Biological and physical processes

All continuing activities, functions, and phenomena associated with organisms and non-living matter.
This category is also used for bioenergetic processes.
Subtopics:
Coastal processes (1354 items)
Fires (13 items)
Geologic processes (708 items)
Ocean processes (382 items)

2130 results listed alphabetically [list by similarity]
10cct01_v2rbf_50m.tif: 50-Meter Resolution Grid of Swath Bathymetry Data Collected Offshore of Cat Island, Mississippi in March 2010

In March of 2010, the U.S. Geological Survey (USGS) conducted geophysical surveys east of Cat Island, Mississippi. The efforts were part of the USGS Gulf of Mexico Science Coordination partnership with the U. S. Army Corps of Engineers (USACE) to assist the Mississippi Coastal Improvements Program (MsCIP) and the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazards Susceptibility Project by mapping the shallow geological stratigraphic framework of the Mississippi Barrier Island Complex. The data ...

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1869 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

1869 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1869. In 2002, NOAA published digitized shorelines for T-sheet (T-1097), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted.

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1922 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

1922 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1922. In 2002, NOAA published digitized shorelines for T-sheet (T-3920), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted.

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1950 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

1950 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1950. In 2002, NOAA published digitized shorelines for T-sheet (T-9393), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted.

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1970s Shorelines for the Main Island of Puerto Rico

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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1970s Shorelines for Vieques and Culebra, Puerto Rico

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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1983 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

Shorelines were derived from the National High Altitude Photography (NHAP) program. The NHAP was coordinated by the U.S. Geological Survey as an interagency project to acquire cloud-free aerial photographs at a specific altitude above mean terrain elevation. Two different camera systems were used to obtain simultaneous coverage of black-and-white (BW) and color infrared (CIR) aerial photographs over the conterminous United States. Black-and-white aerial photographs were obtained on 9-inch film from an ...

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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 Digitized Shoreline for Breton Island, Louisiana(Geographic, NAD83)

Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center's Digital Orthophoto Quarter Quads (DOQQ) images collected on January 24, 1998. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) Version 4.0.

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1998 East Coast NASA/NOAA/USGS Winter ATM Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Atlantic Coast ...

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1998 Fall Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Fall Gulf Coast ...

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1998 MA, NY, MD, and VA USGS/NASA ATM2 Lidar-derived dune crest, toe and shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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1998 Southeast ATM Lidar-derived dune crest, toe and shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1998 Southeast USGS/NASA ...

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1999 Atlantic Coast NASA/NOAA/USGS ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Floyd

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1999 Atlantic Coast ...

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1999 Fall Texas USGS/NASA/NOAA ATM Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 1999 Fall Gulf Coast ...

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2000 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2000 U.S. Army Corps of ...

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2001 Gulf Coast USGS/NASA ATM Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2001 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 U.S. Army Corps of ...

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2001 Vectorized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements collected by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA) on September 07-09, 2001. Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft ...

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2002 NOAA/NASA/USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 Post-Hurricane Lili ...

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2002 Post-Tropical Storm Fay University of Texas Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2002 University of Texas ...

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2002 USGS Virgina and Maryland Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ...

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2003 NOAA Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2003 NOAA Oahu lidar ...

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2003 Pre- and Post-Hurricane Isabel USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2003 Pre- and Post ...

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2004 Digitized Shoreline for Breton Island, Louisiana(Geographic, NAD83)

Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center’s Digital Orthophoto Quarter Quads (DOQQ) images collected on January 20, 2004. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital Shoreline Analysis System (DSAS) version 4.0.

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2004 Maine NOAA Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 NOAA Maine lidar ...

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2004 Post-Hurricane Charley West Florida EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ...

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2004 Post-Hurricane Frances USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ...

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2004 Post-Hurricane Ivan Northern Gulf of Mexico EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 USGS Post-Ivan ...

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2004 Post-Hurricane Jeanne USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Post-Hurricane ...

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2004 Pre-Hurricane Ivan Eastern Gulf Coast United States Army Corps of Engineers (USACE) Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 Pre-Ivan Eastern ...

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2004 USACE Post-Ivan Florida Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2004 U.S. Army Corps of ...

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2005-2006 Atlantic Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005-2006 Atlantic Coast ...

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2005 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center’s Digital Orthophoto Quadrangle (DOQ) images collected on November 17, 2005. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital Shoreline Analysis System (DSAS) version 4.0.

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2005 EAARL Fire Island Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Fire Island USGS ...

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2005 East Coast (DE, MD, NJ, NY, NC, and VA) USACE NCMP Topobathy Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2005 Padre Island USGS EAARL Lidar-derived dune crest, toe and shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Experimental ...

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2005 Post-Hurricane Dennis Florida U.S. Army Corps of Engineers Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USACE Post-Dennis ...

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2005 Post-Hurricane Katrina EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 Post-Hurricane ...

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2005 USGS Post-Hurricane Rita Texas and Louisiana Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2005 USGS Post-Hurricane ...

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2006 FEMA Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2006 Federal Emergency ...

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2007 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

Shorelines were derived from the National Agriculture Imagery Program (NAIP) digital ortho imagery collected on October 11, 2007. This dataset contains digitized shorelines created from the NAIP imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) Version 4.0.

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2007 Northeast Barrier Islands USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Northeast Barrier ...

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2007 South Florida FDEM Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 Florida Division of ...

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2007 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2007 U.S. Army Corps of ...

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2008 Assateague Island USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Assateague Island ...

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2008 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center high-resolution orthorectified images collected on October 01, 2008. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital Shoreline Analysis System (DSAS) Version 4.0.

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2008 North Carolina and Virginia NOAA/NGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Atlantic Coast ...

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2008 Post-Hurricane Gustav Northern Gulf of Mexico USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 Post-Hurricane ...

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2008 South Louisiana USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 South Louisiana ...

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2008 USGS Post-Hurricane Ike Texas Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2008 USGS Post-Hurricane ...

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2009 Cape Canaveral USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Cape Canaveral ...

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2009 Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Florida U.S. Army ...

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2009 North Carolina USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 U.S. Army Corps of ...

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2009 Post-Nor’Ida 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-Nor’Ida USGS ...

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2009 Western Gulf of Mexico USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2009 Western Gulf of ...

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2010-2022 New Jersey and New York Beach Shoreline Change

This dataset defines shoreline change rates for each 10-meter (m)-wide profile calculated via endpoint rate and linear regression from Himmelstoss and others (2018). Shoreline change rates were calculated for two time periods: pre-Sandy (2010-2012) and post-Sandy (2012-2022). The profiles were derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife ...

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2010-2022 New Jersey and New York Beach Volumes

This dataset defines the volume of sand along a 10-meter (m) wide profile between the seaward-most dune toe and the mean high water shoreline derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife Foundation (NFWF)-funded project entitled “Monitoring Hurricane Sandy Beach and Marsh Resilience in New York and New Jersey” (NFWF project ID 2300.16 ...

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2010 Alabama and Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Alabama and Florida ...

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2010 Assateague Island National Seashore USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Assateague Island ...

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2010 Delaware USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Delaware U.S. Army ...

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2010 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

Shorelines were derived from the National Agriculture Imagery Program (NAIP) digital ortho imagery collected on May 10, 2010. This dataset contains digitized shorelines created from the NAIP imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) version 4.0.

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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 lidar-derived mean high water shoreline for the coast of South Carolina

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2010 Louisiana and Mississippi USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Louisiana and ...

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2010 Maryland USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Maryland U.S. Army ...

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2010 New Jersey USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 New Jersey U.S. ...

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2010 New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 New York U.S. Army ...

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2010 Northeast Atlantic USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Northeast Atlantic ...

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2010 profile-derived mean high water shorelines of the North Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2010 profile-derived mean high water shorelines of the South Coast of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2010 Shorelines for Vieques, Culebra, and the Main Island of Puerto Rico

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2010 Southeast Atlantic USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Southeast Atlantic ...

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2010 Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2010 Virginia U.S. Army ...

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2011 East Coast New York/New Jersey NOAA/NGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 East Coast New York ...

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2011 Northern Gulf Coast USACE Lidar-derived dune crest, toe and shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 Northern Gulf Coast ...

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2011 profile-derived mean high water shorelines of the Outer Cape of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2011 profile-derived mean high water shorelines of the South Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2011 USGS New York Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2011 Atlantic Coast ...

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2012-2014 contour-derived mean high water shorelines of the Massachusetts coast used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2012 Digitized Shoreline for Breton Island, Louisiana(Geographic, NAD83)

Shorelines were derived from a U.S. Geological Survey Earth Resources Observations and Science Center (EROS) high-resolution orthorectified image that was collected on October 20, 2012 over Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) version 4.0.

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2012 Post-Hurricane Isaac USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2012 Post-Hurricane Sandy Fire Island, New York Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2012 Post-Hurricane Sandy Long Island, New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2012 Post-Hurricane Sandy New Jersey USGS EAARL-B Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2012 Post-Hurricane Sandy Northeast Atlantic Coast USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post ...

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2012 Post-Sandy New York and New Jersey USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Sandy New York ...

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2012 Pre-Hurricane Sandy Fire Island National Seashore, USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Post-Hurricane ...

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2012 Pre-Sandy New York and New Jersey USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Pre Hurricane Sandy ...

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2012 profile-derived mean high water shorelines of Martha's Vineyard, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2012 profile-derived mean high water shorelines of Nantucket, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013-14 Massachusetts Lidar-Derived Dune Crest Point Data

This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ...

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2013-14 Massachusetts Lidar-Derived Dune Toe Point Data

This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ...

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2013-2014 Northeast USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013-2014 Post� ...

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2013-2014 profile-derived mean high water shorelines of the South Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 Dauphin Island USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Dauphin Island ...

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2013 Maine USACE/NAE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Maine United States ...

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2013 NOAA Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 National Oceanic ...

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2013 profile-derived mean high water shorelines of Martha's Vineyard, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of Nantucket, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of the north shore of Martha's Vineyard, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of the north shore of Nantucket, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 profile-derived mean high water shorelines of the South Coast of MA used in shoreline change analysis.

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2013 USACE NAE Topobathy Lidar: Maine Point Cloud files with Orthometric Vertical Datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ...

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2013 USACE Oahu Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 U.S. Army Corps of ...

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2013 Vectorized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

Shorelines were derived from a U.S. Geological Survey topographic lidar survey that was conducted on July 12-14, 2013 over Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana and published in USGS Data Series 838. Photo Science, Inc., was contracted by the USGS to collect and process these data. Lidar data were acquired around portions of both the Alabama and Louisiana barrier islands; however, this dataset only contains shorelines created from data acquired from ...

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2014–2015 Ocean Current and Pressure Time Series Data from the Upper Florida Keys: Crocker Reef, FL

Three Acoustic Doppler current profilers (ADCP), a current meter and a pressure logger were deployed at Crocker Reef, a senile (dead) barrier reef located in the northern portion of the Florida Reef Tract from December 12, 2014 to January 30, 2015 to quantify flow characteristics in various sub-regions. A Nortek Aquadopp current meter was deployed on the reef flat and configured to measure three-dimensional flow velocities at the middle of the water column. Current measurements were taken at a rate of 1 ...

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2014–2015 Ocean Current and Pressure Time Series Data from the Upper Florida Keys: Crocker Reef, FL

Three Acoustic Doppler current profilers (ADCP), a current meter and a pressure logger were deployed at Crocker Reef, a senile (dead) barrier reef located in the northern portion of the Florida Reef Tract from December 12, 2014 to January 30, 2015 to quantify flow characteristics in various sub-regions. Two SonTek Argonaut-XR current profilers were deployed on the reef flat and configured to measure three-dimensional flow velocities throughout the water column. Both current profilers sampled at a rate of ...

