pyrosequencing with Titanium series reagents. The 16S rRNA gene ... |
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Collection locations of sediment cores from the New England Mud Patch collected on USGS Field Activity 2016-001-FA
Variability in sediment properties with depth and the thickness of individual sedimentary layers are critical determinants of seabed acoustic response. The New England Mud Patch (NEMP), located south of Cape Cod, is an unusual feature on the U.S. Continental Shelf in that it is composed of fine-grained sediment layers containing a relatively-homogeneous mix of sand, silt, and clay-sized particles bounded by more typical sandy shelf sediments. The unique characteristics and nature of this deposit is due to ... |
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Collections inventory for the U.S. Geological Survey Woods Hole Coastal and Marine Science Center Samples Repository (ver. 2.0, September 2023)
Since 2002, the Woods Hole Coastal and Marine Science Center’s Samples Repository supports research by providing secure storage for geological, biological, and geochemical samples; maintaining organization and an active inventory of these sample collections; and providing access to these collections for study and reuse. This collections inventory has been compiled, organized, and released as a searchable database to provide researchers and the general public with means to discover and request scientific ... |
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Computed tomography (CT) scans of push cores from Loki's Castle and Favne vent fields, Mohns Ridge
This portion of the data release presents computed tomography (CT) images from push cores collected from Loki's Castle and Favne vent fields, on the Mohns Ridge, in the Norwegian Sea. These data were collected in 2018 and 2019 (USGS Field Activity 2018-691-DD and 2019-624-FA). A Geotek Rotating X-Ray CT (RXCT) system was used to acquire x-ray images and perform CT reconstructions of unsplit core segments. The full three-dimensional data set consists of individual axial slices which are reconstructed images ... |
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Continental Margin Mapping Program (CONMAP) sediments grainsize distribution for the United States East Coast Continental Margin (CONMAPSG)
Sediments off the eastern United States vary markedly in texture - the size, shape, and arrangement of their grains. However, for descriptive purposes, it is typically most useful to classify these sediments according to their grain-size distributions. Starting in 1962, the U.S. Geological Survey (USGS) and the Woods Hole Oceanographic Institution (WHOI) began a joint program to study the marine geology of the continental margin off the Atlantic coast of the United States. As part of this program and ... |
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Continuous Resistivity Profiling, Electrical Resistivity Tomography and Hydrologic Data Collected in 2017 from Indian River Lagoon, Florida
Extending 200 kilometers (km) along the Atlantic Coast of Central Florida, Indian River Lagoon (IRL) is one of the most biologically diverse estuarine systems in the continental United States. The lagoon is characterized by shallow, brackish waters and a width that varies between 0.5 and 9.0 km; there is significant human development along both shores. Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center used continuous resistivity profiling (CRP, a towed ... |
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Contours--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore Scott Creek map area, California. The vector data file is included in "Contours_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., ... |
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Coral cores collected in Dry Tortugas National Park, Florida, U.S.A.: Photographs and X-rays
Cores from living coral colonies were collected from Dry Tortugas National Park, Florida, to obtain skeletal records of past coral growth and allow geochemical reconstruction of environmental variables during the corals’ centuries-long lifespans. The samples were collected as part of the U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies project (http://coastal.er.usgs.gov/crest/) that provides science to assist resource managers tasked with the stewardship of coral reef resources. Three colonies ... |
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Coral microbiome preservation and extraction method comparison of samples collected in March and August 2018-raw data
The files in this this U.S. Geological Survey (USGS) data release (Kellogg and others, 2021) are the raw 16S ribosomal ribonucleic acid (rRNA) gene amplicon deoxyribonucleic acid (DNA) sequence files from 90 samples of tropical and cold-water corals, as well as sequence files from a mock community and extraction blanks for the kits used for DNA extraction. The mock community was sequenced in order to assess any biases in the sequencing technology, while extraction blanks were sequenced in order to identify ... |
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Core descriptions and sedimentologic data from vibracores and sand augers collected in 2021 and 2022 from Fire Island, New York
In 2021 and 2022, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS New York Water Science Center (NYWSC), on behalf of SPCMSC, conducted sediment sampling and ground penetrating radar (GPR) surveys at Point O' Woods and Ho-Hum Beach (NYWSC, 2021) and Watch Hill, Long Cove, and Smith Point (SPCMSC, 2022), Fire Island, New York. These data complement previous SPCMSC GPR and sediment sampling surveys conducted at Fire Island in 2016 ... |
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Core descriptions and sedimentologic data from vibracores collected in 2021 from Central Florida Gulf Coast Barrier Islands
In 2021, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted ground penetrating radar (GPR) and sediment sampling surveys on barrier islands located along the central Florida Gulf Coast (CFGC), Pinellas County, Florida (FL). This study investigated the past evolution of the CFGC from field sites at Anclote Keys, Caladesi and Honeymoon Islands, and Fort DeSoto to quantify changes that occurred along these barrier systems prior to the 20th ... |
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Core logger data from vibracores collected offshore Oceanside to San Diego, southern California, during field activity 2018-638-FA from 2018-05-22 to 2018-05-26
This section of the data release contains core logger tabular data of 41 vibracores that were collected aboard the R/V Bold Horizon in 2018 on U.S. Geological Survey Field Activity 2018-638-FA offshore Oceanside to San Diego, southern California. The cores were analyzed for sound velocity (P-wave) and gamma ray density. The logging was performed at 1-cm intervals from the top of each core section. In addition to the core logger data, the location of the cores are available as either a comma-delimited file ... |
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Core logger data from vibracores collected offshore San Francisco, California, during field activity 2019-649-FA from 2019-10-11 to 2019-10-18
This section of the data release contains core logger tabular data of 34 vibracores that were collected aboard the R/V Bold Horizon in 2019 on U.S. Geological Survey Field Activity 2019-649-FA offshore San Francisco, California. The cores were analyzed for gamma ray density and magnetic susceptibility. The logging was performed at 1-cm intervals from the top of each core section. In addition to the core logger data, the locations of the cores are available as either a comma-delimited file or a shapefile. |
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CRLS97007 sidescan-sonar track lines on the inner continental shelf off the northern Oregon and southern Washington coast from U.S. Geological Survey field activity 1997-007-FA
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan-sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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CRLS98014 sidescan-sonar track lines on the inner continental shelf off the northern Oregon and southern Washington coast from U.S. Geological Survey field activity 1998-014-FA
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan-sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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Crocker Reef, Florida, 2016-2017 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2017 at Crocker Reef near Islamorada, Florida (FL), within a 33.62 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2016 and 2017 using ... |
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Crocker Reef, Florida, 2017-2018 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2017 and 2018 at Crocker Reef near Islamorada, Florida (FL), within a 6.11 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2019) derived from an elevation-change analysis between two elevation datasets acquired in 2017 and 2018 using ... |
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Database for the U.S. Geological Survey Woods Hole Science Center's marine sediment samples, including locations, sample data and collection information (SED_ARCHIVE)
The U.S. Geological Survey (USGS), Woods Hole Science Center (WHSC) has been an active member of the Woods Hole research community for over 40 years. In that time there have been many sediment collection projects conducted by USGS scientists and technicians for the research and study of seabed environments and processes. These samples are collected at sea or near shore and then brought back to the WHSC for study. While at the Center, samples are stored in ambient temperature, cold or freezing conditions, ... |
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Data for evaluating the Sr/Ca temperature proxy with in-situ temperature in the western Atlantic coral Siderastrea siderea
Massive corals are used as environmental recorders throughout the tropics and subtropics to study environmental variability during time periods preceding ocean-observing instrumentation. However, careful testing of paleoproxies is necessary to validate the environmental-proxy record throughout a range of conditions experienced by the recording organisms. As part of the USGS Coral Reef Ecosystems Studies project (http://coastal.er.usgs.gov/crest/), we tested the hypothesis that the coral Siderastrea siderea ... |
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Data from Oceanographer, Lydonia, and Gilbert Canyons acquired in 1965 (SCHWARTZ65 shapefile)
Submarine canyons occur at the edge of the continental shelf and cut across the slope and rise along the U.S. east coast. Three of these canyons (Oceanographer, Lydonia, and Gilbert) are situated south of Georges Bank. Gravity cores and grab samples were collected as part of a study of the active processes and sediment distributions within these features. The results of the textural analyses are contained in this data layer. |
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Data Layer Containing the Features Interpreted to be on the Sea Floor within the National Oceanic and Atmospheric Administration (NOAA) H11255 Survey Area in Southeastern Long Island Sound (H11255INTERP.SHP, Geographic)
Digital terrain models (DTMs) produced from multibeam bathymetric data provide valuable base maps for marine geological interpretations. These maps help define the geological variability of the seafloor (one of the primary controls of benthic habitat diversity); improve our understanding of the processes that control the distribution and transport of bottom sediments, and the distribution of benthic habitats and associated infaunal community structures; and provide a detailed framework for future research, ... |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 2 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 3 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 4 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 5 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 6 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 7 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Initial DEMs with and without restoration alternatives R2-R7
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Hindcast Model Inputs and Results: Final DEM
The model output of bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in USGS Open-File Report 2019–1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020). |
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Dauphin Island Decadal Hindcast Model Inputs and Results: Initial DEM
The model input for the bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in U.S. Geological Survey (USGS) Open-File Report 2019-1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020). |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Intermediate-Low Sea Level Rise (SLR) Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Low Sea Level Rise (SLR) Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Present-Day Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Intermediate-Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
Info |
Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
Info |
Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Intermediate-Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Present-Day Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assateague Island, MD & VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Hatteras, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Lookout, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cedar Island, VA, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cedar Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Coast Guard Beach, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cobb Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Metompkin Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Monomoy Island, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Myrtle Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parker River, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parramore Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rhode Island National Wildlife Refuge, RI, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Ship Shoal Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Smith Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Wreck Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Deep-Towed Chirp Profiles of the Blake Ridge Collapse Structure Collected on USGS cruises 92023 and 95023 Aboard the R/V Cape Hatteras in 1992 and 1995
This CD-ROM contains copies of the navigation and deep-towed chirp subbottom data collected aboard the R/V Cape Hatteras,on cruises 92023 and 95023 in 1992 and 1995 respectively. This CD-ROM is (Compact Disc-Read Only Memory UDF (Universal Disc Format) CD-ROM Standard (ISO 9660 equivalent). The HTML documentation is written utilizing some HTML 4.0 enhancements. The disk should be viewable by all WWW browsers but may not properly format on some older WWW browsers. Also, some links to USGS collaborators and ... |
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Defined Map Units of the seafloor of Boston Harbor and Approaches (BOTTOMTYPE, UTM 19, WGS84)
This data is a qualitatively-derived interpretative polygon shapefile defining the bottom types of the seafloor from Boston Harbor and the harbor approaches, Massachusetts. Approximately 170 km square of sidescan sonar and bathymetric data were collected by the National Oceanic and Atmospheric Administration (NOAA) Ship Whiting in 2000 and 2001 and reprocessed and gridded by the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS). |
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Delineated Coastal Cliff Toes Derived from Post-Hurricane Maria Lidar Elevation Data Collected from Puerto Rico: 2018
The National Assessment of Coastal Change Hazards project aims to understand and forecast coastal landscape change. This dataset consists of delineated coastal cliff toes that may be used to assess the hazard posed by eroding coastal cliffs on the islands of Puerto Rico, Culebra, and Vieques. The delineation of cliff tops and toes can be used as an input into cliff hazard metrics and to measure overall cliff changes over time. Cliff tops and cliff toes were identified along three-dimensional (3D) transects ... |
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Delineated Coastal Cliff Tops Derived from Post-Hurricane Maria Lidar Elevation Data Collected from Puerto Rico: 2018
The National Assessment of Coastal Change Hazards project aims to understand and forecast coastal landscape change. This dataset consists of delineated coastal cliff tops that may be used to assess the hazard posed by eroding coastal cliffs on the islands of Puerto Rico, Culebra, and Vieques. The delineation of cliff tops and toes can be used as an input into cliff hazard metrics and to measure overall cliff changes over time. Cliff tops and cliff toes were identified along three-dimensional (3D) transects ... |
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Delineated Coastal Cliff Transects Derived from Post-Hurricane Maria Lidar Elevation Data Collected from Puerto Rico: 2018
The National Assessment of Coastal Change Hazards project aims to understand and forecast coastal landscape change. This dataset consists of delineated coastal cliff transects that may be used to assess the hazard posed by eroding coastal cliffs on the islands of Puerto Rico, Culebra, and Vieques. The delineation of cliff tops and toes can be used as an input into cliff hazard metrics and to measure overall cliff changes over time. Cliff tops and cliff toes were identified along three-dimensional (3D) ... |
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Depth to base of last glacial maximum point data in California State Waters between Refugio and Hueneme Canyon, California (sbsedbsmpt).
