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Hillshade of lidar-derived, bare earth digital elevation model, with 235-degree azimuth and 20-degree sun angle, 0.25m resolution, depicting earthquake effects following the August 24, 2014 South Napa Earthquake.
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Carlisle 30 x 60 minute quadrangle in Pennsylvania. The source data used to construct this imagery consists of 1-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2019 and 2020 and downloaded from the USGS National Map TNM Download. The data were processed using geographic information systems (GIS) software. The data is projected in WGS 1984 Web Mercator. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief according to a topographic position index (TPI) calculation.
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Separate data for floodplain elevation and bathymetry were collected on the Upper Mississippi River System (UMRS) by the US Army Corps of Engineers (USACE), Upper Mississippi River Restoration (UMRR) Program. While many information needs can be met by using these data separately, in many cases seamless elevation data across the river and its floodplain are needed. This seamless elevation surface was generated by merging lidar (i.e., floodplain elevation) and bathymetry data. Merging the data required special processing in the areas of transition between the two sources of data.
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This dataset is a digital elevation model (DEM) of the beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, Minnesota. The DEM has a 10-meter (m; 32.8084 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography, and multibeam sonar data representing the bathymetry. The survey area extends approximately 0.85 kilometers (0.5 miles) offshore, for an approximately 1.87 square kilometer surveyed area. Lidar data were collected September 23, 2020 using a boat mounted Velodyne unit. Multibeam sonar data were collected September 22-23, 2020 using a Norbit integrated wide band multibeam system compact (iWBMSc)...
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This dataset is a digital elevation model (DEM) of the beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, Minnesota. The DEM has a 5-meter (m; 16.404 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography, and multibeam sonar data representing the bathymetry. The survey area extends approximately 0.85 kilometers (0.5 miles) offshore, for an approximately 1.87 square kilometer surveyed area. Lidar data were collected September 23, 2020 using a boat mounted Velodyne unit. Multibeam sonar data were collected September 22-23, 2020 using a Norbit integrated wide band multibeam system compact (iWBMSc)...
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This dataset represents post-nourishment digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Minnesota Point near the Duluth Entry of Lake Superior, Duluth, Minnesota. The Lidar DEM has a 1-meter (m; 3.28084 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography. The topobathy DEMs have a 10-meter (m; 32.8084 feet) or a 5-meter (m; 16.4042 feet) cell size, and were created from a combined LAS dataset of lidar data representing the beach topography, and single-beam and multibeam sonar data representing the bathymetry. The survey area extends approximately 1 kilometers (0.62 miles) offshore, for an...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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This dataset contains a 6 foot resolution digital elevation model (DEM) covering two watersheds in Clarksburg, Montgomery County, Maryland.
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Separate data for floodplain elevation and bathymetry were collected on the Upper Mississippi River System (UMRS) by the US Army Corps of Engineers (USACE), Upper Mississippi River Restoration (UMRR) Program. While many information needs can be met by using these data separately, in many cases seamless elevation data across the river and its floodplain are needed. This seamless elevation surface was generated by merging lidar (i.e., floodplain elevation) and bathymetry data. Merging the data required special processing in the areas of transition between the two sources of data.
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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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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Roanoke 30 x 60 minute quadrangle in Virginia. It also covers a part of the Appalachian Basin Province. The source data used to construct this imagery consists of 1-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2017 and 2021 and downloaded from the USGS National Map TNM Download. The data were processed using geographic information systems (GIS) software. The data spatial reference is the WGS 1984 geographic coordinate system. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief...
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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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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Harrisburg 30 x 60 minute quadrangle in Pennsylvania. It also covers part of the Delaware River Basin. The source data used to construct this imagery consist of 1-meter and 3-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2013 and 2018 from the U.S. Department of Agriculture (USDA) and the US Geological Survey (USGS). The data were processed using geographic information systems (GIS) software. The data are projected in North America Datum (NAD) UTM Zone 18 North. This representation illustrates the terrain as a hillshade with contrast...
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Separate data for floodplain elevation and bathymetry were collected on the Upper Mississippi River System (UMRS) by the US Army Corps of Engineers (USACE), Upper Mississippi River Restoration (UMRR) program. While many information needs can be met by using these data separately, in many cases seamless elevation data across the river and its floodplain are needed. This seamless elevation surface was generated by merging lidar (i.e., floodplain elevation) and bathymetry data. Merging the data required special processing in the areas of transition between the two sources of data.
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Separate data for floodplain elevation and bathymetry were collected on the Upper Mississippi River System (UMRS) by the US Army Corps of Engineers (USACE), Upper Mississippi River Restoration (UMRR) program. While many information needs can be met by using these data separately, in many cases seamless elevation data across the river and its floodplain are needed. This seamless elevation surface was generated by merging lidar (i.e., floodplain elevation) and bathymetry data. Merging the data required special processing in the areas of transition between the two sources of data.
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This dataset represents post-nourishment digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Minnesota Point near the Duluth Entry of Lake Superior, Duluth, Minnesota. The Lidar DEM has a 1-meter (m; 3.28084 feet) cell size and was created from a LAS dataset of terrestrial light detection and ranging (lidar) data representing the beach topography. The topobathy DEMs have a 10-meter (m; 32.8084 feet) or a 5-meter (m; 16.4042 feet) cell size, and were created from a combined LAS dataset of lidar data representing the beach topography, and single-beam and multibeam sonar data representing the bathymetry. The survey area extends approximately 0.85 kilometers (0.5 miles) offshore, for...


map background search result map search result map Pre-pulse lidar UMRR Pool 15 Topobathy UMRR Pool 16 Topobathy UMRR Dresden Reach Topobathy UMRR Marseilles Topobathy Hillshade raster (235-degree azimuth, 20-degree sun angle) derived from lidar data collected after the August 24, 2014 South Napa earthquake LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 LEAN-Corrected Collier County DEM for wetlands ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014 ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014 Raw Digital Elevation Model in Clarksburg, MD Duluth Entry: 10-meter Digital elevation model (DEM) of beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, MN, September 2020 Duluth Entry: 5-meter Digital elevation model (DEM) of beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, MN, September 2020 Enhanced Terrain Imagery of the Harrisburg 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Digital elevation models (DEMs) of beach topography and near-shore bathymetry of Minnesota Point near the Duluth Entry of Lake Superior, Duluth, MN, October 2021 Digital elevation models (DEMs) of beach topography and near-shore bathymetry of Minnesota Point, near the Superior Entry of Lake Superior, Duluth, MN, September 2021 Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Roanoke 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Duluth Entry: 10-meter Digital elevation model (DEM) of beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, MN, September 2020 Duluth Entry: 5-meter Digital elevation model (DEM) of beach topography and near-shore bathymetry of Lake Superior at the Duluth Entry, Duluth, MN, September 2020 Digital elevation models (DEMs) of beach topography and near-shore bathymetry of Minnesota Point near the Duluth Entry of Lake Superior, Duluth, MN, October 2021 Digital elevation models (DEMs) of beach topography and near-shore bathymetry of Minnesota Point, near the Superior Entry of Lake Superior, Duluth, MN, September 2021 Raw Digital Elevation Model in Clarksburg, MD UMRR Pool 15 Topobathy UMRR Dresden Reach Topobathy UMRR Pool 16 Topobathy UMRR Marseilles Topobathy ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014 Enhanced Terrain Imagery of the Roanoke 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Pre-pulse lidar Enhanced Terrain Imagery of the Harrisburg 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 LEAN-Corrected Collier County DEM for wetlands