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2014–2015 Ocean Current and Pressure Time Series Data from the Upper Florida Keys: Crocker Reef, FL

Three Acoustic Doppler current profilers (ADCP), a current meter and a pressure logger were deployed at Crocker Reef, a senile (dead) barrier reef located in the northern portion of the Florida Reef Tract from December 12, 2014 to January 30, 2015 to quantify flow characteristics in various sub-regions. A RBR pressure logger was deployed on the fore reef and configured to measure pressure at a rate of 2 hertz (Hz). The logger was positioned at a water depth of 14 meters, the deepest part of the fore reef) ...

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2014–2015 Ocean Current and Pressure Time Series Data from the Upper Florida Keys: Crocker Reef, FL

Three Acoustic Doppler current profilers (ADCP), a current meter and a pressure logger were deployed at Crocker Reef, a senile (dead) barrier reef located in the northern portion of the Florida Reef Tract from December 12, 2014 to January 30, 2015 to quantify flow characteristics in various sub-regions. A RDI Workhorse Monitor current profiler was deployed on the reef flat and configured to measure three-dimensional flow velocities throughout the water column. Current measurements were taken at a rate of 1 ...

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2014 East Coast Maine USACE/NAE ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast Maine ...

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2014 East Coast New Hampshire USACE/NAE ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast New ...

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2014 East Coast Rhode Island NOAA/NGS ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Sandy

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 East Coast Rhode ...

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2014 Mobile County, Alabama Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2014 Mobile County, ...

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2014 Post-Hurricane Sandy SC to NY NOAA NGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2014 profile-derived mean high water shorelines of Cape Cod Bay, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2014 profile-derived mean high water shorelines of the North Shore of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2014 profile-derived mean high water shorelines of the Outer Cape of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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2014 profile-derived mean high water shorelines of the south shore of Cape Cod, MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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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 Vectorized Shoreline for Breton Island, Louisiana (Geographic, NAD83)

Shorelines were derived from a U.S. Geological Survey topographic lidar survey that was conducted on January 16-18, 2014 over Breton Island, Louisiana and released under USGS field activity number 14LGC01. Quantum Spatial was contracted by the USGS to collect and process these data. This dataset contains vectorized shorelines created from data acquired from Breton Island, Louisiana. Shorelines were vectorized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital ...

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2015-330-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile 1,000-shot-interval locations.

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2015-330-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a point dataset of field activity number (FAN) 2015-330-FA chirp subbottom profile start of trackline locations.

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2015-330-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2015-330-FA Offshore of Dauphin Island, Alabama, September 2015

From September 16 through 23, 2015, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Dauphin Island, Alabama. Geophysical data were collected as part of the Alabama Barrier Island Restoration Feasibility Study. This shapefile represents a line dataset of field activity number (FAN) 2015-330-FA chirp tracklines.

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2015 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2015 Mississippi and Alabama USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2015 Mississippi and ...

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2015 USACE Florida Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2015 U.S. Army Corps of ...

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2016 Florida East Coast USACE Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2016 U.S. Army Corps of ...

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2016 Massachusetts NOAA Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2016 NOAA Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2016 USACE Gulf Coast Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2016 U.S. Army Corps of ...

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2016 USACE Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2016 USACE Post-Hurricane Matthew Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2017-2018 lidar-derived mean high water shoreline for the coast of South Carolina

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 East Coast USACE/FEMA ATM Lidar-Derived Dune Crest, Toe and Shoreline, post-Hurricane Irma

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2017 Atlantic Coast ...

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2017 Florida West Coast NOAA Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches.Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2017 Georgia through New York USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

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2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Fear to the South Carolina border (NCwest)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 lidar-derived mean high water shoreline for the coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 lidar-derived mean high water shoreline for the coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 lidar-derived mean high water shoreline for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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2017 USGS Lidar: Chenier Plain, LA Point Cloud files with Orthometric Vertical Datum North American Vertical Datum of 1988 (NAVD88) using GEOID12B

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2001 Gulf Coast USGS ...

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2018 Alabama and Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 East Coast (NC) USACE NCMP Topobathy Lidar Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 East Coast (VA, NC, SC) USACE NCMP Post-Florence Topobathy Lidar-Derived Dune Crest, Toe, and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 mean high water shoreline of the coast of MA used in shoreline change analysis

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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2018 Mean High Water Shorelines of the Puerto Rico coast used in Shoreline Change Analysis

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photos or topographic surveys, as well as contemporary sources like lidar point clouds and digital elevation models (DEMs). These shorelines are compiled and analyzed in the Digital Shoreline Analysis System (DSAS) software to compute rates of change. It is useful to keep a record of historical shoreline positions as a method of monitoring change over time to identify areas ...

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2018 Mississippi and Alabama USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 Puerto Rico USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2018 South Texas USGS Lidar-Derived Dune Crest, Toe and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline derived from the 2018 United States ...

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2018 USGS Florida Panhandle Post-Michael Lidar-derived Dune Crest, Toe, and Shoreline

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2018 United States Army ...

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2019-333-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2019-333-FA Offshore of the Rockaway Peninsula, New York, September–October 2019

From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a point dataset of field activity number (FAN) 2019-333-FA chirp subbottom profile 1,000-shot-interval locations.

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2019-333-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2019-333-FA Offshore of the Rockaway Peninsula, New York, September–October 2019

From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a point dataset of field activity number (FAN) 2019-333-FA chirp subbottom profile start of trackline locations.

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2019-333-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2019-333-FA Offshore of the Rockaway Peninsula, New York, September–October 2019

From September 27 through October 5, 2019, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of the Rockaway Peninsula, New York. This shapefile represents a line dataset of field activity number (FAN) 2019-333-FA chirp tracklines.

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2019 North Carolina and Virginia Post-Dorian USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2019 North Carolina and Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (L=lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2020 New Jersey and New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2020 New Jersey USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

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2021-322-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2021-322-FA Offshore of Pensacola Beach, Florida, June 2021

From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a point dataset of field activity number (FAN) 2021-322-FA chirp subbottom profile 1,000-shot-interval locations collected inshore and offshore of Pensacola Beach, FL.

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2021-322-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2021-322-FA Offshore of Pensacola Beach, Florida, June 2021

From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a point dataset of field activity number (FAN) 2021-322-FA chirp subbottom profile start of trackline locations collected inshore and offshore of Pensacola Beach, FL.

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2021-322-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2021-322-FA Offshore of Pensacola Beach, Florida, June 2021

From June 2 through 9, 2021, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and determine Holocene stratigraphy near Santa Rosa Island, Florida (FL). This shapefile represents a line dataset of field activity number (FAN) 2021-322-FA chirp tracklines collected inshore and offshore of Pensacola Beach, FL.

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2021 New York State Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

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2022-309-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile 1,000-shot-interval locations.

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2022-309-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a point dataset of field activity number (FAN) 2022-309-FA chirp subbottom profile start of trackline locations.

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2022-309-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-309-FA Offshore of Seven Mile Island, New Jersey, April and May 2022

From April 29 through May 2, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Seven Mile Island, New Jersey. Geophysical data were collected as part of the Coastal Sediment Availability and Flux project. This shapefile represents a line dataset of field activity number (FAN) 2022-309-FA chirp tracklines.

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2022-312-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, November 2022

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile 1,000-shot-interval locations.

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2022-312-FA _sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, June 2022

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-312-FA chirp subbottom profile start of trackline locations.

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2022-312-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-312-FA Near Panama City, Florida, November 2022

From June 20-30, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport near Panama City, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-312-FA chirp tracklines.

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2022-328-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile 1,000-shot-interval locations.

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2022-328-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a point dataset of field activity number (FAN) 2022-328-FA chirp subbottom profile start of trackline locations.

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2022-328-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-328-FA Offshore of Breton Island, Louisiana, August 2022

On August 5, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Breton Island, Louisiana (LA). Geophysical data were collected as part of the Breton Island Post Construction Monitoring project. This shapefile represents a line dataset of field activity number (FAN) 2022-328-FA chirp tracklines.

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2022-334-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile 1,000-shot-interval ...

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2022-334-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2022-334-FA chirp subbottom profile start of trackline ...

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2022-334-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2022-334-FA Offshore of Boca Chica Key, Florida, November 2022

From November 8-13, 2022, the U.S. Geological Survey (USGS) conducted geophysical surveys to investigate the geologic controls on barrier island evolution and sediment transport offshore of Boca Chica Key, Florida (FL). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2022-334-FA chirp tracklines.

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2022 New Jersey and New York USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

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2023-310-FA_shots: Digital Chirp Subbottom Profile Shotpoint Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023

From May 7-13, 2023, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a point dataset of field activity number (FAN) 2023-310-FA chirp subbottom ...

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2023-310-FA_sol: Digital Chirp Subbottom Profile Start of Line Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023

From May 7-13, 2022, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced ...

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2023-310-FA_trkln: Digital Chirp Subbottom Profile Trackline Data Collected During USGS Field Activity Number 2023-310-FA Offshore of Kailua, Hawaii, May 2023

From May 7-13, 2022, the U.S. Geological Survey (USGS) conducted a geologic assessment, including bathymetric mapping, near Kailua, Hawaii in support of efforts to construct an artificial coral reef offshore of Marine Corps Base Hawaii (MCBH). Geophysical data were collected as part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects. This shapefile represents a line dataset of field activity number (FAN) 2023-310-FA chirp tracklines.

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95th percentile of wave-current bottom shear stress in the Middle Atlantic Bight for May, 2010 - May, 2011 (MAB_95th_perc.SHP)

The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ...

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Acidification and Increasing CO2 Flux Associated with Five, Springs Coast, Florida Springs (1991-2014)

Scientists from the South West Florida Management District (SWFWMD) acquired and analyzed over 20 years of seasonally-sampled hydrochemical data from five first-order-magnitude (springs that discharge 2.83 m3 s-1 or more) coastal springs located in west-central Florida. These data were subsequently obtained by the U.S. Geological Survey (USGS) for further analyses and interpretation. The spring study sites (Chassahowitzka, Homosassa, Kings Bay, Rainbow, and Weeki Wachee), which are fed by the Floridan ...

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Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

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Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

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Aerial Imagery of the North Carolina Coast: 2019-10-11

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

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Aerial Imagery of the North Carolina Coast: 2019-11-26

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

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Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

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Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

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Aerial_Shorelines_1940_2015.shp - Dauphin Island, Alabama Shoreline Data Derived from Aerial Imagery from 1940 to 2015

Aerial_WDL_Shorelines.zip features digitized historic shorelines for the Dauphin Island coastline from October 1940 to November 2015. This dataset contains 10 Wet Dry Line (WDL) shorelines separated into 58 shoreline segments alongshore Dauphin Island, AL. The individual sections are divided according to location along the island and shoreline type: open-ocean, back-barrier, marsh shoreline. Imagery of Dauphin Island, Alabama was acquired from several sources including the United States Geological Survey ...

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A GIS compilation of vector shorelines for the Virginia coastal region from the 1840s to 2010s

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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ALASKA1964_INUNDATION - Alaska 1964 Estimated Tsunami Inundation Line at Seaside, Oregon

This data set is a polyline shapefile representing the tsunami inundation line for the Alaska 1964 event based on observations and associated information obtained by Tom Horning (1997). The polyline was digitized from a line drawn by Tom Horning on an orthophoto taken in 1997.

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ALASKA1964_OBS - Alaska 1964 Tsunami Observations at Seaside, Oregon

This data set is a point shapefile representing observations of inundation and water levels from the Alaska 1964 event obtained by Tom Horning (1997). The geospatial dataset were derived from a spreadsheet provided by Bruce Jaffe.

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ALASKA1964_RUNUP - Alaska 1964 Tsunami Runup Heights at Seaside, Oregon (alaska1964_runup.shp)

This data set is a point shapefile representing tsunami inundation runup heights for the Alaska 1964 event based on observations and associated information obtained by Tom Horning (1997). The geospatial data was digitized from a points drawn by Tom Horning on an orthophoto taken in 1997.