As part of the USGS's California State Waters Mapping Project, depth to base of last glacial maximum within the 3-nautical mile limit between Gaviota and Hueneme Canyon was extracted from seismic-reflection data collected in 2007 (USGS activity (Z-3-07-SC) and 2008 (S-7-08-SC). Depths range from 7 to 568 m with a mean of 67 m and a standard deviation of 65 m. |
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Depth to Quaternary regional unconformities offshore of the Delmarva Peninsula, including Maryland and Virginia state waters
Geologic structure and isopach maps were constructed by interpreting over 19,890 trackline kilometers of co-located multichannel boomer, sparker and chirp seismic reflection profiles from the continental shelf of the Delmarva Peninsula, including Maryland and Virginia state waters. In this region, Brothers and others (2020) interpret 12 seismic units and 11 regional unconformities. They interpret the infilled channels as Late Tertiary and Quaternary courses of the Susquehanna, Potomac, Rappahannock, York ... |
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Depth to Transition--Bolinas to Pescadero, California
This part of DS 781 presents data for the depth-to-transition map of the Bolinas to Pescadero, California, region. The raster data file is included in "DepthToTransition_BolinastoPescadero.zip," which is accessible from https://pubs.usgs.gov/ds/781/BolinasToPescadero/data_catalog_BolinasToPescadero.html. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Bolinas and Pescadero was generated from seismic ... |
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Depth to Transition--Pigeon Point to Monterey, California
This part of DS 781 presents data for the depth-to-transition map of the Pigeon Point to Monterey, California, map region. The raster data file is included in "DepthToTransition_PigeonPointToMonterey.zip," which is accessible from https://doi.org/10.5066/F7N29V0Z. As part of the USGS's California State Waters Mapping Project, a 50-m-resolution grid of sediment thickness for the seafloor within the limit of California’s State Waters between Pigeon Point and southern Monterey Bay was generated from seismic ... |
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Depth to Transition--Point Conception to Hueneme Canyon, California
This part of DS 781 presents data for the depth-to-transition map of the Point Conception to Hueneme Canyon, California, region. The raster data file is included in "DepthToTransition_PointConceptionToHuenemeCanyon.zip," which is accessible from https://doi.org/10.5066/F7891424. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Point Conception and Hueneme Canyon was generated from seismic-reflection ... |
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Depth to Transition—Point Sur to Point Arguello, California
This part of DS 781 presents data for the depth-to-transition map of the Point Sur to Point Arguello, California, region. The raster data file is included in the “DepthToTransition_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Point Sur and Point Arguello was generated from seismic-reflection data collected ... |
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Depth to Transition--Punta Gorda to Point Arena, California
This part of DS 781 presents data for the depth-to-transition map of the Punta Gorda to Point Arena, California, region. The raster data file is included in the "DepthToTransition_PuntaGordaToPointArena.zip," which is accessible from https://doi.org/10.5066/P9PNNI9H. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Punta Gorda and Point Arena was generated from seismic-reflection data collected between ... |
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Depth to Transition--Punta Gorda to Point Arena, California
This part of DS 781 presents data for the depth-to-transition map of the Punta Gorda to Point Arena, California, region. The raster data file is included in the "DepthToTransition_PuntaGordaToPointArena.zip," which is accessible from https://doi.org/10.5066/P9PNNI9H. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the 3-nautical mile limit between Punta Gorda and Point Arena was generated from seismic-reflection data collected between ... |
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Depth to Transition--Salt Point to Drakes Bay, California
This part of DS 781 presents data for the depth-to-transition map of the Salt Point to Drakes Bay, California, region. The raster data file is included in "DepthToTransition_SaltPointToDrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/SaltPointToDrakesBay/data_catalog_SaltPointToDrakesBay.html. As part of the USGS's California State Waters Mapping Project, a 20-m grid of depth to the transgressive surface of the last glacial maximum was generated for the areas within the 3-nautical mile ... |
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Depth to transition--Santa Barbara Channel, California
This part of DS 781 presents data for the depth-to-transition (the depth to the bedrock at the Last Glacial Maximum) map of the Santa Barbara Channel, California, region. The raster data file is included in "DepthToTransition_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. As part of the USGS's California Seafloor Mapping Project, a 50-m-resolution grid of depth to the transgressive surface of the Last Glacial ... |
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Descriptive core logs, high-resolution images and derived data for Holocene reef cores collected from 1976 to 2017 along the Florida Keys reef tract
The USGS core archive (Reich and others, 2009; https://olga.er.usgs.gov/coreviewer/) houses an extensive collection of coral-reef cores that USGS researchers have collected from throughout the Florida Keys reef tract (FKRT). USGS scientists have compiled all available data on the 71 core records that recovered Holocene reef framework, including radiometric ages (radiocarbon and U-series), data on reef development (timing of reef initiation and senescence, reef accretion, and reef thickness) and geospatial ... |
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Detailed grain-size data of estuarine, barrier island, and shoreface environments around Dauphin Island, Alabama, USA
In 2015, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted sediment sampling surveys on and around the barrier islands of Dauphin Island and Little Dauphin Island, Mobile County, Alabama (AL) under USGS Field Activity Number (FAN) 2015-322-FA (sub-FAN 15BIM09). The study investigated surficial sediment surrounding Dauphin Island and surrounding environments to inform sediment transport model scenarios of coastal change. This data release ... |
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Digital data for depth to basement in the deep-sea basins of the Pacific continental margin (cowbsm) based on data collected in 1984.
Digital vector data for the contours of depth to basement for the deep-sea basins of the Pacific continental margin offshore of Washington, Oregon, and California. The data were interpreted from GLORIA (Paskevich and others, 2011) sidescan data and related seismic-reflection data. The data were published as USGS maps in paper format (Gardner and others, 1992, 1993a, 1993b). |
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Digital data for sediment thickness in the deep-sea basins of the Pacific continental margin based on 1984 surveys
Contours of sediment thickness for the deep-sea basins of the Pacific continental margin offshore of Washington, Oregon, and California were were interpreted from GLORIA (Paskevich and others, 2011) sidescan imagery and related seismic-reflection data and were published as maps in paper format (Gardner and others, 1992, 1993a, 1993b). |
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Digital Elevation Model from Single-Beam Bathymetry XYZ Data Collected in 2015 from Raccoon Point to Point Au Fer, Louisiana
As part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the south-central coast of Louisiana, from Raccoon Point to Point Au Fer Island, in July 2015. The goal of the BICM program is to provide long-term data on Louisiana’s coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration ... |
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Digital Elevation Model from Single Beam Bathymetry XYZ Data Collected in June 2015 from the Chandeleur Islands, Louisiana
As part of the Louisiana Coastal Protection and Restoration Authority (CPRA) Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a single-beam bathymetry survey around the Chandeleur Islands, Louisiana in June 2015. The goal of the program is to provide long-term data on Louisiana’s barrier islands and use this data to plan, design, evaluate, and maintain current and future barrier island ... |
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Digital Elevation Model of Oxbow Reservoir, Placer County, California, October 2022
This portion of the data release presents a digital elevation model (DEM) of portions of Oxbow Reservoir in Placer County, California. The DEM was created using topographic survey data collected on 26 October 2022, when the reservoir was partially de-watered to allow repairs to the dam infrastructure following the Mosquito Fire. Although the gates of the dam were open during this time, significant portions of the reservoir site remained inaccessible to surveyors due to the continued flow of the Middle Fork ... |
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Digital elevation models (DEMs) of coastal North Carolina, from 2019-08-30 to 2019-09-02, Pre-Hurricane Dorian
Digital elevation models (DEMs) were created from aerial imagery collected between August 30 and September 2, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions prior to Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface before Hurricane Dorian and were created to document inter-annual changes in ... |
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Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian
Digital elevation models (DEMs) were created from aerial imagery collected between September 08 and September 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions post-Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface after Hurricane Dorian and were created to document inter-annual changes in ... |
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Digital elevation models (DEMs) of coastal North Carolina, from 2020-02-08 to 2020-02-09
Digital elevation models (DEMs) were created from aerial imagery collected February 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using ... |
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Digital elevation models (DEMs) of coastal North Carolina, from 2020-05-08 to 2020-05-09
Digital elevation models (DEMs) were created from aerial imagery collected May 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using aerial ... |
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Digital elevation models (DEMs) of coastal North Carolina, on 2019-10-11, one month Post-Hurricane Dorian
Digital elevation models (DEMs) were created from aerial imagery collected October 11, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions one-month after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ... |
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Digital elevation models (DEMs) of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian
Digital elevation models (DEMs) were created from aerial imagery collected November 26, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions two-months after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ... |
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Digital elevation models of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016
This part of the data release presents digital elevation models (DEMs) spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the DEMs were created, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were collected ... |
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Digital image mosaic of the nearshore coastal waters from Waikiki to Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography. These five image mosaics were then combined into one larger mosaic and resampled to 1-meter resolution. |
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Digital image mosaic of the nearshore coastal waters of Diamond Head on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Diamond Head area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Haleolono Point on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Haleolono Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kawela on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Kawela on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of La'au Point on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the La'au Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Maunalua Bay on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Maunalua Bay area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Pala'au on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Pala'au on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Portlock area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Puko'o on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Puko'o area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of the Napili-Honokowai area on the northwest coast of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Napili-Honokowai area on the northwest coast of Maui. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). The image mosaic has been geometrically corrected using lidar data. Also available is a lower-resolution 'browse' image, and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Umipa'a on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Umipa'a area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Waiakane on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Waiakane area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata. |
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Digital image mosaic of the nearshore coastal waters of Wai'alae on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Wai'alae area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of Kailua-Kona on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic with 1.0 meter-per-pixel resolution of the Kailua-Kona area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial ... |
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Digital image mosaics of the nearshore coastal waters of Kalaeloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kalaeloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of Kawaihae on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Kawaihae area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ... |
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Digital image mosaics of the nearshore coastal waters of Kukio on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Kukio area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains digital image mosaics along the south coast of Moloka'i. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Pala'au, Umipa'a, Kaunakakai, Kamiloloa, Kawela, Kamalo, and Kalaeloa, were generated from 1:10K aerial photography, and are presented in one zip file (molokai_1ft.zip) that also contains lower-resolution 'browse' graphics of each image-mosaic area, as well as associated metadata. Digital mosaics at 1-meter resolution, including the ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were ... |
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Digital image mosaics of the nearshore coastal waters of selected areas on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were ... |
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Digital image mosaics of the nearshore coastal waters of Waikiki on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Waikiki area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata. |
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Digital image mosaics of the nearshore coastal waters of Waikoloa on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains an image mosaic of the Waikoloa area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ... |
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Digital shaded-relief image mosaic of the nearshore coastal waters of southcentral Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southcentral Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief ... |
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Digital shaded-relief image mosaic of the nearshore coastal waters southeast Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southeast Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. ... |
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Digital shaded-relief image mosaic of the nearshore coastal waters southwest Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data
This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southwest Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. ... |
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Digital Shoreline Analysis System (DSAS) version 5.0 transects with bluff rate change calculations for the north coast of Barter Island Alaska, 1950 to 2020
This dataset consists of rate-of-change statistics for the coastal bluffs at Barter Island, Alaska for the time period 1950 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each bluff line establishing measurement points, which are then used to ... |
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Digital Shoreline Analysis System (DSAS) version 5.0 transects with shoreline rate change calculations at Barter Island Alaska, 1947 to 2020
This dataset consists of rate-of-change statistics for the shorelines at Barter Island, Alaska for the time period 1947 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to ... |
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Digital surface model (DSM) and digital elevation model (DEM) of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01
This portion of the data release presents a digital surface model (DSM) and digital elevation model (DEM) of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The DSM and DEM have a resolution of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. The DSM represents the elevation of the highest object within the bounds of a cell, including vegetation, woody ... |
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Digital surface model (DSM) for the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05
This portion of the data release presents a digital surface model (DSM) and hillshade image of the intertidal zone at Lone Tree Point, Kiket Bay, WA. The DSM has a resolution of 4 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-05. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have ... |
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Digital surface model (DSM) for the intertidal zone at West Whidbey Island, WA, 2019-06-04
This portion of the data release presents a digital surface model (DSM) and hillshade image of the intertidal zone at West Whidbey Island, WA. The DSM has a resolution of 4 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-04. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been ... |
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Digital surface model (DSM) for the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23
This portion of the data release presents a digital surface model (DSM) and hillshade of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta. The DSM has a resolution of 10 centimeters per-pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an Unmanned Aerial System (UAS) on 2018-10-23. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. ... |
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Digital surface models (DSM) for the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03
This portion of the data release presents digital surface models (DSM) and hillshade images of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA. The DSMs have a resolution of 2.5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-03. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and ... |
