Time-series measurements of oceanographic and water quality data collected in the Herring River, Wellfleet, Massachusetts, USA, November 2018 to November 2019
Restoration in the tidally restricted Herring River Estuary in Wellfleet, MA benefits from understanding pre-restoration sediment transport conditions. Submerged sensors were deployed at four sites landward and seaward of the Herring River restriction to measure water velocity, water quality, water level, waves, and seabed elevation. These data will be used to evaluate sediment dynamics and geomorphic change and inform marsh modeling efforts over tidal and seasonal timescales. |
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Time-series oceanographic data collected off Makua, Kauai, USA, August 2016
Time-series data of water-surface elevation, wave height, water-column currents, temperature were acquired for 6 days off the north coast of the island of Kauai, Hawaii in support of a study on the coastal circulation patterns and groundwater input to the coral reefs of Makua. |
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U.S. Geological Survey Oceanographic Time Series Data Collection
The oceanographic time series data collected by U.S. Geological Survey scientists and collaborators are served in an online database at http://stellwagen.er.usgs.gov/index.html. These data were collected as part of research experiments investigating circulation and sediment transport in the coastal ocean. The experiments (projects, research programs) are typically one month to several years long and have been carried out since 1975. New experiments will be conducted, and the data from them will be added to ... |
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Oceanographic time-series measurements collected in Bellingham Bay, Washington, USA, 2019 to 2021
Bottom-landing and floating platforms with instrumentation to measure currents, waves, water level, optical turbidity, water temperature, and conductivity were deployed at four locations in Bellingham Bay, Washington, USA. Platforms were deployed in three separate periods: July 30, 2019–November 14, 2019, November 19, 2019–February 5, 2020, and January 22, 2021–April 13, 2021. These data were collected to support studies of sediment delivery, transport, deposition, and resuspension in this Pacific ... |
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Documentation of the U.S. Geological Survey Oceanographic Time-Series Measurement Database
The U.S. Geological Survey (USGS) Oceanographic Time-Series Measurements Database contains oceanographic observations made as part of studies designed to increase understanding of sediment transport processes and associated ocean dynamics. This report describes the instrumentation and platforms used to make the measurements; the methods used to process and apply quality-control criteria and archive the data; and the data storage format. The report also includes instructions on how to access the data from ... |
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Sonde data to characterize physical and chemical water column properties of flooded caves (Ox Bel Ha and Cenote Crustacea) within the coastal aquifer of the Yucatan Peninsula, Quintana Roo, from December 2013 to January 2015
Natural cave passages penetrating coastal aquifers in the Yucatan Peninsula (Quintana Roo, Mexico) were accessed to investigate how regional meteorology and hydrology control dissolved organic carbon and methane dynamics in karst subterranean estuaries, the region of aquifers where fresh and saline waters mix. Three field trips were carried out in December 2013, August 2014, and January 2015 to obtain 1) physicochemical and 2) geochemical data from the water column and 3) temporal records of water chemistry ... |
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Time-series measurements of oceanographic and water quality data collected at Thompsons Beach and Stone Harbor, New Jersey, USA, September 2018 to September 2019 and March 2022 to May 2023
In October 2012, Hurricane Sandy made landfall in the Northeastern U.S., affecting ecosystems and communities of 12 states. In response, the National Fish and Wildlife Federation (NFWF) and the U.S. Department of Interior (DOI) implemented the Hurricane Sandy Coastal Resiliency Program, which funded various projects designed to reduce future impacts of coastal hazards. These projects included marsh, beach, and dune restoration, aquatic connectivity, and living shoreline installation, among others. To ... |
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Sound velocity profile data from an AML Oceanographic MVP30 collected in Little Egg Inlet and offshore the southern end of Long Beach Island, NJ, during USGS Field Activity 2018-001-FA (PNG images, CSV text, ASVP text, and point shapefile, GCS WGS 84)
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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Woods Hole Oceanographic Institute's Martha's Vineyard Coastal Observatory component locations (ESRI POINT SHAPEFILE, MVCO)
The Woods Hole Oceanographic Institution has built the Martha's Vineyard Coastal Observatory (MVCO) near South Beach in Edgartown, Massachusetts. The project was initiated by scientists in the Coastal and Ocean Fluid Dynamics Laboratory (COFDL) at WHOI, who will use the observatory to study coastal atmospheric and oceanic processes. Specifically, the observatory is expected to: * Provide a local climatology for intensive, short duration field campaigns. * Further facilitate regional studies of coastal ... |
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Local radiocarbon reservoir age (Delta-R) variability from the nearshore and open-ocean environments of the Florida Keys reef tract during the Holocene and associated U-series and radiocarbon data (Marine13 Radiocarbon Calibration Curve)
Holocene-aged corals from reef cores collected throughout the Florida Keys reef tract (FKRT) were dated using a combination of U-series and radiocarbon techniques to quantify the millennial-scale variability in the local radiocarbon reservoir age (ΔR) of the shallow water environments of south Florida. ΔR provides a measure of the deviation of local radiocarbon concentrations of marine environments from the global average and can be used as a tracer of oceanic circulation and local hydrology. U.S. ... |
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Local radiocarbon reservoir age (ΔR) variability from the nearshore and open-ocean environments of the Florida Keys reef tract during the Holocene and associated U-series and radiocarbon data (Marine20 Radiocarbon Calibration Curve)