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AllScenarios_Bin1thru18_SSC: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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AllScenarios_Initial_and_Final_Bed_Elevations: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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AllScenarios_Sediment_Fluxes: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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AllScenarios_Spatial_Flow: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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AllScenarios_Spatial_Waves: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output

The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ...

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Archive of Chirp Subbottom Profile Data Collected in 2015 from the Northern Chandeleur Islands, Louisiana

From September 14 to 28, 2015, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales ...

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Archive of Chirp Subbottom Profile Data Collected in 2016 from the Northern Chandeleur Islands, Louisiana

From June 10 to 19, 2016, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months to ...

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Archive of Chirp Subbottom Profile Data Collected in 2017 from the Louisiana Chenier Plain

June 2–10 and July 2, 2017, the U.S. Geological Survey (USGS) conducted geophysical surveys offshore of the Louisiana Chenier Plain to document the changing morphology of the coastal environment. Data were collected under the Barrier Island Coastal Monitoring (BICM) program, an ongoing collaboration between the State of Louisiana Coastal Protection and Restoration Authority (CPRA), the University of New Orleans (UNO) Pontchartrain Institute for Environmental Sciences (PIES), and the USGS. Project ...

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Archive of Chirp Subbottom Profile Data Collected in 2017 From the Northern Chandeleur Islands, Louisiana

From August 7 to 16, 2017, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months ...

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Archive of Chirp Subbottom Profile Data Collected in 2018 from the Northern Chandeleur Islands, Louisiana

From August 16 to 21, 2018, the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate the geologic controls on barrier island evolution and medium-term and interannual sediment transport along the sand berm constructed in 2011 (offshore, at the northern end of the Chandeleur Islands, Louisiana) as mitigation of the Deepwater Horizon oil spill. This investigation is part of a broader USGS project, which seeks to better understand barrier island evolution over medium time scales (months ...

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Archive of Chirp Subbottom Profile Data Collected in 2019 from Cedar Island, Virginia

From August 9 to 14, 2019, researchers from the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate shoreface morphology and geology near Cedar Island, Virginia. The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. This publication serves as an archive of high-resolution ...

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Archive of Chirp Subbottom Profile Data Collected in June 2018 From Fire Island, New York

Researchers from the U.S. Geological Survey (USGS) conducted a long-term, coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal System Change project (https://coastal.er.usgs.gov/fire-island/) objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. From ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2015 Offshore of Dauphin Island, Alabama

From September 16 through 23, 2015, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Dauphin Island, Alabama (AL). The Alabama Barrier Island Restoration Feasibility Study project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation files, geographic ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2019 from Rockaway Peninsula, New York

From September 27 through October 5, 2019, researchers from the U.S. Geological Survey (USGS) conducted a geophysical survey to investigate shoreface morphology and geology near the Rockaway Peninsula, New York. The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. This publication serves as an ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2021 Near Pensacola Beach, Florida

From June 2 through 9, 2021, researchers from the U.S. Geological Survey (USGS) conducted an inshore and offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Pensacola Beach, Florida (FL). The Coastal Resource Evaluation for Management Applications (CREMA) project objective includes the investigation of nearshore geologic controls on surface morphology. This publication serves as an archive of high-resolution chirp subbottom trace data, survey trackline map, navigation ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 from Boca Chica Key, Florida

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey at the nearshore ledge offshore of Boca Chica Key, Florida (FL) November 8-13, 2022. The objective of the project was to collect bathymetric maps and conduct a geologic assessment of the nearshore ledge off Boca Chica Key in support ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 from Seven Mile Island, New Jersey

From April 29 through May 2, 2022, researchers from the U.S. Geological Survey (USGS) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Seven Mile Island, New Jersey (NJ). The Coastal Sediment Availability and Flux project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in 2022 Offshore of Breton Island, Louisiana

On August 5, 2022, researchers from the U.S. Geological Survey (USGS) conducted an offshore geophysical survey to map the shoreface and determine Holocene stratigraphy near Breton Island, Louisiana (LA). The Breton Island Post Construction Monitoring project objective includes the investigation of nearshore geologic controls on surface morphology in addition to mapping the seafloor to evaluate coastal change. This publication (Forde and others, 2023) serves as an archive of high-resolution chirp subbottom ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in June 2022 Near Panama City, Florida

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map back-barrier and lagoonal areas, as well as characterizing stratigraphy near Panama City, Florida (FL) in June 2022. The purpose of this study was to conduct a geologic assessment (including bathymetric mapping) of the environs ...

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Archive of Chirp Subbottom Profile, Imagery, and Geospatial Data Collected in May 2023 from Oahu, Hawaii

As part of the Coastal Sediment Availability and Flux and Defense Advanced Research Protection Agency (DARPA) Reefense projects, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted a nearshore geophysical survey to map the shoreface and inner shelf, as well as characterizing stratigraphy near Oahu, Hawaii (HI) May 7-13, 2023. The purpose of this study was to conduct a geologic assessment (including bathymetric mapping) near Fort Hase Beach, ...

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Archive of Digitized Analog Boomer and Minisparker Seismic Reflection Data Collected from the Northern Gulf of Mexico: 1981, 1990 and 1991

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (https:/ ...

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Archive of digitized analog boomer seismic reflection data collected along the Louisiana Shelf, 1982–1984

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (https:/ ...

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Archive of digitized analog boomer seismic reflection data collected during U.S. Geological S cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the ...

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Archive of digitized analog boomer seismic reflection data collected during U.S. Geological Survey cruise Acadiana 87-2 in the northern Gulf of Mexico, June 1987

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the ...

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Archive of Digitized Analog Boomer Seismic-Reflection Data Collected During U.S. Geological Survey Cruises Erda 92-2 and Erda 92-4 in Mississippi Sound, June and August 1992

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP) (https:/ ...

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Archive of digitized analog boomer seismic reflection data collected during USGS Cruise Kit Jones 92-1 along the Florida Shelf, July 1992

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP; https:/ ...

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Archive of digitized analog boomer seismic reflection data collected during USGS Cruise USFHC in Mississippi Sound and Bay St. Louis, September 1989

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP, https:/ ...

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Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: 1982, 1985, 1986, 1989, 1991, and 1992

The U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program (CMHRP) has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program ...

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Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: Intersea 1980

The U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program (CMHRP) has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters (m) long. As part of the National Geological and Geophysical Data Preservation ...

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Archive of Ground Penetrating Radar and Differential Global Positioning System Data Collected in April 2016 from Fire Island, New York

Researchers from the U.S. Geological Survey (USGS) conducted a long-term, coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal Change project (https://coastal.er.usgs.gov/fire-island/) objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. In April ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Initial_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Initial_Elevations_N.txt)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_114_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_114_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_134_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_134_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_152_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_152_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_155_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_155_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_158_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_158_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_186_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_186_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_191_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_191_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_23_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_23_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_257_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_257_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_4_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_4_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_71_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_71_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_95_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Storm_95_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Year_30_Elevations_N)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Info
Assessing the Effectiveness of Nourishment in Decadal Barrier Island Morphological Resilience: Model Inputs and Outputs (Year_30_Elevations_NA)

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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Atlantic and Gulf coast sandy coastline topo-bathy profile and characteristic database

Seamless topographic-bathymetric (topo-bathy) profiles and their derived morphologic characteristics were developed for sandy coastlines along the Atlantic and Gulf coasts of the United States. As such, the rocky coasts of Maine, the coral reefs in southern Florida and the Keys, and the marsh coasts in the Mississippi Delta and the Florida Big Bend region and are not included in this dataset. Topographic light detection and ranging (lidar) data (dune crest, dune toe, and shorelines) from Doran and others ...

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ATLANTIC - Coastal Vulnerability to Sea-Level Rise: A Preliminary Database for the U.S. Atlantic Coast

The goal of this project is to provide a preliminary overview, at a National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of ...

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Attendee Survey Results from the April and May 2020 Gulf Islands National Seashore Workshop

In early 2020, scientists gathered to advance sediment budget modeling efforts by conducting a “Needs Assessment Workshop” for the Gulf Island National Seashore (GINS) to understand the coastal processes affecting island resiliency. The “Gulf Islands Sediment Budget Needs Assessment Workshop” was held, virtually, April 23–24 and May 27–28, 2020. The workshop series was organized by researchers from North Carolina State University in collaboration with National Park Service (NPS) and U.S. ...

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Autonomous Flow-Thru (AFT) CO2 data of the West Florida Shelf: USGS Cruise 11BHM01

The United States Geological Survey (USGS) is conducting a study on the effects of climate change on ocean acidification within the Gulf of Mexico; dealing specifically with the effect of ocean acidification on marine organisms and habitats. To investigate this, the USGS participated in cruises in the West Florida Shelf and northern Gulf of Mexico regions aboard the R/V Weatherbird II, a ship of opportunity lead by Dr. Kendra Daly, of the University of South Florida (USF). This cruise occurred May 03 - 09, ...

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Autonomous Flow-Thru (AFT) CO2 data of the West Florida Shelf: USGS Cruise 11BHM02

The United States Geological Survey (USGS) is conducting a study on the effects of climate change on ocean acidification within the Gulf of Mexico; dealing specifically with the effect of ocean acidification on marine organisms and habitats. To investigate this, the USGS participated in cruises in the West Florida Shelf and northern Gulf of Mexico regions aboard the R/V Weatherbird II, a ship of opportunity lead by Dr. Kendra Daly, of the University of South Florida (USF). This cruise occurred June 25 - 30, ...

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Autonomous Flow-Thru (AFT) pH data of the West Florida Shelf: USGS Cruise 11BHM01

The United States Geological Survey (USGS) is conducting a study on the effects of climate change on ocean acidification within the Gulf of Mexico; dealing specifically with the effect of ocean acidification on marine organisms and habitats. To investigate this, the USGS participated in cruises in the West Florida Shelf and northern Gulf of Mexico regions aboard the R/V Weatherbird II, a ship of opportunity lead by Dr. Kendra Daly, of the University of South Florida (USF). This cruise occurred May 03 - 09, ...

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Autonomous Flow-Thru (AFT) pH data of the West Florida Shelf: USGS Cruise 11BHM02

The United States Geological Survey (USGS) is conducting a study on the effects of climate change on ocean acidification within the Gulf of Mexico; dealing specifically with the effect of ocean acidification on marine organisms and habitats. To investigate this, the USGS participated in cruises in the West Florida Shelf and northern Gulf of Mexico regions aboard the R/V Weatherbird II, a ship of opportunity lead by Dr. Kendra Daly, of the University of South Florida (USF). This cruise occurred June 25 - 30, ...

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Autonomous Flow-Thru (AFT) pH data of the West Florida Shelf: USGS Cruise 11BHM04

The United States Geological Survey (USGS) is conducting a study on the effects of climate change on ocean acidification within the Gulf of Mexico; dealing specifically with the effect of ocean acidification on marine organisms and habitats. To investigate this, the USGS participated in two cruises in the West Florida Shelf and northern Gulf of Mexico regions aboard the R/V Weatherbird II, a ship of opportunity lead by Dr. Kendra Daly, of the University of South Florida (USF). The cruises occurred September ...

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Barrier island geomorphology and seabeach amaranth metrics at 50-m alongshore transects, and 5-m cross-shore points for 2008 — Assateague Island, MD and VA.

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as piping plover ...

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Baseline_BackBarrier.shp - Baseline Along the Back-Barrier (North-Facing) Coast of Dauphin Island, Alabama, Generated to Calculate Shoreline Change Rates.

Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ...

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Baseline coastal oblique aerial photographs collected at Breton Island and the Chandeleur Islands, Louisiana, January 22, 2011

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On January 22, 2011, the USGS conducted an oblique aerial photographic survey at Breton Island and the Chandeleur Islands, LA, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the beach and ...

