Long, Joseph W.

About the author


EAARL Coastal Topography-Louisiana, Mississippi and Alabama, March 2006: First Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

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EAARL Coastal Topography-Louisiana, Mississippi and Alabama, March 2006: Last Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
EAARL Coastal Topography--Louisiana, Mississippi and Alabama September 2006: First Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
EAARL Coastal Topography--Louisiana, Mississippi and Alabama September 2006: Last Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Locations of convergences in the maximum alongshore current

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

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Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Locations of decelerations in the direction of flow in the maximum alongshore current

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: peak wave period

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Ratio of the wave- and current-induced shear stress to the critical value for oil-tar balls and sediment mobilization over a tidal cycle

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Ratio of the wave- and current-induced shear stress to the critical value for oil-tar balls and sediment mobilization weighted by probability of wave scenario occurrence

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Ratio of wave- and current-induced shear stress to critical values for oil-sand ball and sediment mobilization

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Significant wave height

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Surf-zone integrated alongshore potential flux for oil-sand balls

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Surf-zone integrated alongshore potential flux for oil-sand balls of varying sizes weighted by probability of wave scenario occurrence

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: wave direction

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Scenarios_Grid

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Tidal_Grid

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Southeast Atlantic Salvo to Duck, North Carolina Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives features of beach morphology from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes along the United States Southeast Atlantic Ocean from Salvo to Duck, North Carolina for data collected at various times between 1996 and 2012.

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National Assessment of Hurricane-Induced Coastal Erosion Hazards: Southeast Atlantic Salvo to Duck, North Carolina Raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives features of beach morphology from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Southeast Atlantic Ocean from Salvo to Duck, North Carolina for data collected at various times between 1996 and 2012.

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Storm-Impact Scenario XBeach Model Results – Scenario 1 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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Storm-Impact Scenario XBeach Model Inputs – Initial Bathymetry and Topography Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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Storm-Impact Scenario XBeach Model Results – Scenario 11 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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Storm-Impact Scenario XBeach Model Results – Scenario 12 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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Storm-Impact Scenario XBeach Model Results – Scenario 20 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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Storm-Impact Scenario XBeach Model Results – Scenario 2 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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Storm-Impact Scenario XBeach Model Results – Scenario 3 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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Storm-Impact Scenario XBeach Model Results – Scenario 6 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

Info
Storm-Impact Scenario XBeach Model Results – Scenario 7 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

Info
Storm-Impact Scenario XBeach Model Results – Scenario 8 Digital Elevation Model (DEM) Grid

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

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

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

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

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

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

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

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

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

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

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

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

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

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2009 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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2010 Alabama and Florida USACE Lidar-Derived Dune Crest, Toe and Shoreline

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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2014 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 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 Post-Hurricane ...

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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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June 2008 Alabama and Florida USGS EAARL Lidar-derived dune crest, toe and shoreline

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

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March 2006 Mississippi and Alabama USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

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

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September 2006 Mississippi and Alabama USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

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

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September 2006 Post-Hurricane Wilma Florida U.S. Army Corps of Engineers Lidar-Derived Dune Crest, Toe and Shoreline

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

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September 2007 Southwest Florida Division of Emergency Management Lidar-Derived Dune Crest, Toe and Shoreline

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

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XBeach Bottom Friction Scenarios: Model Inputs and Results

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Constant Land Friction Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Default Friction Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Spatially Varying Friction Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina before Hurricane Ivan Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Constant Land Friction Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Default Friction Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Spatially Varying Friction Scenario

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama 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) time series. Model inputs ...