68 Holocene-aged corals from reef cores collected throughout the Florida Keys reef tract (FKRT) were dated using a combination of U-series and radiocarbon techniques to quantify the millennial-scale variability in the local radiocarbon reservoir age (ΔR) of the shallow water environments of south Florida. ΔR provides a measure of the deviation of local radiocarbon concentrations of marine environments from the global average and can be used as a tracer of oceanic circulation and local hydrology. U.S. ... |
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Sound velocity profile data from an AML Oceanographic MVP30 and Minos X collected in Cape Cod Bay, Massachusetts during USGS Field Activity 2019-002-FA (PNG images, SVP text, and point shapefile, 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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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 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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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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September 2007 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 2007 Northern Gulf of ... |
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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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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 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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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 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 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 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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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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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 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 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 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 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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July 2010 Dauphin 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 2010 Dauphin Island U.S. ... |
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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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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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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 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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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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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 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 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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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 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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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 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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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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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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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 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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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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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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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 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 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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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 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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Sound Velocity Profiles collected in Nantucket Sound Massachusetts in the vicinity of Horseshoe Shoal, during USGS Field Activity 2022-001-FA using AML-3 LGR or AML Minos-X CTDSV sensors (PNG images, SVP text, and ESRI point shapefile, 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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected by the U.S. Geological Survey on Stellwagen Bank during three surveys 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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Shot point navigation at even 500 shot intervals for EdgeTech SB-512i chirp seismic-reflection data collected in 2014 by the U.S. Geological Survey offshore of Fire Island, NY (Esri point shapefile, GCS WGS 84)
The U.S. Geological Survey (USGS) conducted a geophysical and sampling survey in October 2014 that focused on a series of shoreface-attached ridges offshore of western Fire Island, NY. Seismic-reflection data, surficial grab samples and bottom photographs and video were collected along the lower shoreface and inner continental shelf. The purpose of this survey was to assess the impact of Hurricane Sandy on this coastal region. These data were compared to seismic-reflection and surficial sediment data ... |
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Trackline navigation for EdgeTech SB-512i chirp seismic-reflection data collected in 2014 by the U.S. Geological Survey offshore of Fire Island, NY (Esri polyline shapefile, GCS WGS 84)
The U.S. Geological Survey (USGS) conducted a geophysical and sampling survey in October 2014 that focused on a series of shoreface-attached ridges offshore of western Fire Island, NY. Seismic-reflection data, surficial grab samples and bottom photographs and video were collected along the lower shoreface and inner continental shelf. The purpose of this survey was to assess the impact of Hurricane Sandy on this coastal region. These data were compared to seismic-reflection and surficial sediment data ... |
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Location of bottom photographs along with images collected in 2014 by the U.S. Geological Survey offshore of Fire Island, NY (JPEG images and Esri point shapefile, Geographic, WGS 84)
The U.S. Geological Survey (USGS) conducted a geophysical and sampling survey in October 2014 that focused on a series of shoreface-attached ridges offshore of western Fire Island, NY. Seismic-reflection data, surficial grab samples and bottom photographs and video were collected along the lower shoreface and inner continental shelf. The purpose of this survey was to assess the impact of Hurricane Sandy on this coastal region. These data were compared to seismic-reflection and surficial sediment data ... |