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Baseline coastal oblique aerial photographs collected at the Chandeleur Islands, Louisiana, and Dauphin Island, Alabama, July 24, 2010

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 24, 2010, the USGS conducted an oblique aerial photographic survey at the Chandeleur Islands, Louisiana, and Dauphin Island, Alabama, aboard a Beechcraft BE90 King Air aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

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Baseline coastal oblique aerial photographs collected from Breton Island to the Chandeleur Islands, Louisiana, September 3, 2010

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 3, 2010, the USGS conducted an oblique aerial photographic survey from Breton Island to the Chandeleur Islands, Louisiana, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ...

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Baseline coastal oblique aerial photographs collected from Dauphin Island, Alabama, to Breton Island, Louisiana, July 26–27, 2007

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 26-27, 2007, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

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Baseline coastal oblique aerial photographs collected from Dauphin Island, Alabama, to Breton Island, Louisiana, September 26–27, 2006

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 26-27, 2006, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

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Baseline coastal oblique aerial photographs collected from Dog Island, Florida, to Breton Island, Louisiana, June 24–25, 2008

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 24–25, 2008, the USGS conducted an oblique aerial photographic survey from Dog Island, Florida, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental ...

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Baseline coastal oblique aerial photographs collected from False Cape State Park, Virginia, to Myrtle Beach, South Carolina, May 6, 2008

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 6, 2008, the USGS conducted an oblique aerial photographic survey from False Cape State Park, Virginia, to Myrtle Beach, South Carolina, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission (08CH01) was conducted to collect data ...

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Baseline coastal oblique aerial photographs collected from Fenwick Island State Park, Delaware, to Corolla, North Carolina, March 27, 1998

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On March 27, 1998, the USGS conducted an oblique aerial photographic survey from Fenwick Island State Park, Delaware, to Corolla, North Carolina, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. This mission was conducted to collect data for assessing ...

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Baseline Coastal oblique aerial photographs collected from Horseshoe Beach, Florida, to East Cape, Florida, May 19-20, 2010

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 19-20, 2010, the USGS conducted an oblique aerial photographic survey from Horseshoe Beach, Florida, to East Cape, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes ...

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Baseline coastal oblique aerial photographs collected from Navarre Beach, Florida, to Breton Island, Louisiana, September 7, 2016

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 7, 2016, the USGS conducted an oblique aerial photographic survey from Navarre Beach, Florida, to Breton Island, Louisiana, aboard a Maule MT57 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ...

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Baseline coastal oblique aerial photographs collected from Navarre, Florida, to the Chandeleur Islands, Louisiana, and from Grand Point, Alabama, to St. Joseph Point, Mississippi, June 6, 2006

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 6, 2006, the USGS conducted an oblique aerial photographic survey from Navarre, Florida, to the Chandeleur Islands, Louisiana, and from Grand Point, Alabama, to St. Joseph Point, Mississippi, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore ...

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Baseline coastal oblique aerial photographs collected from Ponte Vedra, Florida, to the South Carolina/North Carolina border, August 24, 2011

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On August 24, 2011, the USGS conducted an oblique aerial photographic survey from Ponte Vedra, Florida, to the South Carolina/North Carolina border, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

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Baseline coastal oblique aerial photographs collected from Tampa Bay to the Marquesas Keys, Florida, June 22–23, 2010

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 22–23, 2010, the USGS conducted an oblique aerial photographic survey from Tampa Bay to the Marquesas Keys, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in ...

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Baseline coastal oblique aerial photographs collected from the Harney River, Everglades National Park, Florida to Anclote Key, Florida, November 14, 2006

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On November 14, 2006, the USGS conducted an oblique aerial photographic survey from the Harney River, Everglades National Park, Florida to Anclote Key, Florida, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect ...

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Baseline coastal oblique aerial photographs collected U.S. Army Corps of Engineers Field Research Facility, Duck, North Carolina, June 9, 2017

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 09, 2017, the USGS conducted an oblique aerial photographic survey of the U.S. Army Corps of Engineers Field Research Facility (USACE FRF), located in Duck, North Carolina, aboard a Cessna 182 aircraft at an altitude of approximately 1000 feet (ft). This mission was conducted to collect data for USACE FRF ...

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Baseline for Buzzards Bay coastal region generated to calculate shoreline change rates from Nobska Point in Woods Hole to Westport at the Massachusetts-Rhode Island border (BuzzardsBay_baseline.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

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Baseline for Elizabeth Islands coastal region generated to calculate shoreline change rates from Nonamesset Island southwest of Woods Hole to Cuttyhunk Island north of Martha's Vineyard (ElizabethIslands_baseline.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

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Baseline for the backshore of Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Buzzards Bay coastal region in Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Cape Cod Bay coastal region in Massachusetts, generated to calculate shoreline change rates (without the proxy-datum bias) using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Cape Cod Bay coastal region in Massachusetts, generated to calculate shoreline change rates (with the proxy-datum bias) using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the coastal region north of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baseline for the coastal region of Buzzards Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baseline for the coastal region south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baseline for the coast of Puerto Rico's main island generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 (ver. 2.0, March 2023)

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States' coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

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Baseline for the coast south of Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the east facing coast of Cape Cod, Massachusetts, from Monomoy to Provincetown, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Elizabeth Islands, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baseline for the Florida east coast (FLec) coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Baseline for the Florida panhandle (FLph) coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Baseline for the Florida west coast (FLwc) coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Baseline for the Georgia coastal region generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Baseline for the islands of Vieques and Culebra, Puerto Rico, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the USGS Digital Shoreline Analysis System (DSAS), version 5.1 software to calculate rates of change. Keeping a record of historical shoreline positions is an effective method to monitor change over time, enabling ...

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Baseline for the North Carolina coastal region from Cape Fear to the South Carolina border (NCwest)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the North Carolina coastal region from Cape Hatteras to Cape Lookout (NCcentral)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the North Carolina coastal region from Cape Lookout to Cape Fear (NCsouth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the North Carolina coastal region from the Virginia border to Cape Hatteras (NCnorth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the northern coast of Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the northern coast of Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the region of Cape Cod Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baseline for the South Cape Cod coastal region generated to calculate shoreline change rates from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_baseline.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

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Baseline for the South Carolina coastal region, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline for the southern coast Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the southern coast of Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the southern coast of Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baseline for the southern coast of Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.0

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-9 color ...

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Baseline for the Virginia coastal region, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Baseline_OpenOcean.shp - Baseline Along the Open-Ocean (South-Facing) Coast of Dauphin Island, Alabama, Generated to Calculate Shoreline Change Rates.

Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ...

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Baselines for the coast of Martha's Vineyard, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baselines for the coast of Nantucket, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Baselines for the Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline ...

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Bathymetric change analyses of the Sacramento River near Rio Vista, California, and the junction of Cache and Steamboat sloughs, from 1992 to 2004

Bathymetric change grids covering the periods of time from 1992 to 1998 and from 1994 to 2004 are presented. The grids cover a portion of the Sacramento River near Rio Vista, California, extending partially upstream on Cache and Steamboat sloughs by the Ryer Island Ferry, as well as continuing up the Sacramento River towards Isleton. Positive grid values indicate accretion, or a shallowing of the surface bathymetric surface, and negative grid values indicate erosion, or a deepening of the bathymetric ...

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Bathymetric change analyses of the southernmost portion of the Mokelumne River, California, from 1934 to 2018

Bathymetric change grids covering the periods of time from 1934 to 2011, from 2011 to 2018, and from 1934 to 2018 are presented. The grids cover a portion of the Mokelumne River, California, starting at its terminus at the San Joaquin River and moving upriver to the confluences of the north and south branches of the Mokelumne. Positive grid values indicate accretion, or a shallowing of the surface bathymetric surface, and negative grid values indicate erosion, or a deepening of the bathymetric surface. ...

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Bathymetric change map of the nearshore around Ship, Horn, and Petit Bois islands, Mississippi: 1916-1920 to 2008-2009

To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Data sets include 1916 through 1920 soundings collected by the United States Coast and ...

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Bathymetric change map of the nearshore around Ship, Horn, and Petit Bois islands, Mississippi: 1916-1920 to 2016

To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Datasets include 1916 through 1920 soundings collected by the United States Coast and ...

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Bathymetric change map of the nearshore around Ship, Horn, and Petit Bois islands, Mississippi: 2008-2009 to 2016

To characterize coastal change, historical maps and complementary records were compiled including: topographic sheets (T-sheets), hydrographic sheets (H-sheets, smooth sheets), shorelines, and bathymetric soundings surrounding the Mississippi (MS) barrier islands over several time periods (1916-1920, 2008-2009 and 2016). One goal of this work was to create a time-series of bathymetric change maps around the islands. Data sets include 1916 through 1920 soundings collected by the United States Coast and ...

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Bathymetric change of Central San Francisco Bay, California: 1971 to 2020

This 25-m-resolution surface presents bathymetric change of Central San Francisco Bay, California (hereafter referred to as Central Bay). This surface compares a 1-m-resolution digital elevation model (DEM) of the central portion of San Francisco Bay (Fregoso and others, 2021), comprised of bathymetry data in the Central Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution DEM of Central Bay comprised of historic surveys from ...

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Bathymetric change of San Pablo Bay, California: 1983 to 2015

This 25-m-resolution surface presents bathymetric change of San Pablo Bay, California, from 1983 to 2015. This surface compares a 1-m-resolution digital elevation model (DEM) of the northern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the San Pablo Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution bathymetric DEM of San Pablo Bay comprised of historic surveys from 1983 to 1986 ...

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Bathymetric change of South San Francisco Bay, California: 1979 to 2020

This 50-m-resolution surface presents bathymetric change of South San Francisco Bay, California (hereafter referred to as South Bay). This surface compares a 1-m-resolution digital elevation model (DEM) of the southern portion of San Francisco Bay (Fregoso and others, 2021), comprised of bathymetry data in the South Bay region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 50-m-resolution DEM of South Bay comprised of historic surveys from 1979 to ...

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Bathymetric change of Suisun Bay, California: 1988 to 2016

This 25-m-resolution surface presents bathymetric change of Suisun Bay, California, from 1988 to 2016. This surface compares a 1-m-resolution digital elevation model (DEM) of the northern portion of San Francisco Bay (Fregoso and others, 2020), comprised of bathymetry data in the Suisun region from the time period referred to as the 2010s because the majority of the surveys were in that decade, to a 25-m-resolution bathymetric DEM of Suisun Bay comprised of historic surveys from 1988 to 1990 (referred to as ...

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Bathymetric Grid for a Wave Exposure Model of Grand Bay, Mississippi

Coastal marshes are highly dynamic and ecologically important ecosystems that are subject to pervasive and often harmful disturbances, including shoreline erosion. Shoreline erosion can result in an overall loss of coastal marsh, particularly in estuaries with moderate- or high-wave energy. Not only can waves be important physical drivers of shoreline change they can also influence shore-proximal vertical accretion through sediment delivery. For these reasons, estimates of wave energy can provide a ...

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Beach profile data collected in 2010 and 2011 in the vicinity of Arey Lagoon and Barter Island, Alaska

Beach elevation profiles were measured along 29 shore-normal transects on and around Arey and Barter Islands, Alaska in August 2010 and July 2011. Profile data are available in a single comma-delimited file and a zip file including multiple .jpg images that show a visual representation of the individual profiles.

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Beach Topography—Fire Island, New York, Pre-Hurricane Sandy, January 2012: Ground Based Lidar (1-Meter Digital Elevation Model)

The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) and the U.S. Army Corps of Engineers Field Research Facility (USACE-FRF) of Duck, North Carolina collaborated to gather alongshore ground-based lidar beach topography at Fire Island, New York. This high-resolution, elevation dataset was collected on January 30, 2012, and was funded by SPCMSC. The USGS data release containing the aforementioned dataset includes the resulting, processed elevation point data (XYZ) and ...