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

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

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2004 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 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 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 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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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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2013 NOAA Oahu Lidar-Derived Dune Crest, Toe and Shoreline

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

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

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

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

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

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2015 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 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 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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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2005/06/19 through 2005/11/20 Deterministic Scenario

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2015/08/27 through 2015/08/29 Deterministic Scenario

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2015/12/09 through 2015/12/11 Deterministic Scenario

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 10-Year Simulation with 0.5-meter of Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 10-Year Simulation Without Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 2010 Simulation With 0.5-meter of Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 2010 Simulation With 0.5-meter of Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 2010 Simulation Without Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Initial Existing Conditions Grid

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Initial Project Conditions Grid

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 10-Year Simulation With 0.5-meter of Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 10-Year Simulation Without Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 2010 Simulation Without Sea Level Rise

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

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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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July 2010 Dauphin Island USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

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

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September 2007 Northern Gulf of Mexico USGS EAARL Lidar-Derived Dune Crest, Toe and Shoreline

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

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Massachusetts raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Northeast Atlantic Ocean for Massachusetts for data collected at various times between 2000 and 2013

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Massachusetts Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes for Massachusetts for data collected at various times between 2000 and 2013.

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New Jersey Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes for New Jersey for data collected at various times between 2007 and 2014.

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New Jersey raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Northeast Atlantic Ocean for New Jersey for data collected at various times between 2007 and 2014

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Wave Scenario Grid with Proposed Sediment Borrow Pit 3 of Breton Island, Louisiana: Model Input Grid 4 with Pit 3 Configuration

The Simulating WAves Nearshore (SWAN) wave model input grid 4 bathymetry with pit 3 configuration (G4_P3_grid.shp) and output of significant wave height, dominant wave period, and mean wave direction resulting from simulation of wave scenarios at Breton Island, LA, as described in USGS Open-File Report 20151055 are provided here.

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Beach Profile Data Collected From Madeira Beach, Florida (February 17, 2017)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (May 9, 2017)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (November 30, 2016)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (November, 9 2017)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (September 14, 2017)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (September 9, 2016)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Extratropical Storm March 2018 Assessment of Potential Coastal Change Impacts: 0800 AM EST FRI MAR 02 2018

This dataset defines storm-induced coastal erosion hazards for the North Carolina, Virginia, Maryland, Delaware, New Jersey, New York, Rhode Island, Massachusetts, New Hampshire and Maine coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of an Extratropical Storm in March 2018. Storm-induced water levels, due to both surge and waves, were ...

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Subtropical Storm Alberto Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0800 AM EDT SUN MAY 27 2018

This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Subtropical Storm Alberto in May 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the ...

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Tropical Storm Gordon Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0700 AM CDT TUE SEP 04 2018

This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Tropical Storm Gordon in September 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the ...

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Hurricane Matthew Overwash Extents

The National Assessment of Coastal Change Hazards project exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the southeast coast of the United States from Florida to North Carolina and attributed to coastal processes during [Atlantic Basin] Hurricane Matthew, which made landfall in the U.S. on October 8, 2016.

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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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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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Beach Profile Data Collected from Madeira Beach, Florida (January 24, 2018)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (July 10, 2020)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (June 10, 2020)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (October 15, 2018)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (September 18, 2019)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (April 21, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (December 18, 2020)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (January 15, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (March 3, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (November 10, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (November 16, 2020)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (November 6, 2020)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (September 21, 2020)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (September 8, 2020)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: False-Floor Experiment Flow Velocity and Shear Stress

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ...

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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: False-Floor Experiment Interpretive Video

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ...

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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Flow Velocity

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ...

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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ...

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Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Interpretive Video

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ...

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Laboratory Observations of Artificial Sand and Oil Agglomerates: Video and Velocity Data: Sea Floor Interaction Experiment Preview Video (GoPro)

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ...

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Laboratory Observations of Artificial Sand and Oil Agglomerates: Video and Velocity Data: Sea Floor Interaction Experiment Video (GoPro)

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 ...

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Beach Profile Data Collected from Madeira Beach, Florida (August 26, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (December 8, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (July 9, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (June 16, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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Beach Profile Data Collected from Madeira Beach, Florida (September 24, 2021)

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

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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).

Info
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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