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Location and analysis of sediment samples collected in 2014 by the U.S. Geological Survey offshore of Fire Island, NY (Esri point shapefile, GCS WGS 84)
The U.S. Geological Survey (USGS) conducted a geophysical and sampling survey in October 2014 that focused on a series of shoreface-attached ridges offshore of western Fire Island, NY. Seismic-reflection data, surficial grab samples and bottom photographs and video were collected along the lower shoreface and inner continental shelf. The purpose of this survey was to assess the impact of Hurricane Sandy on this coastal region. These data were compared to seismic-reflection and surficial sediment data ... |
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Location of sea floor video tracklines along with videos collected in 2014 by the U.S. Geological Survey offshore of Fire Island, NY (MP4 videos files and Esri polyline shapefile, Geographic, WGS 84)
The U.S. Geological Survey (USGS) conducted a geophysical and sampling survey in October 2014 that focused on a series of shoreface-attached ridges offshore of western Fire Island, NY. Seismic-reflection data, surficial grab samples and bottom photographs and video were collected along the lower shoreface and inner continental shelf. The purpose of this survey was to assess the impact of Hurricane Sandy on this coastal region. These data were compared to seismic-reflection and surficial sediment data ... |
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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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Sound velocity vs. depth plots and CTD cast data collected in April 2021 offshore Santa Cruz, California during USGS field activity 2021-619-FA
Sound velocity and CTD (conductivity, temperature, depth) cast data were collected at 9 sites offshore Santa Cruz, CA during USGS field activity 2021-619-FA in April of 2021. Aboard the R/V Parke Snavely (RVPS), a SonTek CastAway-CTD was used to collect these data at in the upper 67 meters of the water column. these data is provided in csv format, a shapefile of cast locations, as well as PNG plots of the speed of sound as a function of depth for each cast location. |
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CTD (conductivity-temperature-depth) data collected on 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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RBR sensor pressure and tidal data for two sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from April 2019 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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RBR sensor wave data for two sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from April 2019 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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CTD (conductivity-temperature-depth) data collected on 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
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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on Stellwagen Bank during U.S. Geological Survey field activity 2017-043-FA, aboard the R/V Auk, Aug. 22 and 23, 2017
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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CTD (conductivity-temperature-depth) data collected on 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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CTD (conductivity-temperature-depth) data collected on 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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Intrinsic and Extrinsic Calibration Data From USGS CoastCam deployed at Madeira Beach, Florida
A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research project to study the beach and ... |
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Imagery from USGS CoastCam deployed at Madeira Beach, Florida
A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. The images included in this data release were collected from January 21, 2017, to December 31, 2017. The camera is part of a U.S. Geological Survey (USGS) research project to study the beach and nearshore environment. USGS researchers analyzed the imagery collected ... |
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RAW sound velocity profile data from a Minos X collected from outer Cape Cod, Massachusetts during USGS Field Activity 2021-004-FA (PNG images, SVP text, and point shapefile, 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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USGS CoastCam at Tres Palmas, Rincón, Puerto Rico: Timestack Imagery and Coordinate Data
A digital video camera was installed at Tres Palmas, Rincón, Puerto Rico (PR) and faced west along the beach. Every hour during daylight hours, daily from August 27, 2019, to March 10, 2020, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, ... |
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USGS CoastCam at Isla Verde, Puerto Rico: 2018-2019 Timestack Imagery and Coordinate Data
A digital video camera was installed at Isla Verde Beach in San Juan, Puerto Rico (PR) and faced northeast along the beach. Every hour during daylight hours, daily from February 1, 2019, to July 15, 2019, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the ... |
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USGS CoastCam at Waiakāne, Moloka'i, Hawai'i: 2018 Timestack Imagery and Coordinate Data
A digital video camera was installed at Waiakāne, Moloka'i, Hawai'i (HI) and faced west along the beach. Every hour during daylight hours, daily from June 26, 2018, to September 20, 2018, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, and ... |
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USGS CoastCam at Isla Verde, Puerto Rico: 2018-2019 Intrinsic and Extrinsic Calibration Data
A digital video camera was installed at Isla Verde, Puerto Rico (PR) and faced northeast along the beach. Every hour during daylight hours, daily from February 1, 2019, to July 15, 2019, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research ... |