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Beach Topography—Fire Island, New York, Pre-Hurricane Sandy, January 2012: Ground Based Lidar (ASCII XYZ Point Data)

The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) and the U.S. Army Corps of Engineers Field Research Facility (USACE-FRF) of Duck, North Carolina collaborated to gather alongshore ground-based lidar beach topography at Fire Island, New York. This high-resolution, elevation dataset was collected on January 30, 2012, and was funded by SPCMSC. The USGS data release containing the aforementioned dataset includes the resulting, processed elevation point data (XYZ) and an ...

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BEWARE database: A Bayesian-based system to assess wave-driven flooding hazards on coral reef-lined coasts

A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE improves system understanding of reef hydrodynamics by examining the intrinsic reef and extrinsic forcing factors controlling runup and flooding on ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the central coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the northern coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the western coast of North Carolina from Cape Fear to the South Carolina border (NCwest)

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ...

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Bias Feature for the Florida east coast (FLec) coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Bias Feature for the Florida panhandle (FLph) coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Bias Feature for the Florida west coast (FLwc) coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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Bias Feature for the Georgia coastal region containing proxy-datum bias information to be used in the Digital Shoreline Analysis System version 5

During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion ...

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BocaChica_2022_MBES: High-resolution Geophysical and Imagery Data Collected in November 2022 Offshore of Boca Chica Key, FL

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Boca Chica Key, the Florida Keys, from November 8-13, 2022. This dataset, BocaChica_2022_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid, and the dataset BocaChica_2022_MBES_Backscatter.zip ...

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Cape Canaveral, Florida, backscatter data collected in 2016 by Coastal Carolina University: Processed GeoTIFF Image

A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data.

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Cape Canaveral, Florida, multibeam bathymetry collected in 2016 by Coastal Carolina University: Processed elevation point data (XYZ)

A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data.

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Cape Canaveral, Florida, multibeam bathymetry collected in 2016 by Coastal Carolina University: Processed GeoTIFF Image

A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data.

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Cape Canaveral, Florida, seismic chirp collected in 2016 by Coastal Carolina University

A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data.

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Cape Canaveral, Florida side scan sonar data collected in 2016 by Coastal Carolina University: Processed GeoTIFF Image

A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data.

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Cape Canaveral tracklines of geophysical data collected in 2016 by Coastal Carolina University

A geophysical survey was conducted offshore Cape Canaveral, Florida by Coastal Carolina University offshore of Cape Canaveral, Florida using high-resolution chirp sub-bottom, multibeam bathymetry and side scan sonar (SSS) systems on June 13, 14, 16, and 17 of 2016. This USGS data release includes the resulting processed elevation point data (xyz), an interpolated digital elevation model (DEM), with processed backscatter, side scan sonar, and seismic chirp data.

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CatIsland_2010_Bathy_NAVD88_grid.tif

In September and October of 2010, the U.S. Geological Survey (USGS), in cooperation with the Army Corps of Engineers (USACE), conducted geophysical surveys around Cat Island, Miss. to collect bathymetry, acoustical backscatter, and seismic reflection data (seismic-reflection data have been published separately, Forde and others, 2012). The geophysical data along with sediment vibracore data (yet to be published) will be integrated to analyze and produce a report describing the geomorphology and geologic ...

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CatIsland_2010_Bathy_Swath_tracklines

In September and October of 2010, the U.S. Geological Survey (USGS), in cooperation with the Army Corps of Engineers (USACE), conducted geophysical surveys around Cat Island, Miss. to collect bathymetry, acoustical backscatter, and seismic reflection data (seismic-reflection data have been published separately, Forde and others, 2012). The geophysical data along with sediment vibracore data (yet to be published) will be integrated to analyze and produce a report describing the geomorphology and geologic ...

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CatIsland 2010 single-beam bathymetry tracklines

In September and October of 2010, the U.S. Geological Survey (USGS), in cooperation with the Army Corps of Engineers (USACE), conducted geophysical surveys around Cat Island, Miss. to collect bathymetry, acoustical backscatter, and seismic reflection data (seismic-reflection data have been published separately, Forde and others, 2012). The geophysical data along with sediment vibracore data (yet to be published) will be integrated to analyze and produce a report describing the geomorphology and geologic ...

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CENCAL1853_1910 - Vectorized Shoreline of Central California Derived from 1853-1910 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

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CENCAL1929_1942 - Vectorized Shoreline of Central Califonia Derived from 1929-1942 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

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CENCAL1945_1976 - Vectorized Shoreline of Central California Derived from 1945-1976 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

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CENCAL_1998_2002 - Vectorized Shoreline of Central California Derived from 1998-2002 Lidar Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

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CENCAL_BASELINE - Offshore Baseline for Central California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

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CENCAL_BIASVALUES - Central California Shoreline Bias Values

The USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. These shorelines were used to calculate long-term and short-term change rates in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS ...

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CENCAL_INTERSECTS_LT - Long-Term Transect-Shoreline Intersection Points for Central California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

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CENCAL_INTERSECTS_ST - Short-Term Transect-Shoreline Intersection Points for Central California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

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CENCAL_TRANSECTS_LT - Long-Term Shoreline Change Rates for Central California Generated at a 50 m Transect Spacing, 1853-2002

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

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CENCAL_TRANSECTS_ST - Short-Term Shoreline Change Rates for Central California Generated at a 50m Transect Spacing, 1971-1998

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

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CentralBeaufort_shorelines.shp - Shorelines for the northern Alaska coastal region used in shoreline change analysis, 1947 to 2007

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

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Central California CoSMoS v3.1 projections of coastal cliff retreat due to 21st century sea-level rise

This dataset contains spatial projections of coastal cliff retreat (and associated uncertainty) for future scenarios of sea-level rise (SLR) in Central California. Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical models and field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS). Read metadata and references ...

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Central California CoSMoS v3.1 projections of shoreline change due to 21st century sea-level rise

This dataset contains projections of shoreline positions and uncertainty bands for future scenarios of sea-level rise. Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model forced with global-to-local nested wave models and assimilated with lidar-derived shoreline vectors. Read metadata carefully. Details: Projections of shoreline position in the Central Coast of California are made for scenarios of 25, 50, 75, 92, 100 ...

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Change in salinity exposure of salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy

As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ...

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Change in salinity in salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy

As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ...

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Change in suspended sediment concentration over the salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy

As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ...

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Characterization of seafloor photographs near the mouth of the Elwha River during the first two years of dam removal (2011-2013)

We characterized seafloor sediment conditions near the mouth of the Elwha River from underwater photographs taken every four hours from September 2011 to December 2013. A digital camera was affixed to a tripod that was deployed in approximately 10 meters of water. Each photograph was qualitatively characterized as one of six categories: (1) base, or no sediment; (2) low sediment; (3) medium sediment; (4) high sediment; (5) turbid; or (6) kelp. For base conditions, no sediment was present on the seafloor. ...

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Climatological wave height, wave period and wave power along coastal areas of the East Coast of the United States and Gulf of Mexico

This U.S. Geological Survey data release provides data on spatial variations in climatological wave parameters (significant wave height, peak wave period, and wave power) for coastal areas along the United States East Coast and Gulf of Mexico. Significant wave height is the average wave height, from crest to trough, of the highest one-third of the waves in a specific time period. Peak wave period is the wave period associated with the most energetic waves in the wave spectrum in a specific time period. Wave ...

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Coastal bathymetry data collected between 2008 and 2009 offshore of the Mississippi and Alabama barrier islands: Processed elevation point data

During the summers of 2008 and 2009 the United States Geological Survey (USGS) conducted bathymetric surveys from West Ship Island, Mississippi, to Dauphin Island, Alabama, as part of the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility project. The survey area extended from the shoreline out to approximately two kilometers and included the adjacent passes. These findings were originally published in Dewitt and others (2012). This USGS data release includes updated elevation point ...

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Coastal Bathymetry Data Collected in June 2018 from Fire Island, New York: Wilderness Breach and Shoreface

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, June 2?17, 2018. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach and the adjacent shoreface environment. During this study, bathymetry data were collected aboard two personal watercraft (PWC) outfitted with single-beam echosounders, as well ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Fabric Dataset

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Hazard Impact Type

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Maximum Change Likelihood

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Perpetual Hazards

Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the ...

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Coastal Multibeam Bathymetry and Backscatter Data Collected in June 2021 from Rockaway Peninsula, New York

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), June 18-25, 2021. This dataset, Rockaway_2021_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid and the dataset Rockaway_2021_MBES ...

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Coastal Multibeam Bathymetry and Backscatter Data Collected in May 2021 From Seven Mile Island, New Jersey

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore extent of Seven Mile Island, New Jersey, from May 19-23, 2021. The download file, 7Mile_2021_MBES_xyz.zip, includes processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. The download file, 7Mile_2021_MBES ...

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Coastal Multibeam Bathymetry and Backscatter Data Collected in May 2023 from Rockaway Peninsula, New York

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), from May 6-16, 2023. This dataset, Rockaway_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid and the dataset Rockaway_2023_MBES ...

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Coastal Multibeam Bathymetry and Backscatter Data Collected in May 2023 From Seven Mile Island, New Jersey

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore extent of Seven Mile Island, New Jersey (NJ), from May 18-27, 2023. The download file, 7Mile_2023_MBES_xyz.zip, includes processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. The download file, 7Mile_2023_MBES ...

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Coastal Multibeam Bathymetry and Backscatter Data Collected in October 2019 from Rockaway Peninsula, New York: Leg 1

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), from October 4-6, 2019. This dataset, Rockaway_2019_MBES_Leg1_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid from the first leg of the ...

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Coastal Multibeam Bathymetry and Backscatter Data Collected in October 2019 from Rockaway Peninsula, New York: Leg 2

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) covering the nearshore, seaward side of Rockaway Peninsula, New York (NY), from October 24-29, 2019. This dataset, Rockaway_2019_MBES_Leg2_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid from the second leg of ...

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Coastal Multibeam Bathymetry Data Collected in 2018 Offshore of Seven Mile Island, New Jersey

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of Seven Mile Island, New Jersey, September 6-8, 2018 and September 21-23, 2018. This dataset, presented as Seven_Mile_Island_2018_MBES_WGS84_UTM18N_xyz.zip and Seven_Mile_Island_2018_MBES_NAD83_NAVD88_GEOID12B_xyz.zip, includes the processed elevation point data ...

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Coastal Multibeam Bathymetry Data Collected in 2019 off of Santa Rosa Island, Florida

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of Santa Rosa Island, Florida (FL), June 15-29, 2019. This dataset, Santa_Rosa_Island_2019_MBES_UTM16N_xyz.zip, includes the processed elevation point data (XYZ) as derived from a 1-meter (m) bathymetric grid.

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Coastal Multibeam Bathymetry Data Collected in August 2017 from the Chandeleur Islands, Louisiana

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of the Chandeleur Islands, Louisiana, August 9-12, 2017. This dataset, Chandeleur_Islands_2017_MBB_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid.

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Coastal Multibeam Bathymetry Data Collected in August 2018 from the Chandeleur Islands, Louisiana

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) offshore of the Chandeleur Islands, Louisiana, August 16-21, 2018. This dataset, Chandeleur_ Islands_2018_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid.

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Coastal Multibeam Bathymetry Data Collected in August 2019 from Cedar Island, Virginia

An Ellipsoidally Referenced Survey (ERS) using two Teledyne Reson SeaBat T50-P multibeam echosounders, in dual-head configuration, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), covering the nearshore, seaward of Cedar Island, Virginia, from August 14-21, 2019. This dataset, Cedar_ Island_2019_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 1-meter (m) bathymetric grid. Additionally, the dataset Cedar_Island ...