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Digital Surface Models (DSM) from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017
This portion of the data release presents digital surface models (DSM) of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) during low tides on 7 and 8 August 2017. Unlike a digital elevation model (DEM), the DSMs represent the elevation of the highest object within the bounds ... |
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Digital Surface Models (DSM) from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021
This portion of the data release presents digital surface models (DSM) of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) during low tides on 22 and 23 July 2021. Unlike a digital elevation model (DEM), the DSMs represent the elevation of the highest object within the bounds ... |
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Digital Surface Models (DSM) from UAS surveys of the upper reservoir delta at Jenkinson Lake, El Dorado County, California
This portion of the data release presents high-resolution Digital Surface Models (DSM) of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to ... |
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Digital surface models (DSMs) for the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06
This portion of the data release presents digital surface models (DSMs) and hillshade images of the intertidal zone at Post Point, Bellingham Bay, WA. The DSMs were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-06. Unlike a digital elevation model (DEM), the DSMs represent the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, ... |
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Digital Surface Models (DSMs) of the Whale's Tail Marsh region, South San Francisco Bay, CA
This portion of the data release presents digital surface models (DSM) of the Whale's Tail Marsh region of South San Francisco Bay, CA. The DSMs have resolutions of 5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of repeat aerial imagery collected from fixed-wing aircraft. Unlike a digital elevation model (DEM), a DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, structures, and other objects have not been removed from the data. ... |
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Digital surface models of Pea Island National Wildlife Refuge DUNEX Site, North Carolina in September and October 2021
The data in this part of the release are digital surface models (DSMs) that characterize the beach at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal ... |
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Digital vector bathymetric/topographic contours of the sea floor in the Stellwagen Bank National Marine Sanctuary region (bathy.shp)
This data set contains the sea floor topographic contours generated from a multibeam sonar survey of the Stellwagen Bank National Marine Sanctuary region off Boston, Massachusetts, an area of approximately 1100 square nautical miles. The Stellwagen Bank NMS Mapping Project is designed to provide detailed maps of the Stellwagen Bank region's environments and habitats and the first complete multibeam topographic and sea floor characterization maps of a significant region of the shallow EEZ. Data were ... |
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Digital version of the Cape Cod and the Islands Geologic Map (CAPE_GEOLGEOG shapefile, Geographic, NAD83)
These data represent a digital form of the geologic map of Cape Cod and the islands. |
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Discrete surface water data for samples collected in-transit along the West Florida Shelf in July and August, 2013
The United States Geological Survey (USGS) is studying the effects of climate change on ocean acidification within the Gulf of Mexico; dealing specifically with the effect of ocean acidification on marine organisms and habitats. To investigate this, the USGS participated in cruises on the West Florida Shelf and northern Gulf of Mexico regions aboard the research vessel (R/V) Weatherbird II or Bellows, ships of opportunity led by Dr. Kendra Daly, of the University of South Florida (USF) in July and August, ... |
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Discrete water column sample data from predefined locations (stations) of the West Florida Shelf collected in July and August, 2013
The United States Geological Survey (USGS) is studying the effects of climate change on ocean acidification within the Gulf of Mexico; dealing specifically with the effect of ocean acidification on marine organisms and habitats. To investigate this, the USGS participated in cruises on the West Florida Shelf and northern Gulf of Mexico regions aboard the research vessel (R/V) Weatherbird II or Bellows, ships of opportunity led by Dr. Kendra Daly, of the University of South Florida (USF) in July and August, ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2014–2015
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Assateague Island, MD & VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Assawoman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Hatteras, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Lookout, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Coast Guard Beach, MA, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cobb Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Fisherman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Metompkin Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Monomoy Island, MA, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Myrtle Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parker River, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parramore Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Rhode Island National Wildlife Refuge, RI, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Ship Shoal Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Wreck Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Assateague Island, MD & VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Assawoman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Cape Hatteras, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Cape Lookout, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Cedar Island, VA, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Cedar Island, VA, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Cedar Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Coast Guard Beach, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Cobb Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Fire Island, NY, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Fire Island, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Fire Island, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Fisherman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Metompkin Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Monomoy Island, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Myrtle Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Parker River, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Parramore Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Rhode Island National Wildlife Refuge, RI, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Rockaway Peninsula, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Rockaway Peninsula, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Ship Shoal Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Smith Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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DisOcean: Distance to the ocean: Wreck Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Distribution of Benthic Habitats at Crocker Reef, Florida, 2014
The distribution of benthic habitats for a 1-kilometer (km) x 1-km area around Crocker Reef in the Florida Keys, USA, is based upon underwater digital images of the seafloor collected on June 24 and 25, 2014 (Zawada and others, 2016). The imagery was collected using the U.S. Geological Survey (USGS) shallow Along-Track Reef-Imaging System (sATRIS), a boat-based, pole-mounted sensor package for mapping shallow-water benthic environments. The polygons contained in the shapefile included in this data release, ... |
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Distribution of sand dollars on the sea floor on the inner continental shelf off the northern Oregon and southern Washington
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan-sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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Distribution of Seafloor Environments within the inner shelf of Long Bay, South Carolina (SEAFLOORENV, Polygon shapefile)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
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Distribution of Surficial Sediments of NOAA H11310 Sidescan Sonar Mosaic in Central Narragansett Bay (H11310SEDS.SHP)
The United States Geological Survey (USGS) is working cooperatively with the National Oceanic and Atmospheric Association (NOAA) to interpret the surficial geology in estuaries along the coast of the northeastern United States. The purpose of our present study is to interpret the distributions of surficial sediments and sedimentary environments in an area of Narragansett Bay using sidescan sonar imagery, high-resolution bathymetry, and sediment data. The mosaic presented herein covers an area of the sea ... |
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DRASTIC model results for Upper Floridan aquifer vulnerability to Bromacil and Ethylene Dibromide
This dataset includes DRASTIC (Aller and others, 1987) model results for Upper Floridan aquifer vulnerability to contamination. The DRASTIC value serves as an intrinsic vulnerability index for assessing the transport of contaminants from the surface. The DRASTIC model setup requires the input of raster data for depth to groundwater, aquifer recharge, aquifer media, soil media, topography, vadose zone media, and aquifer hydraulic conductivity. These variables were entered into the DRASTIC equation using the ... |
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EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: First Surface
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high ... |
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EAARL Coastal Topography–Eastern Louisiana Barrier Islands Barrier Islands, 09 March 2008: First Surface
A Digital Elevation Model (DEM) mosaic was data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ... |
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EAARL Coastal Topography–Northwest Florida, Post-Hurricane Katrina, 2005: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over northwest Florida, post-Hurricane Katrina (August 2005 hurricane), using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ... |
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EAARL Coastal Topography–Northwest Florida, Post-Hurricane Katrina, 2005: First Surface
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over northwest Florida, post-Hurricane Katrina (August 2005 hurricane), using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ... |
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EAARL Coastal Topography–Texas, Post-Hurricane Ike, 2008: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Ike (September 2008 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ... |
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EAARL Coastal Topography–Texas, Post-Hurricane Ike, 2008: First Surface
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Ike (September 2008 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ... |
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EAARL Coastal Topography–Texas, Post-Hurricane Rita, 2005: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Rita (September 2005 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ... |
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EAARL Coastal Topography–Texas, Post-Hurricane Rita, 2005: First Return
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Rita (September 2005 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ... |
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EasternLA2008_EAARLA_BE_n88g03_metadata: EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: Bare Earth
ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high ... |
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EasternLA2008_EAARLA_BE_n88g03_mosaic_metadata: EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: Bare Earth
A Digital Elevation Model (DEM) mosaic was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system ... |
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ECSTDB2005 - U.S. Geological Survey East Coast Sediment Texture Database (2005)
This sediment database contains location, description, and texture of samples taken by numerous marine sampling programs. Most of the samples are from the Atlantic Continental Margin of the United States, but some are from as diverse locations as Lake Baikal, Russia, the Hawaiian Islands region, Puerto Rico, the Gulf of Mexico, and Lake Michigan. The database presently contains data for over 23,000 samples, which includes texture data for approximately 3800 samples taken or analyzed by the Atlantic ... |
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Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
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Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS_MP)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS_MP_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Initial_Elevations_RS_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Velocity_Residual_RS)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Velocity_Residual_RS_MP)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Velocity_Residual_RS_MP_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Velocity_Residual_RS_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Water_Level_RS)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Water_Level_RS_MP)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Water_Level_RS_MP_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Effects of Late Holocene Climate and Coastal Change in Mobile Bay, Alabama: ADCIRC Model Input and Results (Water_Level_RS_PH)
Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ... |
Info |
Elevation data collected in 2009 on the beach and foreshore in the vicinity of Wainwright, Alaska
Beach and foreshore elevation data were collected in the vicinity of Wainwright, Alaska. The area from the mouth of the Kuk River to about 8 km to the northeast was measured in August 2009. The area from the mouth of the Kuk River to about 5 km to the northeast was measured in October 2009. The elevation data were collected with Real-Time Kinematic (RTK) Global Positioning System (GPS) systems mounted on all-terrain vehicles. The GPS sampling rate was 1 Hz with vehicle speeds maintained at less than 15 km ... |
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Elevation Data Collected in 2010 from Sabine National Wildlife Refuge, Louisiana
Data release doi:10.5066/F7BR8QBH associated with this metadata record serves as an archive of elevation data collected in August 2010 from Sabine National Wildlife Refuge (SNWR), Louisiana (U.S. Geological Survey [USGS] Field Activity Number [FAN] 10SWL01). Point (xyz) elevations were collected from historically formed open-water bodies and the surrounding emergent marsh using a combination of stop-and-go (semi-kinematic) and kinematic differential Global Positioning System (DGPS) surveying techniques. ... |
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Elevation data for four sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from July 2018 through January 2020
To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ... |
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Elevation of paleochannel unconformities underlying the inner shelf of Long Bay (Grid)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
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Elevation of the bedrock surface within the St. Clair River between Michigan and Ontario, Canada, 2008 (ESRI GRID, DSUELEV)
In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ... |
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Elevation of the late Wisconsinan to early Holocene regressive unconformity (Ur) beneath Vineyard and western Nantucket Sounds, Massachusetts (Esri binary grid; UTM, Zone 19N, WGS 84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ... |
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Elevation of the late Wisconsinan to early Holocene regressive unconformity (Ur) offshore of western and southern Martha's Vineyard and north of Nantucket, Massachusetts
Geologic, sediment texture, and physiographic zone maps characterize the sea floor south and west of Martha's Vineyard and north of Nantucket, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This ... |
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Elevation of the regional transgressive unconformity underlying the inner shelf of Long Bay (Grid; transgr_grd)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
Info |
Elevation of the top of glacial deposits beneath Buzzards Bay, Massachusetts (Urelev, Esri binary grid; UTM, Zone 19N, WGS 84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Buzzards Bay, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a result of a collaborative ... |
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Elevation point clouds of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016
This part of the data release presents georeferenced elevation point clouds spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the point clouds were derived, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were ... |
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ElevMHW: Elevation adjusted to local mean high water: Assateague Island, MD & VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Assawoman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Cape Hatteras, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Cape Lookout, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Coast Guard Beach, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Cobb Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Fisherman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Metompkin Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Monomoy Island, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Myrtle Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Parker River, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Ship Shoal Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Smith Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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ElevMHW: Elevation adjusted to local mean high water: Wreck Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Estuarine Back-barrier Shoreline and Beach Sandline Change Model Skill and Predicted Probabilities: Event-driven backshore shoreline change
The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ... |
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Estuarine Back-barrier Shoreline and Beach Sandline Change Model Skill and Predicted Probabilities: Event-driven beach sandline change
The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ... |
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Estuarine Back-barrier Shoreline and Beach Sandline Change Model Skill and Predicted Probabilities: Long-term sandline change
The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ... |
Info |
Estuarine Back-barrier Shoreline and Sandline Change Model Skill and Predicted Probabilities: Long-term back-barrier shoreline change
The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ... |
Info |
Experimental coral-growth and physiological data and time-series imagery for Porites astreoides in the Florida Keys, U.S.A.