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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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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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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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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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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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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 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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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 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 (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 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 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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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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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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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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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 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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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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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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USGS CoastCam at Tres Palmas, Rincón, Puerto Rico: Intrinsic and Extrinsic Calibration Data
A digital video camera was installed at Tres Palmas, Rincón, Puerto Rico (PR) and faced west to view the beach and water offshore. Every hour during daylight hours, daily from August 27, 2019 to March 10, 2020, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological ... |
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USGS CoastCam at Waiakāne, Moloka'i, Hawai'i: 2018 Intrinsic and Extrinsic Calibration Data
A digital video camera was installed at Waiakāne, Moloka'i, Hawai'i (HI) and faced west along the beach. Every hour during daylight hours, daily from June 26, 2018, to September 20, 2018, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research ... |
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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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USGS CoastCam at Sand Key, Florida: Intrinsic and Extrinsic Calibration Data (Camera 1)
Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, the cameras collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements.. The cameras are part of a U.S. Geological Survey (USGS) research project to study the ... |
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USGS CoastCam at Sand Key, Florida: Intrinsic and Extrinsic Calibration Data (Camera 2)
Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, the cameras collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The images included in this data release were collected by camera 2 (c2) from May 29, ... |
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USGS CoastCam at Madeira Beach, Florida: Timestack Imagery and Coordinate Data
A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, and blue or monochrome pixel ... |
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USGS CoastCam at Sand Key, Florida: Timestack Imagery and Coordinate Data (Camera 2)
Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, daily from 2018 to 2022, the cameras collected raw video and produced snapshots and time-averaged image products. For camera 2, one such product that is created is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup ... |
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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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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 Isaias 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 coast of the Carolinas and attributed to coastal processes during [Atlantic Basin] Hurricane Isaias, which made landfall in the U.S. on August 4, 2020. |
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Hurricane Matthew Overwash Extents (version 2.0, 20210916)
The National Assessment of Coastal Change Hazards project 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, Georgia, North Carolina,and South Carolina coasts and attributed to coastal processes during [Atlantic Basin] Hurricane Matthew, which made landfall in the U.S. on October 8, 2018. |
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Hurricane Sally 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 and Alabama coast and attributed to coastal processes during [Atlantic Basin] Hurricane Sally, which made landfall in the U.S. on September 16, 2020. |
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Sea-floor environments 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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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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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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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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Tracklines of a multibeam survey of the sea floor of the Hudson Canyon region carried out in 2002 (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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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 shaded-relief bathymetry, illuminated from 315 degrees, 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 shaded-relief bathymetry, illuminated from 45 degrees, 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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Sound Velocity Profiles, Odim MVP 30 sound velocity profile data, USGS field activity 2017-003-FA, Mississippi River Delta front offshore of southeastern Louisiana (PNG images, ASVP text, and Esri point shapefile, GCS WGS 84).
High resolution bathymetric, sea-floor backscatter, and seismic-reflection data were collected offshore of southeastern Louisiana aboard the research vessel Point Sur on May 19-26, 2017, in an effort to characterize mudflow hazards on the Mississippi River Delta front. As the initial field program of a research cooperative between the U.S. Geological Survey, the Bureau of Ocean Energy Management, and other Federal and academic partners, the primary objective of this cruise was to assess the suitability of ... |
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Geochemical data to characterize chemical water column properties of flooded caves (Ox Bel Ha and Cenote Crustacea) within the coastal aquifer of the Yucatan Peninsula, Quintana Roo, from December 2013 to January 2015