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Coastal Single-beam Bathymetry Data Collected in 2022 From Breton Island, Louisiana

As part of the restoration monitoring component of the Deepwater Horizon early restoration project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted single-beam and multibeam bathymetry surveys around Breton Island, Louisiana (LA), from August 3-5, 2022, for Field Activity Number (FAN) 2022-328-FA. The purpose of data collection was to develop a baseline digital elevation model of the seafloor around Breton Island for comparison with both ...

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Coastal Single-beam Bathymetry Data Collected in 2022 off Seven Mile Island, New Jersey

To determine continued change to the shoreface morphology and evolution at Seven Mile Island, New Jersey, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of Seven Mile Island, New Jersey, from April 29 - May 2, 2022. During this study, single-beam bathymetry data were collected using a personal watercraft (PWC) and a floating-towed-seismic sled. Both the PWC and the seismic sled ...

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Coastal Single-beam Bathymetry Data Collected in August 2018 from the Chandeleur Islands, Louisiana

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS - SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of the northern Chandeleur Islands, August 17-21, 2018. During this study, bathymetry data were collected aboard the research vessel (R/V) Jabba Jaw, a 21-foot (ft) twin hulled vessel outfitted with a single-beam echosounder.

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Coastal Single-beam Bathymetry Data Collected in August 2019 from Cedar Island, Virginia

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS - SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of Cedar Island, Virginia, August 9-15, 2019. During this study, bathymetry data were collected aboard a towed seismic sled outfitted with a single-beam echosounder.

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Coastal Single-beam Bathymetry Data Collected in September and October 2019 from Rockaway Peninsula, New York

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS - SPCMSC) in St. Petersburg, Florida, conducted a single-beam bathymetric survey of Rockaway Peninsula, New York September 27 - October 6, 2019. During this study, bathymetry data were collected aboard two personal watercraft (PWC) outfitted with single-beam echosounders, as well as a towed seismic sled with similar instrumentation.

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Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation

Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or ‘label images’) collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial oblique and nadir imagery. Images include a diverse range of coastal environments from the U.S. Pacific, Gulf of Mexico, ...

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CoconutIsland_2023_MBES: High-resolution Geophysical and Imagery Data Collected in May 2023 Near Fort Hase, Marine Corps Base Hawaii

An Ellipsoidally Referenced Survey (ERS) using a Norbit Winghead multibeam echosounder, was conducted by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) nearshore Coconut Island, on the island of Oahu, May 7, 2023. This dataset, CoconutIsland_2023_MBES_xyz.zip, includes the processed elevation point data (x,y,z), as derived from a 0.25 meter (m) bathymetric grid and the dataset CoconutIsland_2023_MBES_Backscatter.zip includes the acoustic backscatter intensity ...

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Collection, analysis, and age-dating of sediment cores from a salt marsh platform and ponds, Rowley, Massachusetts, 2014-15

Sediment cores were collected from three sites within the Plum Island Ecosystems Long-Term Ecological Research (PIE-LTER) domain in Massachusetts to obtain estimates of long-term marsh decomposition and evaluate shifts in the composition and reactivity of sediment organic carbon in disturbed marsh environments. Paired sediment cores were collected from three sites on the marsh platform and from three ponds; these cores were about 100 and 50 centimeters in length, respectively. The marsh sites had similar ...

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Collection, analysis, and age-dating of sediment cores from Herring River wetlands and other nearby wetlands in Wellfleet, Massachusetts, 2015–17

The Herring River estuary in Wellfleet, Cape Cod, Massachusetts, has been tidally restricted for more than a century by a dike constructed near the mouth of the river. Upstream from the dike, the tidal restriction has caused the conversion of salt marsh wetlands to various other ecosystems including impounded freshwater marshes, flooded shrub land, drained forested upland, and brackish wetlands dominated by Phragmites australis. This estuary is now managed by the National Park Service, which plans to ...

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Collection, analysis, and age-dating of sediment cores from mangrove and salt marsh ecosystems in Tampa Bay, Florida, 2015

Coastal wetlands in Tampa Bay, Florida, are important ecosystems that deliver a variety of ecosystem services. Key to ecosystem functioning is wetland response to sea-level rise through accumulation of mineral and organic sediment. The organic sediment within coastal wetlands is composed of carbon sequestered over the time scale of the wetland’s existence. This study was conducted to provide information on soil accretion and carbon storage rates across a variety of coastal ecosystems that was utilized in ...

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Collection, analysis, and age-dating of sediment cores from mangrove wetlands in San Juan Bay Estuary, Puerto Rico, 2016

The San Juan Bay Estuary, Puerto Rico, contains mangrove forests that store significant amounts of organic carbon in soils and biomass. There is a strong urbanization gradient across the estuary, from the highly urbanized and clogged Caño Martin Peña in the western part of the estuary, a series of lagoons in the center of the estuary, and a tropical forest reserve (Piñones) in the easternmost part with limited urbanization. We collected sediment cores to determine carbon burial rates and vertical ...

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Collection, analysis, and age-dating of sediment cores from natural and restored salt marshes on Cape Cod, Massachusetts, 2015-16

Nineteen sediment cores were collected from five salt marshes on the northern shore of Cape Cod where previously restricted tidal exchange was restored to part of the marshes. Cores were collected in duplicate from two locations within each marsh complex: one upstream and one downstream from the former tidal restriction (typically caused by an undersized culvert or a berm). The unaltered, natural downstream sites provide a comparison against the historically restricted upstream sites. The sampled cores ...

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Collection, Analysis, and Age-Dating of Sediment Cores from Salt Marshes on the South Shore of Cape Cod, Massachusetts, From 2013 Through 2014

The accretion history of fringing microtidal salt marshes located on the south shore of Cape Cod, Massachusetts, was reconstructed from sediment cores collected in low and high marsh vegetation zones. The location of these marshes within protected embayments and the absence of large rivers on Cape Cod result in minimal sediment supply and a dominance of organic matter contribution to sediment peat. Age models based on 210-lead and 137-cesium were constructed to evaluate how vertical accretion and carbon ...

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Collection, Analysis, and Age-Dating of Sediment Cores from Salt Marshes, Rhode Island, 2016

The accretion history of fringing salt marshes in Narragansett Bay, Rhode Island, was reconstructed from sediment cores. Age models, based on excess lead-210 and cesium-137 radionuclide analysis, were constructed to evaluate how vertical accretion and carbon burial rates have changed during the past century. The Constant Rate of Supply (CRS) age model was used to date six cores collected from three salt marshes. Both vertical accretion rates and carbon burial increased from 1900 to 2016, the year the data ...

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Comparison of methane concentration and stable carbon isotope data for natural samples analyzed by discrete sample introduction module - cavity ring down spectroscopy (DSIM-CRDS) and traditional methods

A discrete sample introduction module (DSIM) was developed and interfaced to a cavity ring-down spectrometer to enable measurements of methane and CO2 concentrations and 13C values with a commercially available cavity ring-down spectrometer (CRDS). The DSIM-CRDS system permits the analysis of limited volume (5 - 100-ml) samples ranging six orders-of-magnitude from 100% analyte to the lower limit of instrument detection (2 ppm). We demonstrate system performance for methane by comparing concentrations and ...

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Computed Tomography (CT) scans of sediment cores collected from Montague Island, AK

This dataset includes computed tomography (CT) scans of sediment cores collected from coastal environments on Montague Island, Alaska. The cores were collected with hand driven peat augers to assess environmental changes related to tectonic uplift caused by historic and prehistoric earthquakes.

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Computed tomography (CT) scans of sediment cores collected offshore southern Cascadia, during field activity 2019-643-FA

This dataset includes computed tomography (CT) scan imagery of sediment cores collected in southern Cascadia (offshore northern California) aboard the M/V Bold Horizon in September-October 2019.

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Computed tomography (CT) scans of vibracores collected offshore central California, during field activity 2019-651-FA

This dataset includes computed tomography (CT) scans of sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Conceptual marsh units for Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia

The salt marsh complex of Assateague Island National Seashore (ASIS) and Chincoteague Bay was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the Hurricane Sandy ...

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Conceptual marsh units for Cape Cod National Seashore salt marsh complex, Massachusetts

The salt marsh complex of Cape Cod National Seashore (CACO), Massachusetts, USA and approximal wetlands were delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the ...

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Conceptual marsh units for Fire Island National Seashore and central Great South Bay salt marsh complex, New York

The salt marsh complex of Fire Island National Seashore (FIIS) and central Great South Bay was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the Hurricane Sandy ...

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Conceptual marsh units for Jamaica Bay to western Great South Bay salt marsh complex, New York

This data release contains coastal wetland synthesis products for the geographic region from Jamaica Bay to western Great South Bay, located in southeastern New York State. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy ...

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Conceptual marsh units for Plum Island Estuary and Parker River salt marsh complex, Massachusetts

The salt marsh complex of Plum Island Estuary and Parker River (PIEPR) was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location was used to determine the ridge lines that separate each marsh unit while the surface slope was used to automatically assign each unit a drainage point, where water is expected to drain through. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. ...

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Conceptual marsh units of Blackwater salt marsh complex, Chesapeake Bay, Maryland

This data release contains coastal wetland synthesis products for the geographic region of Blackwater, Chesapeake Bay, Maryland. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and others, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to ...

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Conceptual marsh units of Chesapeake Bay salt marshes

This data release contains coastal wetland synthesis products for Chesapeake Bay. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the intent of providing ...

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Conceptual marsh units of Connecticut salt marshes

This data release contains coastal wetland synthesis products for the state of Connecticut. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, wave power, and exposure potential to environmental health stressors are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change ...

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Conceptual marsh units of eastern Long Island salt marsh complex, New York (ver. 2.0, March 2024)

This data release contains coastal wetland synthesis products for the geographic region of eastern Long Island, New York, including the north and south forks, Gardiners Island, and Fishers Island. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with ...

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Conceptual marsh units of Hudson Valley and New York City salt marsh complex, New York

This data release contains coastal wetland synthesis products for the geographic region of Hudson Valley and New York City, New York. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey ...

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Conceptual marsh units of Maine salt marshes

This data release contains coastal wetland synthesis products for the state of Maine. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, and lifespan, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the ...

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Conceptual marsh units of Massachusetts salt marshes

This data release contains coastal wetland synthesis products for Massachusetts, developed in collaboration with the Massachusetts Office of Coastal Zone Management. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal ...

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Conceptual marsh units of north shore Long Island salt marsh complex, New York

This data release contains coastal wetland synthesis products for the geographic region of north shore Long Island, New York. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been ...

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Conceptual marsh units of salt marshes on the Eastern Shore of Virginia

This data release contains coastal wetland synthesis products for the Atlantic-facing Eastern Shore of Virginia (the data release for the Chesapeake Bay-facing portion of the Eastern Shore of Virginia is found here: https://doi.org/10.5066/P997EJYB). Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland ...

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Conceptual salt marsh units for wetland synthesis: Edwin B. Forsythe National Wildlife Refuge, New Jersey

The salt marsh complex of the Edwin B. Forsythe National Wildlife Refuge (EBFNWR), which spans over Great Bay, Little Egg Harbor, and Barnegat Bay (New Jersey, USA), was delineated to smaller, conceptual marsh units by geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain ...

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Conductivity, temperature and depth time-series data collected in 2011 in the vicinity of Arey Lagoon and Barter Island, Alaska

Time-series measurements of waves, currents, water levels, sea surface temperatures, ocean salinity, and water, air, and ground temperatures were collected in July through September 2011 in and around Arey Lagoon, near Barter Island, Alaska. Directional wave spectra, currents, water levels, salinity, and bottom and surface water temperatures were measured with a bottom-mounted 1MHz Nortek AWAC, HOBO temperature loggers, and a Solinst Levelogger in ~5m water depth offshore of Arey Island. Within Arey Lagoon, ...