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates and time-series photographs taken of colonies of the mustard hill coral, Porites astreoides, grown at four sites on the Florida Keys reef tract from Spring 2015 to Spring 2017. The data will be used to inform resource managers on the spatial and ... |
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Experimental coral-growth data and time-series imagery for Acropora palmata and Pseudodiploria strigosa in St. Croix, U.S. Virgin Islands
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps Department of Interior and other resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates and time-series photographs taken of colonies of the elkhorn coral, Acropora palmata, and the symmetrical brain coral, Pseudodiploria strigosa, grown at three sites at Buck Island Reef National Monument in St. ... |
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Experimental coral-growth data and time-series imagery for Acropora palmata in the Florida Keys, U.S.A.
The USGS Coral Reef Ecosystems Studies project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates and time-series photographs taken of colonies of the elkhorn coral, Acropora palmata, grown at five sites on the Florida Keys reef tract from Spring 2018 to Autumn 2019. The data will be used to inform resource managers of the capacity for restoration and growth of this ... |
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Experimental coral-growth rate, reef survey, and time-series imagery data collected between 1998 and 2017 to investigate construction and erosion of Orbicella coral reefs in the Florida Keys, U.S.A.
The USGS Coral Reef Ecosystems Studies project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates for Orbicella sp. coral colonies grown at five sites on the Florida Keys reef tract from 2013 to 2015, survey data for census-based carbonate budgeting at Hen and Chickens Reef (Islamorada, Florida) collected in 2017, and time-series photographs taken of permanent markers ... |
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Experimental coral-physiology data for Acropora palmata in Florida, U.S.A.
The U.S. Geological Survey (USGS) Coral Reef Ecosystems Studies (CREST) project (https://coastal.er.usgs.gov/crest/) provides science that helps Department of Interior and other resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral physiology of the elkhorn coral, Acropora palmata, grown at five sites along the Florida outer reef tract including in Biscayne National Park, the Florida Keys National Marine Sanctuary, and Dry Tortugas National Park, ... |
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Experimental data comparing two coral grow-out methods in nursery-raised Acropora cervicornis
Staghorn coral, Acropora cervicornis, is a threatened species and the primary focus of western Atlantic reef-restoration efforts to date. As part of the USGS Coral Reef Ecosystems Studies project (http://coastal.er.usgs.gov/crest/), scientists investigated skeletal characteristics of nursery-grown staghorn coral reared using two commonly used grow-out methods at Mote Tropical Research Laboratory’s offshore nursery. USGS staff compared linear extension, calcification rate, and skeletal density of nursery ... |
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Extent of a depositional lobe on the Mississippi Fan (LOBE.SHP)
Since 1982 the U.S. Geological Survey (USGS) has collected a large amount of surficial and shallow subsurface geologic information in the deep parts of the Gulf of Mexico. These data include digital sidescan sonar imagery, digital seismic-reflection data, and descriptions and analyses of piston and gravity cores. The data were collected during several different projects that addressed surficial and shallow subsurface geologic processes. Some of these data sets have already been published, but the growing ... |
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Extent of the depositional lobe of the Mississippi Fan
This GIS layer contains an interpretive layer of the extent of the depositional lobe of the Mississippi Fan. |
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Extratropical Storm Jan2016 Assessment of Potential Coastal Change Impacts: 1200 PM EST FRI JAN 22 2016
This dataset defines storm-induced coastal erosion hazards for the Virginia, Maryland, Delaware, New Jersey and New York coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct impact of the Extratropical Storm in January 2016. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities ... |
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Extratropical Storm March 2018 Assessment of Potential Coastal Change Impacts: 0800 AM EST FRI MAR 02 2018
This dataset defines storm-induced coastal erosion hazards for the North Carolina, Virginia, Maryland, Delaware, New Jersey, New York, Rhode Island, Massachusetts, New Hampshire and Maine coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of an Extratropical Storm in March 2018. Storm-induced water levels, due to both surge and waves, were ... |
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Fall 2000 USGS Mid-Atlantic Lidar-Derived Dune Crest, Toe and Shoreline
The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2000 Atlantic Coast U.S. ... |
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Faults--Drakes Bay and Vicinity, California
This part of DS 781 presents data of faults for the geologic and geomorphologic map of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Faults_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Faults--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Faults_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K ... |
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Faults--Monterey Canyon and Vicinity Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Monterey Canyon and Vicinity map area, California. The vector data file is included in "Faults_MontereyCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/MontereyCanyon/data_catalog_MontereyCanyon.html. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G. ... |
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Faults--Offshore of Aptos Map Area, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore Aptos map area, California. The vector data file is included in "Faults_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, ... |
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Faults--Offshore of Bodega Head Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Bodega Head map area, California. The vector data file is included in "Faults_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., ... |
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Faults--Offshore of Bolinas Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Bolinas map area, California. The vector data file is included in "Faults_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., ... |
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Faults--Offshore of Carpinteria, California
This part of DS 781 presents data for fault data for the Offshore of Carpinteria map area, California. The vector data file is included in "Faults_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., ... |
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Faults--Offshore of Coal Oil Point, California
This part of DS 781 presents fault data for the Offshore of Coal Oil Point map area, California. The vector data file is included in "Faults_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., ... |
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Faults--Offshore of Fort Ross Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Fort Ross map area, California. The vector data file is included in "Faults_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Faults--Offshore of Gaviota Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Faults_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota ... |
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Faults--Offshore of Half Moon Bay Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Half Moon Bay map area, California. The vector data file is included in "Faults_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L. ... |
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Faults--Offshore of Monterey, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Faults_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, ... |
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Faults--Offshore of Pacifica map area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Pacifica map area, California. The vector data file is included in "Faults_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, ... |
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Faults--Offshore of Point Conception Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Faults_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series� ... |
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Faults--Offshore of Point Reyes Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Point Reyes map area, California. The vector data file is included in "Faults_OffshorePointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C ... |
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Faults--Offshore of Salt Point Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Salt Point map area, California. The vector data file is included in "Faults_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter ... |
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Faults--Offshore of San Francisco Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore San Francisco map area, California. The vector data file is included in "Faults_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W ... |
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Faults--Offshore of San Gregorio Map Area, California
This part of SIM 3306 presents data for the faults for the geologic and geomorphic map of the Offshore of San Gregorio map area, California. The vector data file is included in "Faults_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., ... |
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Faults--Offshore of Santa Barbara, California
This part of DS 781 presents fault data for the Offshore of Santa Barbara map area, California. The vector data file is included in "Faults_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., ... |
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Faults--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Faults_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., ... |
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Faults--Offshore of Tomales Point Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Faults_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M ... |
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Faults--Offshore of Ventura, California
This part of SA 781 presents fault data for the Offshore of Ventura map area, California. The vector data file is included in "Faults_OffshoreVentura.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M ... |
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Faults--Offshore Pigeon Point, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Faults_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., ... |
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Faults--Offshore Refugio Beach, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Faults_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H ... |
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Faults--Offshore Santa Cruz, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore of Santa Cruz map area, California. The vector data file is included in "Faults_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., ... |
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Faults—Point Sur to Point Arguello, California
This part of DS 781 presents data for the faults of the Point Sur to Point Arguello, California, region. The vector data file is included in the “Faults_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. Faults in the Point Sur to Point Arguello region are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, ... |
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Faults--Punta Gorda to Point Arena, California
This part of DS 781 presents data for the faults of the Punta Gorda to Point Arena, California, region. The vector data file is included in the "Faults_PuntaGordaToPointArena.zip," which is accessible from https://doi.org/10.5066/P9PNNI9H. Faults in the Punta Gorda and Point Arena region are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, frequency, ... |
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Faults--Punta Gorda to Point Arena, California
This part of DS 781 presents data for the faults of the Punta Gorda to Point Arena, California, region. The vector data file is included in the "Faults_PuntaGordaToPointArena.zip," which is accessible from https://doi.org/10.5066/P9PNNI9H. Faults in the Punta Gorda and Point Arena region are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, frequency, ... |
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FIIS_Breach_Shorelines.shp - Fire Island National Seashore Wilderness Breach Shoreline Data Collected from Fire Island, New York, October 2014 to October 2017
Hurricane Sandy made U.S. landfall, coincident with astronomically high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New ... |
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FIIS_Breach_Shorelines.shp - Fire Island National Seashore Wilderness Breach Shoreline Data Collected from Fire Island, New York, October 2014 to September 2016
Hurricane Sandy made U.S. landfall, coincident with astronomical high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New ... |
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FIIS_Shorelines_Oct2012_Oct2017.shp: Fire Island, NY pre- and post-storm shoreline data from October 2012 to October 2017
Hurricane Sandy made U.S. landfall, coincident with astronomically high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New ... |
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Fire Island Shoreface Bathymetric Data collected with Personal Watercraft and Backpack along Fire Island, New York (2014) as a GeoTIFF
Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ... |
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Fisheries Sediment Data (WIGLEY65 shapefile)
This is a part of the National Geophysical Data Center (NGDC) Seafloor Surficial Sediment (Deck 41) Data File. Deck 41 is an original data file created by the Marine Geology and Geophysics Group of NGDC from 1970-1975, abstracted from unpublished material contributed to NGDC by multiple groups of individuals. No updates of Deck 41 have been added since 1975. The data that comprise this portion of Deck 41 were generated by R.L. Wigley during 1965 aboard ALBATROSS IV cruises 65-2, 65-13, and 65-14. |
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Florida Keys Corals: A Photographic Record of Changes from 1959 to 2015
This data release contains time-series photographs taken of corals and coral habitats in the Florida Keys between 1959 and 2015 at Carysfort Reef and Grecian Rocks (a total of six sites). The original intent was to show coral reef recovery after Hurricane Donna devastated the area in 1960. Corals, especially elkhorn and staghorn coral, grew prolifically after the storm until the late 1970s, then began to decline, with the maximum period of decline centered around 1983 and 1984. These time-series photographs ... |
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Florida Reef Tract 1930s-2016 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the 1930’s and 2016 along the Florida Reef Tract (FRT) from Miami to Key West within a 982.4 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Yates and others (2021) derived from an elevation-change analysis between two elevation datasets acquired in the 1930’s ... |
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Florida Reef Tract 2016-2019 Seafloor Elevation Stability Models, Maps, and Tables
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted research to identify areas of seafloor elevation stability and instability based on elevation changes between the years of 2016 and 2019 along the Florida Reef Tract (FRT) from Miami to Key West within a 939.4 square-kilometer area. USGS SPCMSC staff used seafloor elevation-change data from Fehr and others (2021) derived from an elevation-change analysis between two elevation datasets acquired in 2016/2017 ... |
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Fluvial-Marine Interactions, Maine (BUYNEVICH01 shapefile)
Grab samples and cores were collected as part of a study of the fluvial-marine interaction in the system comprised by the Kennebec River, Androscoggin River, Merrymeeting Bay, and Kennebec Rver Estuary. Processes controlling the Holocene evolution of the popham Barrier were also examined. |
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Folds--Drakes Bay and Vicinity Map Area, California