Natural cave passages penetrating coastal aquifers in the Yucatan Peninsula (Quintana Roo, Mexico) were accessed to investigate how regional meteorology and hydrology control dissolved organic carbon and methane dynamics in karst subterranean estuaries, the region of aquifers where fresh and saline waters mix. Three field trips were carried out in December 2013, August 2014, and January 2015 to obtain 1) physicochemical and 2) geochemical data from the water column and 3) temporal records of water chemistry ... |
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Hydrological and chemical records from the flooded Ox Bel Ha cave system in the Yucatan Peninsula, Quintana Roo, from August 2014 to January 2015
Natural cave passages penetrating coastal aquifers in the Yucatan Peninsula (Quintana Roo, Mexico) were accessed to investigate how regional meteorology and hydrology control dissolved organic carbon and methane dynamics in karst subterranean estuaries, the region of aquifers where fresh and saline waters mix. Three field trips were carried out in December 2013, August 2014, and January 2015 to obtain 1) physicochemical and 2) geochemical data from the water column and 3) temporal records of water chemistry ... |
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Sound velocity profiles - locations, images, and text files for sound velocity profiles calculated from XBT and CTD casts conducted during USGS field activities 2017-001-FA and 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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USGS CoastCam at DUNEX: Intrinsic and Extrinsic Calibration Data (Camera 1)
Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ... |
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USGS CoastCam at DUNEX: Intrinsic and Extrinsic Calibration Data (Camera 2)
Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ... |
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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 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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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 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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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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September 2006 Post-Hurricane Wilma 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 2006 Post-Hurricane ... |
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March 2006 Mississippi and Alabama 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 2006 USGS Mississippi ... |
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September 2006 Mississippi and Alabama 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 2006 USGS Mississippi ... |
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September 2007 Southwest Florida Division of Emergency Management 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 Southwest Florida ... |
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June 2008 Alabama and Florida 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 June 2008 Louisiana, ... |
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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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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 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 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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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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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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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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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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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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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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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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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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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 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 Laura Overwash Extents
The National Assessment of Coastal Change Hazards project 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 Laura, which made landfall in the U.S. on August 27, 2020. |
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Hurricane Michael 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 Florida coast and attributed to coastal processes during [Atlantic Basin] Hurricane Michael, which made landfall in the U.S. on October 10, 2018. |
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Hurricane Zeta Overwash Extents
The National Assessment of Coastal Change Hazards project 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 Zeta, which made landfall in the U.S. on October 28, 2020. |
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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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Wave observations from bottom-mounted pressure sensors along the West side of Whidbey Island, Washington from Dec 2018 to Jan 2020
RBRduo pressure and temperature sensors mounted on aluminum frames, were moored in shallow (4-9 m) water depths along the West side of Whidbey Island, Washington, to measure wave heights and periods. Continuous pressure fluctuations were transformed into surface-wave observations of wave heights, periods, and frequency spectra at 30-minute intervals. |
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USGS CoastCam at DUNEX: Timestack Imagery and Coordinate Data (Camera 1)
Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ... |
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USGS CoastCam at DUNEX: Timestack Imagery and Coordinate Data (Camera 2)
Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ... |
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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for ILM site
This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024). |
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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for MHX site
This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024). |
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SWASH Model Water Level Time Series at Wrightsville Beach, NC, USA for PIER site