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Continuous core photographs of sediment cores collected in 2009 offshore from Palos Verdes, California

This part of the data release includes continuous core photographs in bmp format of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan ...

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Continuous core photographs of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California

This part of the data release includes continuous core photographs in bmp format of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely ...

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Continuous Resistivity Profiling, Electrical Resistivity Tomography and Hydrologic Data Collected in 2017 from Indian River Lagoon, Florida

Extending 200 kilometers (km) along the Atlantic Coast of Central Florida, Indian River Lagoon (IRL) is one of the most biologically diverse estuarine systems in the continental United States. The lagoon is characterized by shallow, brackish waters and a width that varies between 0.5 and 9.0 km; there is significant human development along both shores. Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center used continuous resistivity profiling (CRP, a towed ...

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Coordinates of vibracores collected offshore central California, during field activity 2019-651-FA (ver 2.0, August 2023)

This dataset includes coordinate information for sediment cores collected offshore central California in the vicinity of Morro Bay. These data were collected aboard the M/V Bold Horizon in October 2019 for use in regional hazard assessments relating to the Hosgri Fault.

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Coral geochemistry time series from Kahekili, west Maui

Geochemical analysis (including stable boron, boron:calcium ratio, and carbon and oxygen isotopes) were measured from coral cores collected in July 2013 from the shallow reef at Kahekili in Kaanapali, west Maui, Hawaii from scleractinian Porites lobata.

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Coral growth parameters, Kahekili, west Maui

Surface runoff and submarine groundwater discharge in particular are known vectors to the coastal ocean of elevated nutrients and contaminants leading to eutrophication, algal overgrowth, and coral disease. Freshwater discharging directly from submarine groundwater vents off of Kahekili Beach Park, Kaanapali, in West Maui contains elevated nutrient concentrations and lower pH values. Coral cores were collected in July 2013 from the shallow reef at Kahekili in Kaanapali, West Maui, Hawaii from ...

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Coral reef profiles for wave-runup prediction

This data release includes representative cluster profiles (RCPs) from a large (>24,000) selection of coral reef topobathymetric cross-shore profiles (Scott and others, 2020). We used statistics, machine learning, and numerical modelling to develop the set of RCPs, which can be used to accurately represent the shoreline hydrodynamics of a large variety of coral reef-lined coasts around the globe. In two stages, the data were reduced by clustering cross-shore profiles based on morphology and hydrodynamic ...

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Core descriptions and sedimentologic data from vibracores and sand augers collected in 2021 and 2022 from Fire Island, New York

In 2021 and 2022, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS New York Water Science Center (NYWSC), on behalf of SPCMSC, conducted sediment sampling and ground penetrating radar (GPR) surveys at Point O' Woods and Ho-Hum Beach (NYWSC, 2021) and Watch Hill, Long Cove, and Smith Point (SPCMSC, 2022), Fire Island, New York. These data complement previous SPCMSC GPR and sediment sampling surveys conducted at Fire Island in 2016 ...

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CoSMoS 3.2 Northern California sub-regional tier 2 FLOW-WAVE model input files

This data set consists of physics-based Delft3D-FLOW and WAVE hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) sub-regional tier 2 simulations. Sub-regional tier 2 simulations cover portions of the Northern California open-coast region, from Point Arena to the California/Oregon state border, and they provide boundary conditions to higher-resolution simulations. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal ...

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CoSMoS 3.2 Northern California Tier 1 FLOW-WAVE model input files

This data set consists of physics-based Delft3D-FLOW and WAVE hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) Tier 1 simulations. Tier 1 simulations cover the Northern California open-coast region, from the Golden Gate Bridge to the California/Oregon state border, and they provide boundary conditions to higher-resolution simulations. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal storm conditions) and sea-level ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: 100-year storm in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: 1-year storm in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: 20-year storm in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: average conditions in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 coastal squeeze projections

Projected coastal squeeze derived from CoSMoS Phase 2 shoreline change and cliff retreat projections. Projected coastal squeeze extents illustrate the available area between shoreline (mean high water; MHW) positions and man-made structures and barriers (referred to as non-erodible structures) or cliff-top retreat, as applicable, for a range of sea-level rise scenarios. The coastal squeeze polygons include results from the Coastal Storm Modeling System (CoSMoS) shoreline change (CoSMoS-COAST; Vitousek and ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in San Diego County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in San Diego County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in San Diego County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in San Diego County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in San Diego County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in San Diego County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in San Diego County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in San Diego County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in San Diego County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in San Diego County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in San Diego County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in San Diego County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 runup projections

Geographic extent of projected runup associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in San Diego County

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in San Diego County

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in San Diego County

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in San Diego County

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in San Diego County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in San Diego County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in San Diego County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in San Diego County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS Southern California v3.0 Phase 2 projections of coastal cliff retreat due to 21st century sea-level rise

This dataset contains projections of coastal cliff-retreat rates and positions for future scenarios of sea-level rise (SLR). Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical and statistical models based on field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS) v.3.0 Phase 2 in Southern California. Details: Cliff ...

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CoSMoS Southern California v3.0 projections of shoreline change due to 21st century sea-level rise

This dataset contains projections of shoreline positions and uncertainty bands for future scenarios of sea-level rise. Projections were made using CoSMoS-COAST, a numerical model forced with global-to-local nested wave models and assimilated with lidar-derived shoreline vectors. Details: Projections of shoreline position in Southern California are made for scenarios of 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, and 5.0 meters of sea-level rise by the year 2100. Four datasets are available for different ...

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CTD_casts

Models project the Arctic Ocean will become undersaturated with respect to carbonate minerals in the next decade. Recent field results indicate parts may already be undersaturated in late summer months, when ice melt is at its greatest extent. However, few comprehensive datasets of carbonate system parameters in the Arctic Ocean exist. Researchers from the U.S. Geological Survey (USGS) and University of South Florida (USF) collected high-resolution measurements of pCO2, pH, total dissolved inorganic ...

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CTD_casts

Models project the Arctic Ocean will become undersaturated with respect to carbonate minerals in the next decade. Recent field results indicate parts may already be undersaturated in late summer months when ice melt is at its greatest extent. However, few comprehensive data sets of carbonate system parameters in the Arctic Ocean exist. Researchers from the U.S. Geological Survey (USGS) and University of South Florida (USF) collected high-resolution measurements of pCO2, pH, total dissolved inorganic ...

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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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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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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 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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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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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 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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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 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_DATABASE - Cascadia tsunami deposit database

The Cascadia Tsunami Deposit Database contains data on the location and sedimentological properties of tsunami deposits found along the Cascadia margin. Data have been compiled from 52 studies, documenting 59 sites from northern California to Vancouver Island, British Columbia that contain known or potential tsunami deposits. Bibliographical references are provided for all sites included in the database. Cascadia tsunami deposits are usually seen as anomalous sand layers in coastal marsh or lake sediments. ...

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Current profiler time-series data collected in 2009 offshore of Wainwright, Alaska

A time-series of binned current-velocities and recorded ping amplitudes were collected offshore Wainwright, Alaska, from August 24 to October 02, 2009 (UTC). Measurements were collected using a 1 MHz NortekTM AWAC acoustic Doppler current profiler mounted on a frame in approximately 10 m of water. The profiler was mounted on the frame 0.55 m off the bottom of the seafloor, and collected data in 8 vertical bins, centered at 1.95(bin1), 2.95, 3.95, 4.95, 5.95, 6.95, 7.95, and 8.95(bin8) meters above the ...

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Current-velocity time-series data collected in 2011 in the vicinity of Arey Lagoon and Barter Island, Alaska

Time-series measurements of waves, currents, water levels, sea surface temperatures, ocean salinity, and water, air, and ground temperatures were collected in July through September 2011 in and around Arey Lagoon, near Barter Island, Alaska. Directional wave spectra, currents, water levels, salinity, and bottom and surface water temperatures were measured with a bottom-mounted 1MHz Nortek AWAC, HOBO temperature loggers, and a Solinst Levelogger in ~5m water depth offshore of Arey Island. Within Arey Lagoon, ...

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Daily sediment loads during and after dam removal in the Elwha River, Washington, 2011 to 2016

Daily values of discharge and sediment loads were measured and estimated at U.S. Geological Survey gaging station 12046260, on the Elwha River at the diversion near Port Angeles, Washington. Daily data are reported from September 15, 2011 to September 30, 2016. Specific data include (1) date; (2) discharge; (3) suspended-sediment concentration and one standard-deviation bounds; (4) percentage of fine-grained particles (silts and clays) in suspension; (5) loads of total suspended-sediment, fine-grained ...

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Data and calculations to support the study of the sea-air flux of methane and carbon dioxide on the West Spitsbergen margin in June 2014

A critical question for assessing global greenhouse gas budgets is how much of the methane that escapes from seafloor cold seep sites to the overlying water column eventually crosses the sea-air interface and reaches the atmosphere. The issue is particularly important in Arctic Ocean waters since rapid warming there increases the likelihood that gas hydrate--an ice-like form of methane and water stable at particular pressure and temperature conditions within marine sediments--will break down and release its ...

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration measures for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 2 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 3 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 4 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 5 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 6 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 7 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Initial DEMs with and without restoration alternatives R2-R7

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

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Dauphin Island Decadal Hindcast Model Inputs and Results: Final DEM

The model output of bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in USGS Open-File Report 2019–1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020).

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Dauphin Island Decadal Hindcast Model Inputs and Results: Initial DEM

The model input for the bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in U.S. Geological Survey (USGS) Open-File Report 2019-1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020).

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Intermediate-Low Sea Level Rise (SLR) Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Low Sea Level Rise (SLR) Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Present-Day Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Intermediate-Low Sea Level Rise Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Low Sea Level Rise Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Intermediate-Low Sea Level Rise Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Low Sea Level Rise Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Present-Day Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

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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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Deployments of autonomous, GPS ocean ocean-surface drifters, Makua, Kauai, USA, August 2016

Satellite-tracked, DGPS-equipped Lagrangian surface-current drifter deployments were conducted over 6 days between 30 July and 4 August 2016 at various locations and stages of the tide over the coral reef off Makua, HI. The drifters internally logged their location every 1 minute, and they transmitted their positions to satellites every 5 minutes. A drogue was attached to the drifters at 1 m below sea level in order to track the currents at that depth.

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Digital elevation models (DEMs) of coastal North Carolina, from 2019-08-30 to 2019-09-02, Pre-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected between August 30 and September 2, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions prior to Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface before Hurricane Dorian and were created to document inter-annual changes in ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected between September 08 and September 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions post-Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface after Hurricane Dorian and were created to document inter-annual changes in ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2020-02-08 to 2020-02-09

Digital elevation models (DEMs) were created from aerial imagery collected February 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2020-05-08 to 2020-05-09

Digital elevation models (DEMs) were created from aerial imagery collected May 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using aerial ...

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Digital elevation models (DEMs) of coastal North Carolina, on 2019-10-11, one month Post-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected October 11, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions one-month after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ...

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Digital elevation models (DEMs) of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian

Digital elevation models (DEMs) were created from aerial imagery collected November 26, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions two-months after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ...

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Digital elevation models of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016

This part of the data release presents digital elevation models (DEMs) spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the DEMs were created, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were collected ...

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Digital seafloor images and sediment grain size from the mouth of the Columbia River, Oregon and Washington, 2014

This dataset includes 2,523 still images extracted from geo-referenced digital video imagery of the seafloor at the mouth of the Columbia River, OR and WA, USA, along with grain size analysis of the surface sediment. Underwater digital video was collected in September 2014 in the mouth of the Columbia River, USA, as part of the U.S. Geological Survey Coastal and Marine Geology Program contribution to the Office of Naval Research funded River and Inlets Dynamics experiment (RIVET II). Still images were ...