This part of DS 781 presents data of folds for the geologic and geomorphologic map of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Folds_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Folds--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Folds_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B. ... |
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Folds--Monterey Canyon and Vicinity Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Monterey Canyon and Vicinity map area, California. The vector data file is included in "Folds_MontereyCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/MontereyCanyon/data_catalog_MontereyCanyon.html. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., ... |
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Folds--Offshore of Aptos Map Area, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore Aptos map area, California. The vector data file is included in "Folds_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R ... |
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Folds--Offshore of Bodega Head Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Bodega Head map area, California. The vector data file is included in "Folds_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., ... |
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Folds--Offshore of Bolinas Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Bolinas map area, California. The vector data file is included in "Folds_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, ... |
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Folds--Offshore of Carpinteria, California
This part of DS 781 presents fold data for the Offshore of Carpinteria map area, California. The vector data file is included in "Folds_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., ... |
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Folds--Offshore of Coal Oil Point, California
This part of DS 781 presents fold data for the Offshore of Coal Oil Point map area, California. The vector data file is included in "Folds_OffshoreCoalOilPoint.zip," which is accessible from https ://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., ... |
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Folds--Offshore of Fort Ross Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Fort Ross map area, California. The vector data file is included in "Folds_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E ... |
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Folds--Offshore of Gaviota Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Folds_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. In the offshore part of the map area, closely-spaced seismic-reflection profiles image many shallow, west-northwest striking folds that have variable geometry, length, amplitude, continuity, and wavelength. The two longest folds, the 17-km-long Molino anticline ... |
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Folds--Offshore of Half Moon Bay Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Half Moon Bay map area, California. The vector data file is included in "Folds_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., ... |
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Folds--Offshore of Monterey, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Folds_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, ... |
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Folds--Offshore of Pacifica map area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Pacifica map area, California. The vector data file is included in "Folds_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R ... |
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Folds--Offshore of Point Conception Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Folds_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series� ... |
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Folds--Offshore of Point Reyes Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Point Reyes map area, California. The vector data file is included in "Folds_OffshorePointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A ... |
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Folds--Offshore of Salt Point Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Salt Point map area, California. The vector data file is included in "Folds_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, ... |
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Folds--Offshore of San Francisco Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of San Francisco map area, California. The vector data file is included in "Folds_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R ... |
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Folds--Offshore of San Gregorio Map Area, California
This part of SIM 3306 presents data for the folds for the geologic and geomorphic map of the Offshore of San Gregorio map area, California. The vector data file is included in "Folds_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, ... |
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Folds--Offshore of Santa Barbara, California
This part of DS 781 presents fold data for the Offshore of Santa Barbara map area, California. The vector data file is included in "Folds_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., ... |
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Folds--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Folds_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie ... |
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Folds--Offshore of Tomales Point Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Folds_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W. ... |
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Folds--Offshore of Ventura, California
This part of DS 781 presents fold data for the Offshore of Ventura map area, California. The vector data file is included in "Folds_OffshoreVentura.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D ... |
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Folds--Offshore Pigeon Point, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Folds_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, ... |
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Folds--Offshore Refugio Beach, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Folds_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G ... |
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Folds--Offshore Santa Cruz, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore of Santa Cruz map area, California. The vector data file is included in "Folds_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, ... |
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Folds—Point Sur to Point Arguello, California
This part of DS 781 presents data for the folds of the Point Sur to Point Arguello, California, region. The vector data file is included in the “Folds_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. Folds in the Point Sur to Point Arguello region are identified on seismic-reflection data based on warping and tilting of reflections. Folds were primarily mapped by interpretation of seismic reflection profile data collected by the U.S. Geological Survey between 2008 ... |
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Foraminifera biostratigraphy of sediment cores from the New England Mud Patch collected on USGS Field Activity 2016-001-FA
Variability in sediment properties with depth and the thickness of individual sedimentary layers are critical determinants of seabed acoustic response. The New England Mud Patch (NEMP), located south of Cape Cod, is an unusual feature on the U.S. Continental Shelf in that it is composed of fine-grained sediment layers containing a relatively-homogeneous mix of sand, silt, and clay-sized particles bounded by more typical sandy shelf sediments. The unique characteristics and nature of this deposit is due to ... |
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Foraminiferal Mg/Ca data from IODP sediment core U1446
In 2019, the magnesium-to-calcium (Mg/Ca) ratios were measured in the tests of planktic foraminiferal species, Globigerinoides ruber (white variety), in a subset of samples from Integrated Ocean Drilling Program (IODP) sediment core U1146 from the Bay of Bengal drilled November 2014 to January 2015. For further information regarding data collection and/or processing methods, refer to the associated journal article (Clemens and others, 2021). |
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FtHase_2023_MBES: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii
An Ellipsoidally Referenced Survey (ERS) using a Norbit Winghead multibeam echosounder, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Fort Hase Marine Corps Base Hawaii (MCBH), on the island of Oahu, May 4-12, 2023. This dataset, FtHase_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid and the dataset FtHase_2023_MBES_Backscatter.zip includes the acoustic backscatter ... |
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General physiographic zones of the inner continental shelf between Cape Ann and Salisbury Beach Massachusetts (PHYSIOGRAPHICZONES, Geographic, WGS84)
These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ... |
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Geochemistry of ferromanganese crusts, nodules, and hydrothermally altered rocks from the Arctic Ocean
Ferromanganese crusts, nodules, and hydrothermally altered rocks were collected via dredge within the Amerasia Basin in the Arctic Ocean during USCGC icebreaker Healy cruises HLY0805, HLY0905, and HLY1202 in 2008, 2009, and 2012 respectively. Dredged samples were donated and sent to USGS for subsampling and major and trace element geochemical analyses. Major and trace element data as well as location information (latitude, longitude, depth) for each sample are provided here. |
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Geochemistry of sediment subsamples from Loki's Castle and Favne Vent Fields, Mohns Ridge
This data release contains geochemical data of sediment subsamples collected in 2018 and 2019 from Loki’s Ridge and Favne Vent Fields, Mohns Ridge, part of the Arctic Mid-Atlantic Ridge. Data include major, minor and trace element concentrations, location information (latitude, longitude, depth), analytical methods, and instrument detection limits where available. |
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Geographic Locations of Seabed Sediment Samples from the Stellwagen Bank National Marine Sanctuary Region (SB_SEDSAMPLES Shapefile)
The U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration's (NOAA) National Marine Sanctuary Program, conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region from 1993 to 2004. The mapped area is approximately 3,700 square km (1,100 square nm) in size and was subdivided into 18 quadrangles. Several series of sea floor maps of the region based on multibeam sonar surveys have been published. In addition, 2,628 seabed ... |
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Geologic Interpretation of the Acoustic Data Collected During National Oceanic and Atmospheric Administration (NOAA) Survey H11252 (H11252_INTERP.SHP, Geographic)
The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ... |
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Geologic Interpretation of the Acoustic Data Collected During National Oceanic and Atmospheric Administration (NOAA) Survey H11361 (H11361_INTERP.SHP, Geographic)
The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ... |
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Geologic interpretation of the sidescan sonar mosaic of National Oceanic and Atmospheric Administration (NOAA) survey H11043 off Branford, Connecticut
The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ... |
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Geologic Observations-Oregon OCS Floating Wind Farm Site
This part of the Oregon Outer Continental Shelf (OCS) Floating Windfarm Suite Data Release presents geological observations from video collected on U.S. Geological Survey (USGS) field activity 2014-607-FA in the Floating Wind Farm survey area. The survey was conducted using 12 hour day operations out of Charleston Harbor near Coos Bay, Oregon. The cruise plan consisted of 23 days on site split between sonar mapping and video ground truth surveying. Activities parsed out to nine days of sonar mapping, three ... |
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Geologic outcrop and subcrop type within the inner shelf of Long Bay (Polygon shapefile)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
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Geology and geomorphology--Drakes Bay and Vicinity Bay, California
This part of DS 781 presents data for the geologic and geomorphic map of the Drakes Bay and Vicinity, California. The polygon shapefile is included in "Geology_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., ... |
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Geology and geomorphology--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Geology_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter ... |
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Geology and geomorphology--Monterey Canyon and Vicinity Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of Monterey Canyon and Vicinity, California. The vector data file is included in "Geology_MontereyCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/MontereyCanyon/data_catalog_MontereyCanyon.html. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., ... |
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Geology and geomorphology--Offshore of Aptos Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore Aptos map area, California. The vector data file is included in "Geology_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., ... |
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Geology and geomorphology--Offshore of Bodega Head Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Bodega Head map area, California. The vector data file is included in "Geology_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E. ... |
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Geology and geomorphology--Offshore of Bolinas Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Bolinas map area, California. The vector data file is included in "Geology_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., ... |
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Geology and geomorphology--Offshore of Carpinteria, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Carpinteria map area, California. The vector data file is included in "Geology_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, ... |
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Geology and geomorphology--Offshore of Fort Ross Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Fort Ross map area, California. The vector data file is included in "Geology_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, ... |
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Geology and geomorphology--Offshore of Gaviota Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Geology_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series-Offshore of Gaviota, ... |
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Geology and geomorphology--Offshore of Half Moon Bay map area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Half Moon Bay map area, California. The vector data file is included in "Geology_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J ... |
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Geology and geomorphology--Offshore of Monterey, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Geology_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds. ... |
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Geology and geomorphology--Offshore of Pacifica map area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Pacifica map area, California. The vector data file is included in "Geology_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross ... |
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Geology and geomorphology--Offshore of Point Conception Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Point Conception map area, California. The vector data file is included in "Geology_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series-Offshore ... |
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Geology and geomorphology--Offshore of Point Reyes Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Point Reyes map area, California. The vector data file is included in "Geology_OffshorePointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., ... |
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Geology and geomorphology--Offshore of Salt Point Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Salt Point map area, California. The vector data file is included in "Geology_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Geology and geomorphology--Offshore of San Francisco Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of San Francisco map area, California. The polygon shapefile is included in "Geology_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., ... |