This data release contains model output of water level elevations resulting from deterministic simulations at Wrightsville Beach, North Carolina (NC), USA. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Birchler and others (2024). |
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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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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video Previews
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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Laboratory Observations of Oscillatory Flow Over Sand Ripples: Image Metadata
These data comprise laboratory observations of oscillatory flows over mobile sand ripples. The data were collected January 6-7, 2016, in the small-oscillatory flow tunnel (S-OFT) in the Sediment Dynamics Laboratory at the U.S. Naval Research Laboratory (NRL), Stennis Space Center, Mississippi (MS), while Donya Frank-Gilchrist was a National Research Council post-doctoral fellow there. The flow tunnel has a 2-m long acrylic test section which was filled with coarse quartz sand. A piston and flywheel were ... |
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Laboratory Observations of Oscillatory Flow Over Sand Ripples: Velocity Metadata
These data comprise laboratory observations of oscillatory flows over mobile sand ripples. The data were collected January 6-7, 2016, in the small-oscillatory flow tunnel (S-OFT) in the Sediment Dynamics Laboratory at the U.S. Naval Research Laboratory (NRL), Stennis Space Center, Mississippi (MS), while Donya Frank-Gilchrist was a National Research Council post-doctoral fellow there. The flow tunnel has a 2-m long acrylic test section which was filled with coarse quartz sand. A piston and flywheel were ... |
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Time-series measurements of pressure, conductivity, temperature, and water level collected in Puget Sound and Bellingham Bay, Washington, USA, 2018 to 2021
Pressure, conductivity, temperature, and water level relative the North American Vertical Datum of 1988 (NAVD88) were measured at seven locations in Puget Sound and Bellingham Bay, Washington, USA, from November 2, 2018 to June 4, 2021. These data were collected using submersible pressure-conductivity-temperature sensors mounted on piers to support studies of extreme water levels and flooding hazards in the region. |
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Water level and velocity measurements from the 2012 University of Western Australia Fringing Reef Experiment (UWAFRE)
This data release contains water level and velocity measurements from wave runup experiments performed in a laboratory flume setting. Wave-driven water level variability (and runup at the shoreline) is a significant cause of coastal flooding induced by storms. Wave runup is challenging to predict, particularly along tropical coral reef-fringed coastlines due to the steep bathymetric profiles and large bottom roughness generated by reef organisms. The 2012 University of Western Australia Fringing Reef ... |
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Wave observations from bottom-mounted pressure sensors in Bellingham Bay, Washington from Dec 2017 to Jan 2018
RBRduo pressure and temperature sensors (early 2015 generation), mounted on aluminum frames, were moored in shallow (< 6 m) water depths in Bellingham Bay, Washington, to capture wave heights and periods. Continuous pressure fluctuations are transformed into surface-wave observations of wave heights, periods, and frequency spectra at 30-minute intervals. |
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Wave observations from bottom-mounted pressure sensors in Skagit Bay, Washington from Dec 2017 to Feb 2018
RBRduo pressure and temperature sensors (early 2015 generation), mounted on aluminum frames, were moored in shallow (< 6 m) water depths in Skagit Bay to capture wave heights and periods. Continuous pressure fluctuations are transformed into surface-wave observations of wave heights, periods, and frequency spectra at 30-minute intervals. |
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Near-surface measurements of Conductivity-Temperature-Depth (CTD) data, Makua, Kauai, USA, August 2016
Transects of near-surface seawater properties were collected over the fringing reef off Makua, HI, on the north shore of Kauai using a Conductivity-Temperature-Depth (CTD) logger, either hand-carried or mounted to a kayak. The instrument returns temperature, salinity as a function of depth, and latitude/longitude. |
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Laboratory Observations of Variable Size and Shape Particles-Artificial Sand and Oil Agglomerates: November 2016 Velocity Data
Following marine oil spills, weathered oil can mix with sediment in the surf zone and settle to the seafloor to form mats up to hundreds of meters long. Wave action fragments these mats into 1- to 10-centimeter (cm) diameter sand and oil agglomerates (SOAs). SOAs can persist for years, becoming buried in or exhumed from the seafloor and/or transported cross-shore and alongshore (Dalyander and others, 2015). These fragments are angular near the source mat and become increasingly rounded as they are ... |
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Laboratory Observations of Variable Size and Shape Particles-Artificial Sand and Oil Agglomerates: November 2016 Video Data
Following marine oil spills, weathered oil can mix with sediment in the surf zone and settle to the seafloor to form mats up to hundreds of meters long. Wave action fragments these mats into 1- to 10-centimeter (cm) diameter sand and oil agglomerates (SOAs). SOAs can persist for years, becoming buried in or exhumed from the seafloor and/or transported cross-shore and alongshore (Dalyander and others, 2015). These fragments are angular near the source mat and become increasingly rounded as they are ... |
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Laboratory Observations of Variable Size and Shape Particles-Artificial Sand and Oil Agglomerates: June 2017 Velocity Data
Following marine oil spills, weathered oil can mix with sediment in the surf zone and settle to the seafloor to form mats up to hundreds of meters long. Wave action fragments these mats into 1- to 10-centimeter (cm) diameter sand and oil agglomerates (SOAs). SOAs can persist for years, becoming buried in or exhumed from the seafloor and/or transported cross-shore and alongshore (Dalyander and others., 2015). These fragments are angular near the source mat and become increasingly rounded as they are ... |
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Laboratory Observations of Variable Size and Shape Particles-Artificial Sand and Oil Agglomerates: June 2017 Video Data