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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between Point Barrow and Icy Cape for the time period 1947 to 2012

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between the Colville River Delta and Point Barrow for the time period 1947 to 2005

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between the Okpilak-Hulahula River Delta and Colville River Delta for the time period 1947 to 2007

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between the U.S.-Canadian border and the Okpilak-Hulahula river delta for the time period 1947 to 2003

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between Point Barrow and Icy Cape for the time period 1947 to 2012

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between the Colville River Delta and Point Barrow for the time period 1947 to 2005

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between the Okpilak-Hulahula River Delta and Colville River Delta for the time period 1947 to 2007

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between the U.S.-Canadian border and the Okpilak-Hulahula River Delta for the time period 1947 to 2003

The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the originating ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed West Beaufort Sea coast of Alaska between the Colville River and Point Barrow

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the originating ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered West Beaufort Sea coast of Alaska between the Colville River and Point Barrow

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term End Point Rate Calculations for the Exposed East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape

This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2011. A reference baseline was used as the originating point ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term End Point Rate Calculations for the Sheltered East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape

This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the originating point ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River

This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River

This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2010. A reference baseline was ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed East Chukchi Sea coast of Alaska between the Point Barrow and Icy Cape

This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as the ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed West Beaufort Sea coast of Alaska between the Colville River and Point Barrow

This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River

This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River

This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2010. A reference baseline was ...

Info
Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered West Beaufort Sea coast of Alaska between the Colville River and Point Barrow

This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the ...

Info
Digital Shoreline Analysis System (DSAS) version 4.4 transects with long-term linear regression rate calculations for the exposed north coast of Alaska, from Icy Cape to Cape Prince of Wales

This dataset consists of long-term (less than 68 years) shoreline change rates for the exposed coast of the north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using a linear regression rate-of-change (lrr) method based on available shoreline data between 1948 and 2016. A reference baseline ...

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Digital Shoreline Analysis System (DSAS) version 4.4 transects with long-term linear regression rate calculations for the sheltered north coast of Alaska, from Icy Cape to Cape Prince of Wales

This dataset consists of long-term (less than 68 years) shoreline change rates for the sheltered north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using a linear regression rate-of-change (lrr) method based on available shoreline data between 1948 and 2016. A reference baseline was used ...

Info
Digital Shoreline Analysis System (DSAS) version 4.4 transects with short-term end-point rate-of-change calculations for the exposed north coast of Alaska, from Icy Cape to Cape Prince of Wales

This dataset consists of short-term (less than 37 years) shoreline change rates for the exposed coast of the north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using an end point rate-of-change (epr) method based on available shoreline data between 1980 and 2016. A reference baseline was ...

Info
Digital Shoreline Analysis System (DSAS) version 4.4 transects with short-term end-point rate-of-change calculations for the sheltered north coast of Alaska, from Icy Cape to Cape Prince of Wales

This dataset consists of short-term (less than 37 years) shoreline change rates for the sheltered north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using an end point rate-of-change (epr) method based on available shoreline data between 1980 and 2016. A reference baseline was used as the ...

Info
Digital Shoreline Analysis System (DSAS) version 4.4 transects with short-term linear regression rate calculations for the exposed north coast of Alaska, from Icy Cape to Cape Prince of Wales

This dataset consists of short-term (less than 37 years) shoreline change rates for the north coast of Alaska from Icy Cape to Cape Prince of Wales. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.4, an ArcGIS extension developed by the U.S. Geological Survey. Rates of shoreline change were calculated using a linear regression rate-of-change (lrr) method based on available shoreline data between 1980s and 2016. A reference baseline was used as the ...

Info
Digital Shoreline Analysis System (DSAS) version 5.0 transects with bluff rate change calculations for the north coast of Barter Island Alaska, 1950 to 2020

This dataset consists of rate-of-change statistics for the coastal bluffs at Barter Island, Alaska for the time period 1950 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each bluff line establishing measurement points, which are then used to ...

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Digital Shoreline Analysis System (DSAS) version 5.0 transects with shoreline rate change calculations at Barter Island Alaska, 1947 to 2020

This dataset consists of rate-of-change statistics for the shorelines at Barter Island, Alaska for the time period 1947 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to ...

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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Cape Cod region from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Delmarva North region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Delmarva South/Southern Virginia region from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Greater Boston region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts (GreaterBoston_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Massachusetts Islands Region including Martha's Vineyard and Nantucket (MA_Islands_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New England North region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts (NewEnglandN_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New England South region from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New Jersey North region from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New Jersey South region from Little Egg Inlet to Cape, May, New Jersey (NewJerseyS_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Rate Calculations for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Cape Cod region from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Delmarva North region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Delmarva South/Southern Virginia region from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Greater Boston region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts (GreaterBoston_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Massachusetts Islands Region including Martha's Vineyard and Nantucket (MA_Islands_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New England North region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts (NewEnglandN_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New England South region from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New Jersey North region from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New Jersey South region from Little Egg Inlet to Cape, May, New Jersey (NewJerseyS_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Long-Term Linear Regression Rate Calculations for Oregon (OR_transects_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Long-Term Linear Regression Rate Calculations for Washington (WA_transects_LT.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Short-Term End Point Rate Calculations for Oregon (OR_transects_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.2 Transects with Short-Term End Point Rate Calculations for Washington (WA_transects_ST.shp)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines for the North Shore coastal region from North Salisbury at the New Hampshire border to the west side of Deer Island in Boston harbor (NorthShore_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the Boston coastal region from Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the Buzzards Bay coastal region from Nobska Point in Woods Hole, to Westport at the Rhode Island border (BuzzardsBay_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the Cape Cod Bay coastal region from the Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the Elizabeth Islands coastal region from Nonamesset Island southwest of Woods Hole to Cuttyhunk Island north of Martha's Vineyard (ElizabethIslands_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands Massachusetts-Rhode Island border (Nantucket_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970-1979 and 1994 shorelines within the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich (SouthShore_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics excluding the 1970's and 1994 shorelines within the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_intersects_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the Boston coastal region from Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the Buzzards Bay coastal region from Nobska Point in Woods Hole, to Westport at the Rhode Island border (BuzzardsBay_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the Cape Cod Bay coastal region from Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the Elizabeth Islands coastal region from Nonamesset Island southwest of Woods Hole to Cuttyhunk Island north of Martha's Vineyard (ElizabethIslands_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the North Shore coastal region from North Salisbury at the New Hampshire border to the west side of Deer Island in Boston Harbor (NorthShore_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics for the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate long-term shoreline change statistics within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands (Nantucket_intersects_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics for the Boston coastal region from Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics for the Buzzards Bay coastal region from Nobska Point in Woods Hole, to Westport at the Rhode Island border (BuzzardsBay_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics for the Cape Cod Bay coastal region from the Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics for the Elizabeth Islands coastal region from Nonamesset Island southwest of Woods Hole to Cuttyhunk Island north of Martha's Vineyard (ElizabethIslands_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics for the North Shore coastal region from North Salisbury at the New Hampshire border to the west side of Deer Island in Boston Harbor (NorthShore_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics for the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics for the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate)shoreline change statistics for the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich (SouthShore_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (End Point Rate) shoreline change statistics within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands (Nantucket_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term linear regression rate (LRR) shoreline change statistics for the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich (SouthShore_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics for the Boston coastal region from Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics for the Buzzards Bay coastal region from Nobska Point in Woods Hole, to Westport at the Rhode Island border (BuzzardsBay_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics for the Cape Cod Bay coastal region from Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_intersects_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics for the North Shore coastal region from North Salisbury at the New Hampshire border to the west side of Deer Island in Boston Harbor (NorthShore_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics for the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics for the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 shoreline intersection points used to calculate short-term (Linear Regression Rate) shoreline change statistics within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands (Nantucket_intersects_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available in the Boston coastal region Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available in the Buzzards Bay coastal region from Nobska Point in Woods Hole to Westport at the Rhode Island border (BuzzardsBay_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available in the North Shore coastal region from North Salisbury at the New Hampshire border to the to the west side of Deer Island in Boston Harbor (NorthShore_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available within the Cape Cod Bay coastal region from the Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands (Nantucket_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available within the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available within the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics for all data available within the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich (SouthShore_transects_rates_LTw.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 in the Boston coastal region from Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 in the Buzzards Bay coastal region from Nobska Point in Woods Hole, to Westport at the Rhode Island border (BuzzardsBay_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 in the Elizabeth Islands coastal region from Nonamesset Island southwest of Woods Hole to Cuttyhunk Island north of Martha's Vineyard (ElizabethIslands_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 within the Cape Cod Bay coastal region from the Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands (Nantucket_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 within the North Shore coastal region from North Salisbury at the New Hampshire border to the west side of Deer Island in Boston Harbor (NorthShore_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 within the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970-1979 and 1994 within the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich (SouthShore_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and long-term linear regression shoreline change statistics without shorelines from 1970s and 1994 within the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_transects_rates_LTwo.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point rate shoreline change statistics for the Boston coastal region from Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point rate shoreline change statistics for the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point rate shoreline change statistics within the Cape Cod Bay coastal region from the Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point shoreline change statistics for the Buzzards Bay coastal region from Nobska Point in Woods Hole, to Westport at the Rhode Island border (BuzzardsBay_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point shoreline change statistics for the Elizabeth Islands coastal region from Nonamesset Island southwest of Woods Hole to Cuttyhunk Island north of Martha's Vineyard (ElizabethIslands_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point shoreline change statistics for the North Shore coastal region from North Salisbury at the New Hampshire border to the west side of Deer Island in Boston Harbor (NorthShore_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point shoreline change statistics for the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich (SouthShore_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point shoreline change statistics within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) end point shoreline change statistics within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands (Nantucket_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression rate shoreline change statistics within the Cape Cod Bay coastal region from the Cape Cod Canal in Sandwich to Long Point in Provincetown (CapeCodBay_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics for all data available in the North Shore coastal region from North Salisbury at the New Hampshire border to the west side of Deer Island including the Boston Harbor Islands (NorthShore_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics for the Boston coastal region from Carson Beach in South Boston to Weymouth River, including the Boston Harbor Islands (Boston_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics for the Buzzards Bay coastal region from Nobska Point in Woods Hole, to Westport at the Rhode Island border (BuzzardsBay_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics for the Outer Cape Cod coastal region from Long Point in Provincetown to Monomoy Island (OuterCapeCod_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics for the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics for the South Shore coastal region from Hewitts Cove in Hingham to the Cape Cod Canal in Sandwich (SouthShore_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics within the Martha's Vineyard coastal region including the Vineyard Sound-, Nantucket Sound- and Atlantic Ocean- facing coasts of Martha's Vineyard and Nomans Land (MarthasVineyard_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term (1970-2009) linear regression shoreline change statistics within the Nantucket coastal region including the Nantucket Sound- and Atlantic Ocean- facing coasts of Nantucket, Muskeget and Tuckernuck Islands (Nantucket_transects_rates_STlr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 transects and short-term end point shoreline change statistics for all data available within the South Cape Cod coastal region from Stage Harbor Light in Chatham to Nobska Point in Woods Hole (SouthCapeCod_transects_rates_STepr.shp)

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Alabama

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for central North Carolina (NCcentral)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Florida north (FLnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Florida west (FLwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Georgia (GA)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Louisiana

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Mississippi

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for northeastern Florida (FLne)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for northern North Carolina (NCnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for South Carolina (SC)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for southeastern Florida (FLse)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for southern North Carolina (NCsouth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Texas east (TXeast)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Texas west (TXwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for western North Carolina (NCwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Alabama

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for central North Carolina (NCcentral)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Florida north (FLnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Florida west (FLwest)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

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Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Georgia (GA)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Louisiana

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Mississippi

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for northeastern Florida (FLne)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for northern North Carolina (NCnorth)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ...

Info
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for South Carolina (SC)

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand fo