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Geology and geomorphology--Offshore of San Gregorio Map Area, California
This part of SIM 3306 presents data for the geologic and geomorphic map of the Offshore of San Gregorio map area, California. The vector data file is included in "Geology_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey ... |
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Geology and geomorphology--Offshore of Santa Barbara, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Santa Barbara map area, California. The vector data file is included in "Geology_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., ... |
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Geology and geomorphology--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Geology_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., ... |
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Geology and geomorphology--Offshore of Tomales Point Map Area, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Geology_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris ... |
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Geology and geomorphology--Offshore of Ventura, California
This part of DS 781 presents geologic data of the Offshore of Ventura map area, California. The vector data file is included in "Geology_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., ... |
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Geology and geomorphology--Offshore Pigeon Point, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Geology_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. Marine geology and geomorphology were mapped in the Offshore Pigeon Point map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters. Offshore geologic units were delineated on the basis of ... |
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Geology and geomorphology--Offshore Refugio Beach, California
This part of DS 781 presents the geologic and geomorphic map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Geology_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G ... |
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Geology and geomorphology--Offshore Santa Cruz, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore Santa Cruz map area, California. The vector data file is included in "Geology_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K ... |
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Geology--Offshore of Coal Oil Point, California
This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Coal Oil Point map area, California. The vector data file is included in "Geology_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., ... |
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Geomorphic habitat units derived from 2009 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 11 September 2009 1 meter resolution NAIP aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (17 September 2009) for areas < MHHW and aerial lidar surveys (4-6 April 2009) for elevations > MHHW. |
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Geomorphic habitat units derived from 2011 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 03 September 2011* 0.3 meter resolution Microsoft/Digital Globe aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (25 August 2011) for areas < MHHW and aerial lidar surveys (13-15 April 2012) for elevations > MHHW. *Image date of 3-Sep-11 corrected in metadata. During product generation the imagery date was believed to be 8-25-2011, as reported by ... |
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Geomorphic habitat units derived from 2012 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 30 August 2012 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (28 August 2012) for areas < MHHW and aerial lidar surveys (17 October 2012) for elevations > MHHW. |
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Geomorphic habitat units derived from 2013 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 26 August 2013 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (16 September 2013) for areas < MHHW and aerial lidar surveys (17 October 2012) supplemented with NPS Elwha PlaneCam SfM photogrammetry data (19 September 2013) for elevations > MHHW. |
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Geomorphic habitat units derived from 2014 aerial imagery and elevation data for the Elwha River estuary, Washington
Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 28 August 2014 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (5-8 September 2014) for areas < MHHW and aerial lidar surveys (7 November 2014) supplemented with NPS Elwha PlaneCam SfM photogrammetry data (30 September 2014) for elevations > MHHW. |
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Geomorphic provinces in the Hudson Canyon region (polyline shapefile, geographic, WGS 84)
The Hudson Canyon begins on the outer continental shelf off the east coast of the United States at about 100-meters (m) water depth and extends offshore southeastward across the continental slope and rise. A multibeam survey was carried out in 2002 to map the bathymetry and backscatter intensity of the sea floor of the Hudson Canyon and adjacent slope and rise. The survey covered an area approximately 205 kilometers (km) in the offshore direction, extending from about 500 m to about 4,000 m water depth, and ... |
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Geophysical properties, geochronologic, and geochemical data of sediment cores collected from San Pablo Bay, California, October 17-20, 2016
Geophysical properties (P-wave velocity, gamma ray density, and magnetic susceptibility), geochronologic (radiocarbon, excess Lead-210, and Cesium-137), and geochemical data (organic carbon content and 60 element contents) are reported for select vibracores collected aboard the S/V Retriever October 17-20, 2016, in San Pablo Bay, California. Geophysical properties were measured with a Geotek Multi-Sensor Core Logger (MSCL). Radiocarbon was measured by accelerator mass spectrometry (AMS). Excess Lead-210 and ... |
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Georeferenced National Ocean Service (NOS) Hydrographic Sheets for Grand Bay, Mississippi, and Surrounding Areas
Hydrographic sheets (H-sheets) and nautical charts produced by the National Ocean Service (NOS) during the 1800s provide historic sounding (water depth) measurements of coastal areas. The data can be vectorized into a geographic information system (GIS), adjusted to a modern vertical datum, and converted into a digital elevation model to provide an interpretation of the historic seafloor elevation. These data were produced to provide an estimate of historical bathymetry for the Mississippi-Alabama coastal ... |
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Georeferenced scans of National Oceanic and Atmospheric Administration (NOAA) topographic sheets (T-Sheets) Collected Along the Fire Island and Great South Bay, New York, Coastline from 1834-1875
Topographic sheets (t-sheets) produced by the National Ocean Service (NOS) during the 1800s provide the position of past shorelines. The shoreline data can be vectorized into a geographic information system (GIS) and compared to modern shoreline data to calculate estimates of long-term shoreline rates of change. Many t-sheets were scanned and digitized by the National Oceanic and Atmospheric Administration (NOAA) and are available on the NOAA Shoreline web site (https://shoreline.noaa.gov/data/datasheets/t ... |
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Georeferenced Scans of National Oceanic and Atmospheric Administration (NOAA) T-Sheets Collected Along the New Jersey Coastline from 1839-1875
Historical shoreline surveys were conducted by the National Ocean Service (NOS), dating back to the early 1800s. The maps resulting from these surveys, often called t-sheets, provide a reference of historical shoreline position that can be compared to modern data to identify shoreline change. The t-sheets are stored at the National Archives and many have been scanned by the National Oceanic and Atmospheric Administration (NOAA) and are available on the NOAA Shoreline Web site (http://www.shoreline.noaa.gov ... |
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Geospatial Navigational Data Associated with Chirp Sub-Bottom Profiles Collected During USGS Field Activity Number 2014-303-FA in June and July 2014 from Fire Island, New York
During June 15-23 and July 10-12, 2014, the U.S. Geological Survey (USGS) conducted a nearshore geologic assessment, including bathymetric mapping, along Fire Island, New York (NY). This work was conducted in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near Fire Island, NY to assess the impacts of Hurricane Sandy to the area in October 2012. Geophysical data were collected as part of the Hurricane Sandy Supplemental Project (GS2-2B). The ... |
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Geospatial Navigational Data Associated with Chirp Sub-Bottom Profiles Collected During USGS Field Activity Number 2023-325-FA in June and August 2023 from the Chandeleur Islands, Louisiana
As part of the 2022 Disaster Supplemental project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterize stratigraphy near the Chandeleur Islands, Louisiana (LA) in June and August 2023. The purpose of this study was to conduct a morphologic and geologic assessment of the impacts of the 2020 and 2021 hurricane seasons within part of the Breton National ... |
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Geospatial Navigational Data Associated with Chirp Sub-Bottom Profiles Collected During USGS Field Activity Numbers 2021-326-FA and 2022-326-FA in 2021 and 2022 from Duck, North Carolina
In June/December 2021 and July 2022, the U.S. Geological Survey (USGS) and U.S. Army Corps of Engineers, Engineer Research and Development Center (USACE-ERDC) conducted repeat, nearshore geologic assessments, including bathymetric mapping, near Duck, North Carolina (NC). This work was performed in support of efforts to map the shoreface, characterize stratigraphy, and investigate changes in seafloor elevations near the USACE Field Research Facility and to measure the co-evolution of the morphology and ... |
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Geotagged sea-floor images and location of bottom images collected in Long Island Sound, Connecticut and New York, in fall 2017 and spring 2018 by the U.S. Geological Survey, University of Connecticut, and University of New Haven during field activities 2017-056-FA and 2018-018-FA (JPEG images, point shapefile, and CSV file)
Two marine geological surveys were conducted in Long Island Sound, Connecticut and New York, in fall 2017 and spring 2018 by the U.S. Geological Survey (USGS), University of Connecticut, and University of New Haven through the Long Island Sound Mapping and Research Collaborative. Sea-floor images and videos were collected at 210 sampling sites within the survey area, and surficial sediment samples were collected at 179 of the sites. The sediment data and the observations from the images and videos are used ... |
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Geotagged sea-floor images and locations of bottom images collected in Cape Cod Bay, Massachusetts, in September 2019 by the U.S. Geological Survey during field activity 2019-034-FA (JPEG images, point shapefile, and CSV file; GCS WGS 84)
Accurate data and maps of sea floor geology are important first steps toward protecting fish habitat, delineating marine resources, and assessing environmental changes due to natural or human impacts. To address these concerns the U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management (CZM), comprehensively mapped the Cape Cod Bay sea floor to characterize the surface and shallow subsurface geologic framework. Geophysical data collected include swath bathymetry, ... |
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Geotagged sea-floor photographs and location of bottom photographs collected in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey during field activities 2016-005-FA and 2017-022-FA (JPEG images, point shapefile, and CSV file)
Two marine geological surveys were conducted in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey (USGS) as part of an agreement with the Massachusetts Office of Coastal Zone Management to map the geology of the sea floor offshore of Massachusetts. Samples of surficial sediment and photographs of the sea floor were collected at 76 sampling sites within the survey area, and sea-floor videos were collected at 75 of the sites. The sediment data and the observations from the ... |
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GeoTIFF image of the backscatter intensity of the sea floor of the Hudson Canyon region (100-m resolution, Mercator, WGS 84)
The Hudson Canyon begins on the outer continental shelf off the east coast of the United States at about 100-meters (m) water depth and extends offshore southeastward across the continental slope and rise. A multibeam survey was carried out in 2002 to map the bathymetry and backscatter intensity of the sea floor of the Hudson Canyon and adjacent slope and rise. The survey covered an area approximately 205 kilometers (km) in the offshore direction, extending from about 500 m to about 4,000 m water depth, and ... |
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GeoTIFF image of the backscatter intensity of the sea floor of the Sandy Hook artificial reef (2-m resolution, Mercator, WGS 84)
The Sandy Hook artificial reef, located on the sea floor offshore of Sandy Hook, New Jersey was built to create habitat for marine life. The reef was created by the placement of heavy materials on the sea floor; ninety-five percent of the material in the Sandy Hook reef is rock. In 2000, the U.S. Geological Survey surveyed the area using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard (CCG) ship Frederick G. Creed. The purpose of this multibeam survey, done in cooperation with the ... |
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GeoTIFF image of the shaded-relief bathymetry of the sea floor of the Sandy Hook artificial reef (2-m resolution, Mercator, WGS 84)
The Sandy Hook artificial reef, located on the sea floor offshore of Sandy Hook, New Jersey was built to create habitat for marine life. The reef was created by the placement of heavy materials on the sea floor; ninety-five percent of the material in the Sandy Hook reef is rock. In 2000, the U.S. Geological Survey surveyed the area using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard (CCG) ship Frederick G. Creed. The purpose of this multibeam survey, done in cooperation with the ... |
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GeoTIFF image of the shaded-relief bathymetry, pseudo-colored by backscatter intensity, of the sea floor of the Hudson Canyon region (100-m resolution, Mercator, WGS 84)
The Hudson Canyon begins on the outer continental shelf off the east coast of the United States at about 100-meters (m) water depth and extends offshore southeastward across the continental slope and rise. A multibeam survey was carried out in 2002 to map the bathymetry and backscatter intensity of the sea floor of the Hudson Canyon and adjacent slope and rise. The survey covered an area approximately 205 kilometers (km) in the offshore direction, extending from about 500 m to about 4,000 m water depth, and ... |
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GeoTIFF image of the shaded-relief bathymetry, pseudocolored by backscatter intensity, of the sea floor of the Sandy Hook artificial reef (2-m resolution, Mercator, WGS 84)
The Sandy Hook artificial reef, located on the sea floor offshore of Sandy Hook, New Jersey was built to create habitat for marine life. The reef was created by the placement of heavy materials on the sea floor; ninety-five percent of the material in the Sandy Hook reef is rock. In 2000, the U.S. Geological Survey surveyed the area using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard (CCG) ship Frederick G. Creed. The purpose of this multibeam survey, done in cooperation with the ... |
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GIS data: Sediment Sample Locations Collected in July 2013 from the Northern Chandeleur Islands, Louisiana (U.S. Geological Survey Field Activity Number 13BIM05)
As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in July 2013. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to understand better the depositional and erosional processes that drive the morphologic evolution of barrier islands over ... |
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GIS data: Sediment Sample Locations Collected in March 2012 from the Northern Chandeleur Islands, Louisiana (U.S. Geological Survey Field Activity Number 12BIM01)
As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier ... |
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GIS data: Sediment Sample Locations Collected in September 2012 from the Northern Chandeleur Islands, Louisiana (U.S. Geological Survey Field Activity Number 12LGC02)
As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier ... |