Following marine oil spills, weathered oil can mix with sediment in the surf zone and settle to the seafloor to form mats up to hundreds of meters long. Wave action fragments these mats into 1- to 10-centimeter (cm) diameter sand and oil agglomerates (SOAs). SOAs can persist for years, becoming buried in or exhumed from the seafloor and/or transported cross-shore and alongshore (Dalyander and others, 2015). These fragments are angular near the source mat and become increasingly rounded as they are ... |
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Subtropical Storm Alberto Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0800 AM EDT SUN MAY 27 2018
This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida 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 Subtropical Storm Alberto in May 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the ... |
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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: False-Floor Experiment Flow Velocity and Shear Stress
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: False-Floor Experiment Interpretive Video
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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Laboratory Observations of Artificial Sand and Oil Agglomerates: Video and Velocity Data: Sea Floor Interaction Experiment Preview Video (GoPro)
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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Laboratory Observations of Artificial Sand and Oil Agglomerates: Video and Velocity Data: Sea Floor Interaction Experiment Video (GoPro)
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Flow Velocity
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ... |
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Tropical Storm Bill Assessment of Potential Coastal-Change Impacts: NHC Advisory 2, 0900 AM UTC MON JUN 16 2015
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 Tropical Storm Bill in June 2015. 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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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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Tropical Storm Colin Assessment of Potential Coastal Change Impacts: NHC Advisory 4, 0500 AM EDT MON JUN 06 2016
This dataset defines storm-induced coastal erosion hazards for the Florida 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 Tropical Storm Colin in June 2016. Storm-induced water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of the three types of coastal change: collision ... |
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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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Tropical Storm Gordon Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0700 AM CDT TUE SEP 04 2018
This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida 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 Tropical Storm Gordon in September 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the ... |
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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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Tropical Storm Hermine Assessment of Potential Coastal Change Impacts: NHC Advisory 20, 0500 AM EDT FRI SEP 02 2016
This dataset defines storm-induced coastal erosion hazards for the Florida 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 Tropical Storm Hermine in September 2016. 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 Matthew Overwash Extents
The National Assessment of Coastal Change Hazards project 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 Florida to North Carolina and attributed to coastal processes during [Atlantic Basin] Hurricane Matthew, which made landfall in the U.S. on October 8, 2016. |
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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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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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Hurricane Joaquin Assessment of Potential Coastal Change Impacts: NHC Advisory 27, 0800 AM EDT SUN OCT 04 2015
This dataset defines storm-induced coastal erosion hazards for the North Carolina, Virginia, Maryland, Delaware, New Jersey, New York, Rhode Island and Massachusetts 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 Joaquin in October 2015. Storm-induced water levels, due to both surge and waves, were compared to beach and dune ... |
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Massachusetts Mean (interpolated) Beach Slope Point Data
The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes for Massachusetts for data collected at various times between 2000 and 2013. |
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Massachusetts raw (non-interpolated) Beach Slope Point Data
The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Northeast Atlantic Ocean for Massachusetts for data collected at various times between 2000 and 2013 |
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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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Hurricane Maria Assessment of Potential Coastal Change Impacts: NHC Advisory 41, 0800 AM EDT TUE SEPT 26 2017
This dataset defines storm-induced coastal erosion hazards for the North Carolina, Virginia, Maryland and Delaware 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 Maria 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 ... |
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Hurricane Matthew Assessment of Potential Coastal Change Impacts: NHC Advisory 037, 800 AM EDT FRI OCT 07 2016
This dataset defines storm-induced coastal erosion hazards for the Florida, Georgia, South Carolina and North 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 Matthew in October 2016. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of ... |
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Hurricane Michael Assessment of Potential Coastal Change Impacts: NHC Advisory 15, 0400 AM CDT WED OCT 10 2018
This dataset defines storm-induced coastal erosion hazards for the Alabama and Florida 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 Michael in October 2018. 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 Nate Assessment of Potential Coastal Change Impacts: NHC Advisory 12, 0800 AM EDT SAT OCT 07 2017
This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida 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 Nate in October 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 ... |
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Hurricane Sandy Assessment of Potential Coastal Change Impacts: NHC Advisory 29, 1100 AM EDT MON OCT 29 2012
