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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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U.S. Geological Survey Rocky Mountain Region inland bathymetric survey data are compiled to create a survey inventory providing survey records including survey system and product information, and links to survey datasets when available. Dataset footprints including this information and showing the location and extent of surveys can be downloaded as a shapefile or geodatabase and can be accessed through Spatial Services provided here.
Hurricane Sandy, which made landfall on October 29, 2012, near Brigantine, New Jersey, had a significant impact on coastal New Jersey, including the large areas of emergent wetlands at Edwin B. Forsythe National Wildlife Refuge (NWR) and the Barnegat Bay region. In response to Hurricane Sandy, U.S. Geological Survey (USGS) has undertaken several projects to assess the impacts of the storm and provide data and scientific analysis to support recovery and restoration efforts. As part of these efforts, the USGS Coastal and Marine Geology Program (CMGP) sponsored Coastal National Elevation Database (CoNED) Applications Project in collaboration with the USGS National Geospatial Program (NGP), and National Oceanic and...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for Suisun marsh using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (6912 points, collected across public and private land in 2018), Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image (June 2018), a 1 m lidar DEM from September 2018, and a 1 m canopy surface model were used to generate models of predicted bias across the...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for tidal marsh areas around San Francisco Bay using the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). Survey-grade GPS survey data (6614 points), NAIP-derived Normalized Difference Vegetation Index, and original 1 m lidar DEM from 2010 were used to generate a model of predicted bias across tidal marsh areas. The predicted bias was then subtracted from the original lidar DEM and merged with the NOAA...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for wetlands throughout Collier county using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (15,223 points), NAIP-derived Normalized Difference Vegetation Index (2010), a 10 m lidar DEM from 2007, and a 10 m canopy surface model were used to generate a model of predicted bias across marsh, mangrove, and cypress habitats. The predicted bias was then subtracted from...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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U.S. Geological Survey Northeast Region inland bathymetric survey data are compiled to create a survey inventory providing survey records including survey system and product information, and links to survey datasets when available. Dataset footprints including this information and showing the location and extent of surveys can be downloaded as a shapefile or geodatabase and can be accessed through Spatial Services provided here.
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for the area surrounding Blackwater National Wildlife Refuge in Chesapeake Bay using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (3699 points, collected across four tidal marsh sites in Chesapeake Bay (Eastern Neck, Martin, Bishops Head, and Blackwater) in 2010 and 2017. Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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U.S. Geological Survey Southeast Region inland bathymetric survey data are compiled to create a survey inventory providing survey records including survey system and product information, and links to survey datasets when available. Dataset footprints including this information and showing the location and extent of surveys can be downloaded as a shapefile or geodatabse and can be accessed through Spatial Services provided here.
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The U.S. Geological Survey (USGS) Inland Bathymetric and Topobathymetric Survey Inventory, v. 3 includes a survey records inventory and dataset footprints (when available) for inland bathymetric and topobathymetric surveys published by the USGS for the conterminous US and Puerto Rico. Survey records include water feature, state, publication title, data vintage, mission, online linkage to reports and datasets, collection methods, survey and survey product resolution, datums, geoid, and accuracy information if known. This database, identified as the USGS Inland Bathymetric and Topobathymetric Survey Inventory, v.3, has been approved for release by the U.S. Geological Survey (USGS). Although this database has been...
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Changes in tidal marsh area and habitat type in response to sea-level rise were modeled using the Sea Level Affecting Marshes Model (SLAMM 6) that accounts for the dominant processes involved in wetland conversion and shoreline modifications during long-term sea level rise (Park et al. 1989; Successive versions of the model have been used to estimate the impacts of sea level rise on the coasts of the U.S. The model was produced by Warren Pinnacle Consulting, Inc. for the U.S. Fish and Wildlife Service. The SLAMM version 6 technical document can be accessed at http://warrenpinacle.com/prof/SLAMM. SLAMM outputs were converted from raster to vector features. Land cover (wetland) types were generalized to MesoHabitat...
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U.S. Geological Survey Midcontinent Region inland bathymetric survey data are compiled to create a survey inventory providing survey records including survey system and product information, and links to survey datasets when available. Dataset footprints including this information and showing the location and extent of surveys can be downloaded as a shapefile or geodatabase and can be accessed through Spatial Services provided here.
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U.S. Geological Survey Southwest Region inland bathymetric survey data are compiled to create a survey inventory providing survey records including survey system and product information, and links to survey datasets when available. Dataset footprints including this information and showing the location and extent of surveys can be downloaded as a shapefile or geodatabse and can be accessed through Spatial Services provided here.


map background search result map search result map Seaside Sparrow- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Black Skimmer- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Clapper Rail- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Hudsonian Godwit- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Royal Tern - Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Western Sandpiper- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Wilson's Plover - Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Black Rail- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Whooping Crane - Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions 2010: Delineation of Water Bodies in Emergent Wetlands in Coastal New Jersey LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 LEAN-Corrected DEM for Suisun Marsh Blackwater LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 LEAN-Corrected Collier County DEM for wetlands U.S. Geological Survey Inland Bathymetric and Topobathymetric Survey Inventory, version 3 U.S. Geological Survey Northeast Region Inland to Coastal Zone Bathymetric Surveys U.S. Geological Survey Southeast Region Inland to Coastal Zone Bathymetric Surveys U.S. Geological Survey Midcontinent Region Inland Bathymetric Surveys U.S. Geological Survey Southwest Region Bathymetry Surveys U.S. Geological Survey Rocky Mountain Region Inland Bathymetric Surveys LEAN-Corrected DEM for Suisun Marsh Blackwater LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 2010: Delineation of Water Bodies in Emergent Wetlands in Coastal New Jersey LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 LEAN-Corrected Collier County DEM for wetlands Whooping Crane - Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Black Skimmer- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Clapper Rail- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Black Rail- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Seaside Sparrow- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Hudsonian Godwit- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Royal Tern - Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Western Sandpiper- Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions Wilson's Plover - Potential Habitat Under Sea Level Affecting Marshes Model (SLAMM) Conditions U.S. Geological Survey Rocky Mountain Region Inland Bathymetric Surveys U.S. Geological Survey Southwest Region Bathymetry Surveys U.S. Geological Survey Northeast Region Inland to Coastal Zone Bathymetric Surveys U.S. Geological Survey Southeast Region Inland to Coastal Zone Bathymetric Surveys U.S. Geological Survey Midcontinent Region Inland Bathymetric Surveys U.S. Geological Survey Inland Bathymetric and Topobathymetric Survey Inventory, version 3