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Global ferromanganese crust and abyssal ferromanganese nodule prospective occurrence regions
This data release is a polygon shapefile representing prospective occurrence regions of ferromanganese crusts and abyssal ferromanganese nodules on the seafloor throughout the global oceans. Polygons represent areas where oceanographic criteria, such as low sedimentation rate and moderate primary productivity, overlap with geologic criteria, including regions with appropriate seafloor morphology for each mineral type, such as seamounts and ridges or abyssal plains. The regions indicate where ferromanganese ... |
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Globorotalia truncatulinoides Sediment Trap Data in the Gulf of Mexico
Modern observations of planktic foraminifera from sediment trap studies help to constrain the regional ecology of paleoceanographically valuable species. Results from a weekly-resolved sediment trap time series (2008–2014) in the northern Gulf of Mexico demonstrate that 92% of Globorotalia truncatulinoides flux occurs in winter (January, February, and March), and that encrusted and non-encrusted individuals represent calcification in distinct depth habitats. Individual foraminiferal analysis (IFA) of G. ... |
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Globorotalia truncatulinoides Trace Element Geochemistry (Barium, Magnesium, Strontium, Manganese, and Calcium) from the Gulf of Mexico Sediment Trap
Observations of elevated barium-to-calcium ratio (Ba/Ca) in Globorotalia truncatulinoides have been attributed to contaminant phases, deep calcification depth and diagenetic processes. U.S. Geological Survey (USGS) scientists and their collaborators investigated intra- and inter-test Ba/Ca variability in the non-spinose planktic foraminifer, G. truncatulinoides, from a sediment trap time series (2009-2017) in the northern Gulf of Mexico (generally 27.5°N and 90.3°W) to gain insights into the environmental ... |
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GLORIA sidescan sonar mosaic
This image is a 250m version of the composite Gulf of Mexico GLORIA sidescan sonar mosaic. |
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GLORIA sidescan sonar mosaic
This GIS overlay is a component of the U. S Geological Survey, Woods Hole Field Center's, Gulf of Mexico ArcView GIS database. The Gulf of Mexico GIS database is intended to organize and display USGS held data and provide on-line (WWW) access to the data and/or metadata. |
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GNSS Topography Survey Data Collected from Tres Palmas, Rincón, Puerto Rico
This data release presents the post-processed Global Navigation Satellite System (GNSS) ground-survey data acquired during the installation of a camera system at Tres Palmas, Rincón, Puerto Rico (PR). The data contains topographic survey data collected during the installation of the camera. Data were collected on foot, by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) ... |
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Grab Sample Locations & Surficial Sediment Texture collected by the U.S. Geological Survey 1999-2003 offshore of the Grand Strand, South Carolina region (GRABS, Point shapefile)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
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Grain-size analyses of sediment cores from the Currituck Landslide Complex and upper slope adjacent to Baltimore Canyon collected on USGS Field Activity 2012-007-FA
Twenty-four piston cores (and associated trigger cores) were collected from the source zone of the Currituck Landslide Complex and upper slope adjacent to Baltimore Canyon by the U.S. Geological Survey and the University of Rhode Island Department of Ocean Engineering during an eight-day cruise aboard the R/V Hugh R. Sharp in September/October of 2012. These cores were analyzed for evidence of seafloor mass transport processes, with an emphasis on constraining the age and shallow stratigraphy of the ... |
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Grain size analyses of sediment cores from the New England Mud Patch collected on USGS Field Activity 2016-001-FA
Variability in sediment properties with depth and the thickness of individual sedimentary layers are critical determinants of seabed acoustic response. The New England Mud Patch (NEMP), located south of Cape Cod, is an unusual feature on the U.S. Continental Shelf in that it is composed of fine-grained sediment layers containing a relatively-homogeneous mix of sand, silt, and clay-sized particles bounded by more typical sandy shelf sediments. The unique characteristics and nature of this deposit is due to ... |
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Grain-size analysis of sediment samples collected in July 2016 by the U.S. Geological Survey off Town Neck Beach, Sandwich in Massachusetts, during field activity 2016-037-FA (CSV file and simplified shapefile)
Geophysical and geological survey data were collected off Town Neck Beach in Sandwich, Massachusetts, in May and July 2016. Approximately 130 linear kilometers of subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, sea floor photographs, and (or) video at 26 sites within the geophysical survey area. Sediment grab samples were collected at 19 of the 26 sampling sites and video and (or) photographic imagery of ... |
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Grain-size analysis results and locations of sediment samples collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activity 2018-049-FA (simplified point shapefile and CSV files)
The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg ... |
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Grain-Size and Data Analysis Results from Sediment Samples Collected at Crocker Reef, Florida, Between 2017 and 2019
Sediment samples were collected from undisturbed sections of the seafloor around Crocker Reef, Florida. Crocker Reef is a barrier reef located in the northern portion of the Florida Reef Tract that has been classified by Kellogg and others (2015) as a senile or dead reef consisting of areas of sand and rubble with only scattered stony coral colonies. Samples were collected from November 2017 to April 2019 to help ground truth coincident instrumentation deployed during the same time interval, which was used ... |
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Grainsize and Mineralogy Data of Sediments Samples Collected at Crocker Reef, Florida, 2013-2014
Understanding the processes that govern whether a coral reef is accreting (growing) or dissolving are fundamental to questions of reef health and resiliency. A total of 52 surficial sediment samples were collected within a 1-km x 1-km area around Crocker Reef in the Florida Keys, USA, between 2013 and 2014. Samples 1-35 were collected in July 2013 and samples 36-52 were collected in July 2014. The samples were processed using conventional, published techniques (see process step 2) to yield grain size and ... |
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Grain-Size and Site Data From Sediment Samples Collected at Seven Mile Island, New Jersey and Rockaway Peninsula, New York, Between May 2021 and June 2021
Sediment grab samples were collected from one onshore location and 32 undisturbed locations along the seafloor around Seven Mile Island, New Jersey (NJ) and Rockaway Peninsula, New York (NY). The sediment grab samples were collected in May and June of 2021 at locations within the area where multibeam bathymetry surveys were also conducted during the same trip. All sediment samples were analyzed using a laser diffraction Coulter LS13 320 particle-size analyzer to measure the grain size distribution of the ... |
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Grain-size data from core S3-15G, Monterey Fan, Central California
This data release presents sediment grain-size data from samples collected from core S3-15G, a 4.72-m long gravity core collected at a depth of 3,491 meters on the western levy of the Monterey Fan on May 31, 1978 (USGS Field Activity S-3-78-SC). |
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Grain-size data from vibracores collected in 2014 from Barnegat Bay, New Jersey
In response to the 2010 Governor’s Action Plan to clean up the Barnegat Bay–Little Egg Harbor (BBLEH) estuary in New Jersey, the U.S. Geological Survey (USGS) partnered with the New Jersey Department of Environmental Protection in 2011 to begin a multidisciplinary research project to understand the physical controls on water quality in the bay. Between 2011 and 2013, USGS scientists mapped the geological and morphological characteristics of the seafloor of the BBLEH estuary using a suite of geophysical ... |
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Grain Size Distribution of Surficial Sediments offshore of the Grand Strand, South Carolina region (GRAINSIZE_POLY, Polygon shapefile)
In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ... |
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Grain_Size-met: Archive of sediment physical properties and grain-size data for sediment samples collected offshore of Assateague Island, Maryland and Virginia
This data release serves as an archive of sediment physical properties and grain-size data for surficial samples collected offshore of Assateague Island, Maryland and Virginia, for comparison with surficial estuarine and subaerial sedimentological samples collected and assessed following Hurricane Sandy (Ellis and others, 2015 (http://doi.org/10.3133/ofr20151219); Smith and others, 2015 (http://doi.org/10.3133/ofr20151169); Bernier and others, 2016 (https://pubs.usgs.gov/ds/0999/)). The sediment samples ... |
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GrandBay_2010_Shoreline.shp - Grand Bay, Mississippi/Alabama, Shoreline Data Derived from 2010 Aerial Imagery
GrandBay_2010_Shoreline.zip features a digitized historical shoreline for the Grand Bay, Mississippi (MS) coastline (Pascagoula, MS to Point aux Pins, Alabama [AL]) derived from 2010 aerial imagery. Imagery of the Mississippi and Alabama coastlines was acquired from the National Agriculture Imagery Program (NAIP) and the city of Mobile, AL. Using ArcMap 10.3.1, the imagery was used to delineate and digitize the historical shoreline as either the Wet Dry Line (WDL) along sandy beaches or the vegetation edge ... |
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GrandBay_2012_Shoreline.shp - Grand Bay, Mississippi/Alabama, Shoreline Data Derived from 2012 Aerial Imagery
GrandBay_2012_Shoreline.zip features a digitized historical shoreline for the Grand Bay, Mississippi (MS) coastline (Pascagoula, MS to Bayou La Fourche Bay, Alabama [AL]) derived from 2012 aerial imagery. Imagery of the Mississippi and Alabama coastlines was acquired from the National Agriculture Imagery Program (NAIP). Using ArcMap 10.3.1, the imagery was used to delineate and digitize a coarse historical shoreline as either proximal Wet Dry Line along sandy beaches or proximal vegetation edge along the ... |
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Grid File of Historical Bathymetric Soundings for Mississippi and Alabama Derived from National Ocean Service (NOS) Hydrographic Sheets
Hydrographic sheets (H-sheets) and nautical charts produced by the National Ocean Service (NOS) during the 1800s provide historic sounding (water depth) measurements of coastal areas. The data can be vectorized into a geographic information system (GIS), adjusted to a modern vertical datum, and converted into a digital elevation model to provide an interpretation of the historic seafloor elevation. These data were produced to provide an estimate of historical bathymetry for the Mississippi-Alabama coastal ... |
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Grid of depth to basement in deep-water basins offshore Washington, Oregon, and California (cowbsmg.tif) based on data collected in 1984
COWBSMG is a 1000-m resolution grid of depth to basement off of Washington, Oregon, and California constructed from depth to basement contour data (cowbsm.shp, also in this data set) from 1:1,000,000-scale maps (Gardner and others, 1992, 1993a, 1993b). The range in depth to basement in this region is -5582 to -985 m with a mean of -3817 m. |
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Grid Representing the Holocene Ravinement Surface off the Coast of Washington and Oregon
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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Grid Representing the Last Lowstand of Sealevel off the Coast of Washington and Oregon
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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Grids Representing the Holocene Evolution off the Coast of Washington and Oregon at 1,000 Year Time Increments
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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Grids Representing the Holocene Evolution off the Coast of Washington and Oregon at 1,000 Year Time Increments - Shifted and with Landward DEM
Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ... |
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Ground Control Point Data from the Outer Banks, North Carolina, post-Hurricane Dorian, September 2019
The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project surveyed 34 features visible from the air to be used as ground control points (GCP) on the Outer Banks, North Carolina, on September 24 and 25, 2019, after the passing of Hurricane Dorian (U.S. landfall on September 6, 2019). Global Positioning System (GPS) data were collected in support of aerial imagery surveys documenting the storm impacts and subsequent recovery along the coast and will be used as control and check points in ... |
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Ground Control Point Locations and Photographs From North Topsail Beach and Camp Lejeune, North Carolina, June 2019
Scientist from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected xyz locations for 53 Ground Control Points (GCP) in North Topsail Beach and within the Camp Lejeune Marine Corps Base, North Carolina, June 12-14, 2019. During this study, Global Positing System (GPS) data were collected using a single Spectra SP80 Global Navigation Satellite System (GNSS) receiver affixed to a 2-meter (m) survey pole. Additional attributes pertaining to each survey point ... |
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Ground control point locations for the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. Twenty temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of: nine submerged targets consisting of small (80 centimeter X 80 centimeter) ... |
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Ground control point locations for the UAS survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the unoccupied aerial system (UAS) survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01. Twenty temporary ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns were distributed throughout the area to establish survey control. The GCP positions were measured ... |
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Ground control point locations for UAS survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA on 2019-06-05. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns ... |
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Ground control point locations for UAS survey of the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zone at Post Point, Bellingham Bay, WA on 2019-06-06. Nineteen temporary ground control points (GCPs) were distributed throughout each survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns ... |
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Ground control point locations for UAS survey of the intertidal zone at West Whidbey Island, WA, 2019-06-04
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zone at West Whidbey Island, WA on 2019-06-04. Twenty-five temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns and ... |
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Ground control point locations for UAS survey of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA, on 2019-06-03. Twelve temporary ground control points (GCPs) were distributed throughout each survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white ... |
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Ground control point locations for UAS survey of the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the Unmanned Aerial System (UAS) survey on of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta on 2018-10-23. The GCPs were used to establish ground control for the survey and consisted of 24 small (80 x 80 centimeter) square tarps with black-and-white cross patterns placed ... |
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Ground control point locations for UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the August 2017 unoccupied aerial system (UAS) surveys of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of ... |
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Ground control point locations for UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the July 2021 unoccupied aerial system (UAS) surveys of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small ... |