This dataset defines hurricane-induced coastal erosion hazards for the Delaware, Maryland, New Jersey, New York, and Virginia 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 Sandy in October 2012. Hurricane-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the ... |
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Santa_Rosa_Island_2021_SBES_xyz: Single-Beam Bathymetry Data Collected During USGS Field Activity Number 2021-322-FA Offshore of Santa Rosa Island, Florida
From June 2 through 9, 2021, the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). Santa_Rosa_Island_2021_SBES_xyz.zip is a xyz point file dataset of field activity number (FAN) 2021-322-FA single-beam bathymetry (SBB) data collected concurrently with subbottom data to provide a current seafloor ... |
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National Assessment of Hurricane-Induced Coastal Erosion Hazards: 2021 Update
This dataset contains information on the probabilities of hurricane-induced erosion (collision, inundation and overwash) for each 1-kilometer (km) section of the United States [Gulf of Mexico and Atlantic] coast for category 1-5 hurricanes. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct landfall of category 1-5 hurricanes. Hurricane-induced water levels, due ... |
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South Carolina Coastal Erosion Study Data Report for Observations : October 2003 - April 2004
Oceanographic observations have been made at nine locations in Long Bay, South Carolina from October 2003 through April 2004. These sites are centered around a shore-oblique sand feature that is approximately 10 km long, 2 km wide, and in excess of 3 m thick. The observations were collected through a collaborative effort with the U.S. Geological Survey, the University of South Carolina, and Georgia Institute of Technology Savannah Campus as part of a larger study to understand the physical processes that ... |
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CTD (conductivity-temperature-depth) data collected by the U.S. Geological Survey on Stellwagen Bank during six surveys 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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South Florida mangrove peat radiocarbon metadata
In 2016, U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) researchers and academic collaborators collected cores of mangrove peat from two islands in the Florida Keys: Snipe Key (24.679°N, 81.653°W) and Swan Key (25.349°N, 80.251°W). This data release contains the radiocarbon ages and associated data for peat samples analyzed throughout the two cores (SNK-16-C1 and SBC-16-C10). |
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Uranium-Thorium Ages for Late Holocene Corals from the Southeast Florida Nearshore Ridge Complex
This data release (Modys and others, 2023a) compiles Uranium-Thorium (U-Th) dating data for late Holocene coral samples collected from the Nearshore Ridge Complex (NRC) off Pompano Beach, Southeast Florida (SEFL). The samples were collected under Scientific Activity Licenses (SAL) from the Florida Fish and Wildlife Conservation Commission (SAL-18-1659A-SRP) and with permission from Broward County Environmental Protection and Growth Management. |
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Late Pleistocene coral ages and elevations from south Florida
This data release compiles Uranium-series (U-series) data and descriptive collection information (such as sample/core identifier, location, elevation, etc.) for late Pleistocene coral subsamples from coral reef cores previously collected throughout the Florida Keys (Florida) by U.S. Geological Survey (USGS) researchers. The samples were collected under scientific research permits from the Florida Keys National Marine Sanctuary (FKNMS) and U.S. National Park Service (NPS) and all samples are currently ... |
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Geochemical analysis of authigenic carbonates and chemosynthetic mussels at Atlantic Margin seeps (ver. 2.0, March 2019)
Isotopic analyses of authigenic carbonates and methanotrophic deep-sea mussels, Bathymodiolus sp., was performed on samples collected from seep fields in the Baltimore and Norfolk Canyons on the north Atlantic margin. Samples were collected using remotely operated underwater vehicles (ROVs) during three different research cruises in 2012, 2013, and 2015. Analyses were performed by several different laboratories, and the results are presented in spreadsheet format. |
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Geochemical analysis of seeps along the Queen Charlotte Fault
Geochemical analyses of authigenic carbonates, bivalves, and pore fluids were performed on samples collected from seep fields along the Queen Charlotte Fault, a right lateral transform boundary that separates the Pacific and North American tectonic plates. Samples were collected using grab samplers and piston cores, and were collected during three different research cruises in 2011, 2015, and 2017. |
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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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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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Radiometric ages and descriptive data for Holocene corals from southeast Florida
This data release compiles descriptive information (location, water depth, etc.) and radiometric ages from corals collected through the Southeast Florida Continental Reef Tract (SFCRT; Figure 1). The database includes data from studies published between 1977 and 2015 as well as previously unpublished data. The samples were originally collected using coral-reef coring or other geologic sampling methods. Many of the samples are presently stored in the U.S. Geological Survey (USGS) Core Archive at the St. ... |
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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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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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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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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 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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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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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 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 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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