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Ground Penetrating Radar and Global Positioning System Data Collected from Central Florida Gulf Coast Barrier Islands, Florida, February-March 2021
A morphologically diverse and dynamic group of barrier islands along the Central Florida (FL) Gulf Coast (CFGC) form a 75-kilometer-long chain stretching from Anclote Key in the north to Egmont Key in the south. In 2021, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted ground penetrating radar (GPR) surveys on barrier islands located along the CFGC, in Pinellas County, FL. This study investigated the past evolution of the CFGC from field ... |
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Ground Penetrating Radar and Global Positioning System Data Collected from Fire Island, New York, March-April 2021
Fire Island, New York (NY) is a 50-kilometer (km) long barrier island system fronting the southern coast of Long Island, NY with relatively complex geology. In 2016, the U.S. Geological Survey (USGS) conducted ground penetrating radar (GPR) surveys and sediment sampling at Fire Island to characterize and quantify spatial variability in the subaerial geology (Forde and others, 2018; Buster and others, 2018). These surveys, in combination with historical data, allowed for a preliminary reconstruction of the ... |
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Ground-Penetrating Radar Data and Differential Global Positioning System Data Collected from Long Beach Island, New Jersey, April 2015
Scientists from the United States Geological Survey, St. Petersburg Coastal and Marine Science Center, U.S. Geological Survey Pacific Coastal and Marine Science Center, and students from the University of Hawaii at Manoa collected sediment cores, sediment surface grab samples, ground-penetrating radar (GPR) and Differential Global Positioning System (DGPS) data from within the Edwin B. Forsythe National Wildlife Refuge-Holgate Unit located on the southern end of Long Beach Island, New Jersey, in April 2015 ... |
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Ground Penetrating Radar (GPR) Profile Trace Data Collected from Dauphin Island, Alabama in April 2013
From April 13-20, 2013, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) conducted geophysical and sediment sampling surveys on Dauphin Island, Alabama, as part of field activity number 13BIM01. This dataset, Ground Penetrating Radar (GPR) Profile Trace Data Collected from Dauphin Island, Alabama in April 2013, contains the unprocessed, raw profile trace data obtained during this survey. |
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Gulf of Maine Contaminated Sediments Database (GOMCSDB shapefile)
The Contaminated Sediments Database for the Gulf of Maine provides a compilation and synthesis of existing data to help establish the environmental status of our coastal sediments and the transport paths and fate of contaminants in this region. This information, in turn, forms one of the essential bases for developing successful remediation and resource management policies. The Contaminated Sediments Database for the Gulf of Maine provides a compilation and synthesis of existing data to help establish the ... |
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Gulf of Mexico GLORIA sidescn sonar geologic interpretation
This GIS overlay is a component of the U. S Geological Survey, Woods Hole Field Center's, Gulf of Mexico ArcView GIS database. The Gulf of Mexico GIS database is intended to organize and display USGS held data and provide on-line (WWW) access to the data and/or metadata. |
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Gulf of Mexico Hydrocarbon Seeps (SEEPS.SHP)
This GIS overlay is a component of the U.S. Geological Survey, Woods Hole Science Center's, Gulf of Mexico GIS database. The Gulf of Mexico GIS database is intended to organize and display USGS held data and provide on-line (WWW) access to the data and/or metadata. |
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Gulf of Mexico Sediment Trap Foraminifera Data
The U.S. Geological Survey (USGS) deployed a sediment trap (McLane PARFLUX 78H) mooring in the northern Gulf of Mexico (27.5 °N and 90.3°W, water depth 1150 meters [m]) in January 2008 to collect seasonal time-series data on the flux and assemblage composition of planktic foraminifers. The trap was positioned in the water column at a depth of 700 m on the mooring cable to enable the collection of deeper dwelling species of planktic foraminifera. The trap contains 21 collection cups that were programmed to ... |
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Habitat--Monterey Canyon and Vicinity, California
This part of DS 781 presents data for the habitat map of the seafloor of the Monterey Canyon and Vicinity map area, California. The vector data file is included in "Habitat_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., ... |
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Habitat--Offshore of Gaviota Map Area, California
This part of DS 781 presents data for the habitat map of the Offshore of Gaviota Map Area, California. The vector data file is included in "Habitat_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. ... |
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Habitat--Offshore of Point Conception Map Area, California
This part of DS 781 presents data for the habitat map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Habitat_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point ... |
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HATTERAS_INDEX - Hatteras Island, North Carolina (geographic, WGS84)
The shoreline of Cape Hatteras, North Carolina, is experiencing long-term coastal erosion. In order to better understand and monitor the changing coastline, historical aerial imagery is used to map shoreline change. For the area of Hatteras Island from Cape Point to Oregon Inlet, fourteen aerial datasets from 1978-2002 were scanned and georeferenced for use in a Geographic Information System (GIS). Shoreline positions (high water line) were digitized from georeferenced imagery. The shoreline vectors were ... |
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hawaii_geo - Geologic attributes of the coastal zone of Hawaii, Hawaii
Geologic attributes of the coastal zone of Hawaii, Hawaii |
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hawaii_slp - Coastal Slope along the coastal zone of Hawaii, Hawaii
Coastal Slope along the coastal zone of Hawaii, Hawaii |
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High-resolution bathymetry data collected in 2004 in Skagit Bay, Washington
These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2004 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the USGS, PCMSC collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan-sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. ... |
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High-resolution bathymetry data collected in 2005 in Skagit Bay, Washington
These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2005 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar ... |
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High-resolution bathymetry data collected in 2007 in Skagit Bay, Washington
These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2007 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar ... |
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High-resolution bathymetry data collected in 2010 in Skagit Bay, Washington
These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2010 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar ... |
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High resolution double-difference relocations of earthquakes in and offshore Puerto Rico and Virgin Islands during the deployment of ocean bottom seismometers from mid-2015 to mid-2016
Puerto Rico is a Caribbean Island with a population of about 3.2 million people who are exposed to natural hazards including earthquakes and submarine landslides that can generate tsunamis. Previous work has shown seismicity offshore Puerto Rico especially between the coastline and the Puerto Rico Trench north of the island. The Puerto Rico Seismic Network maintains the local seismic network to record earthquakes, but these earthquake locations rely on seismic instruments that are all located on land. As ... |
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High-resolution magnetic susceptibility of sediment cores from the New England collected on USGS Field Activity 2016-001-FA
Variability in sediment properties with depth and the thickness of individual sedimentary layers are critical determinants of seabed acoustic response. The New England Mud Patch (NEMP), located south of Cape Cod, is an unusual feature on the U.S. Continental Shelf in that it is composed of fine-grained sediment layers containing a relatively-homogeneous mix of sand, silt, and clay-sized particles bounded by more typical sandy shelf sediments. The unique characteristics and nature of this deposit is due to ... |
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High-resolution multibeam backscatter data collected in 2004 for the northern Channel Islands region, southern California
This data release presents data for 5-m resolution acoustic-backscatter data of the northern Channel Islands region, southern California. In 2004 the U.S. Geological Survey, Pacific Coastal and Marine Science Center collected multibeam-bathymetry and acoustic-backscatter data in the northern Channel Islands region, southern California. The region was mapped aboard the R/V Ewing using a Kongsberg Simrad EM-1002 multibeam echosounder. These data were previously published on-line at http://pubs.usgs.gov/of ... |
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High-resolution multibeam bathymetry data collected in 2004 for the northern Channel Islands region, southern California
This data release presents data for 5-m resolution multibeam-bathymetry data of the northern Channel Islands region, southern California. In 2004 The U.S. Geological Survey, Pacific Coastal and Marine Science Center collected multibeam-bathymetry and acoustic-backscatter data in the northern Channel Islands region, southern California. The region was mapped aboard the R/V Ewing using a Kongsberg Simrad EM-1002 multibeam echosounder. These data were previously published on-line at http://pubs.usgs.gov/of ... |
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High-resolution multichannel seismic reflection data collected along the New England outer continental shelf, slope, and rise south of Martha's Vineyard and Nantucket, Massachusetts, U.S. Geological Survey Field Activity 2016-018-FA
High resolution multichannel seismic-reflection data were collected along the New England outer continental shelf, slope, and rise south of Martha's Vineyard and Nantucket, Massachusetts, aboard the Woods Hole Oceanographic Institute (WHOI) research vessel Neil Armstrong on June 11 - 12, 2016 in order to characterize the stratigraphy of a portion of the New England continental margin incised by submarine canyons and showing evidence of mass transport processes. The activity was conducted as a part of the ... |
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Hillshaded-relief image produced from the late Wisconsinan to early Holocene regressive unconformity (Ur) beneath Vineyard and western Nantucket Sounds, Massachusetts (GeoTIFF Image; UTM, Zone 19N, WGS 84)
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ... |
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Historical bathymetry soundings between 1916 and 1920 around the Mississippi and Alabama barrier islands
In order to characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi and Alabama (MSAL) barrier islands. One goal of this work was to create a time-series of bathymetric change maps around the islands between 1916 and 2016. |
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Historical coastal bluff edge positions at Barter Island, Alaska for the years spanning 1950 to 2020
This dataset includes one vector shapefile delineating the position of the top edge of the coastal permafrost bluffs at Barter Island, Alaska spanning seven decades, between the years of 1950 and 2020. Bluff-edge positions delineated from a combination of aerial photography, declassified satellite photography, and very-high resolution satellite imagery can be used to quantify the movement of the bluff edge through time. These data were used to calculate rates of change every 10 meters alongshore using the ... |
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Historical shoreline positions at Barter Island, Alaska for the years spanning 1947 to 2020
This dataset includes one vector shapefile delineating the position of the shorelines at Barter Island, Alaska spanning seven decades, between the years 1947 and 2020. Shoreline positions delineated from a combination of aerial photography, declassified satellite photography, and very-high resolution satellite imagery can be used to quantify the movement of the shoreline through time. These data were used to calculate rates of change every 10 meters alongshore using the Digital Shoreline Analysis System ... |
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Historic shoreline positions for Rincon, Puerto Rico 1936-2006 (shorelines.shp)
The 8 km of shoreline from Punta Higüero to Punta Cadena in Rincón, Puerto Rico is experiencing long-term coastal erosion. This study documents historical shoreline changes at Rincón for the period 1936-2005. Twelve historical shoreline positions were compiled from existing data, new orthophotography, and GPS field surveys. Shoreline vectors represent the high water line at the time of the survey. |
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Holocene evolution of sea-surface temperature and salinity in the Gulf of Mexico
Stable oxygen and carbon isotope composition (δ18O and δ13C) and magnesium-to-calcium (Mg/Ca) ratios were measured in the tests of planktic foraminiferal species, Globigerinoides ruber (white variety), in a northwestern Gulf of Mexico (GoM) sediment core 2010-GB2-GC1 collected from the Garrison Basin (26.67°N, 93.92°W) at a water depth of 1776 meters (m), aboard the R/V Cape Hatteras in April 2010. These measurements are used to generate sub-centennial-scale reconstructions of sea surface temperature ... |
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Holocene fluvial and estuarine (Qfe) and nearshore marine (Qmn) sediment thickness offshore of western and southern Martha's Vineyard and north of Nantucket, Massachusetts
Geologic, sediment texture, and physiographic zone maps characterize the sea floor south and west of Martha's Vineyard and north of Nantucket, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This ... |
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Hurricane Delta Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Louisiana coast and attributed to coastal processes during [Atlantic Basin] Hurricane Delta, which made landfall in the U.S. on October 9, 2020. |
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Hurricane Florence Assessment of Potential Coastal Change Impacts: NHC Advisory 57, 1100 AM EDT THU SEP 13 2018
This dataset defines storm-induced coastal erosion hazards for the Georgia, South Carolina, North Carolina, Virginia, Maryland, Delaware, New Jersey and New York coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Florence in September 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune ... |
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Hurricane Florence Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the southeast coast of the United States from North Carolina to Virginia and attributed to coastal processes during [Atlantic Basin] Hurricane Florence, which made landfall in the U.S. on September 14, 2018. |
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Hurricane Harvey Assessment of Potential Coastal Change Impacts: NHC Advisory 020, 700 AM CDT FRI AUG 25 2017
This dataset defines storm-induced coastal erosion hazards for the Texas and Louisiana coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Harvey in August 2017. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of coastal change: ... |
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Hurricane Irma Assessment of Potential Coastal Change Impacts: NHC Advisory 41, 800 AM EDT SAT SEPT 9 2017
This dataset defines storm-induced coastal erosion hazards for the Florida, Georgia and South Carolina coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Irma in September 2017. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of ... |
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Hurricane Irma Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Florida coast and attributed to coastal processes during [Atlantic Basin] Hurricane Irma, which made landfall in the U.S. on September 9, 2017. |
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Hurricane Isaias Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and pred |