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Defining site potential for an area establishes its possible long-term vegetation growth productivity in a relatively undisturbed state, providing a realistic reference point for ecosystem performance. Modeling and mapping site potential helps to measure and identify naturally occurring variations on the landscape as opposed to variations caused by land management activities or disturbances (Rigge et al. 2020). We integrated remotely sensed data (250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) (https://earthexplorer.usgs.gov/)) with land cover, biogeophysical (i.e., soils, topography) and climate data into regression-tree software (Cubist®). We...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Naomi Outfall Management (BA-0003c), Barataria Bay Waterway East Side Shoreline Protection (BA-0026), and Naomi Freshwater Diversion (BA-0003) projects for 2018. This data is used as a basemap land-water classification. It also serves as...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the West Lake Boudreaux Shoreline Protection and Marsh Creation (TE-46) project for 2021. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems...
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This USGS Data Release represents geospatial and tabular data for the Nisqually River Delta historical habitat mapping. The data release was produced in compliance with the new 'open data' requirements as a way to make the scientific products associated with USGS research efforts and publications available to the public. The dataset consists of 9 separate items: 1. Forest Change (raster dataset) 2. Forest Type Change (raster dataset) 3. Functional Pathway Change (raster dataset) 4. 1957 Habitat Map (raster dataset) 5. 1980 Habitat Map (raster dataset) 6. 2015 Habitat Map (raster dataset) 7. 1980 Species Map (raster dataset) 8. 2015 Species Map (raster dataset) 9. Wetland Change (raster dataset) These data support...
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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 digital terrain model represents historical elevations along the valley of the North Fork Toutle River upstream of its confluence with the Green River in Cowlitz and Skamania Counties, Washington. Most elevations were derived from U.S. Geological Survey 1:62,500 scale topographic quadrangle maps published from 1953 to 1958 that were derived from aerial photographs taken in 1951 and 1952. Elevations representing the bed of Spirit Lake, at the head of the valley, were derived from a bathymetric map based on survey data from 1974. Elevations are in units of meters and have been adjusted to the North American Vertical Datum of 1988.
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Jonathan Davis Wetland Restoration (BA-20) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Lake Hermitage Marsh Creation (BA-0042) project for 2016. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Black Bayou Hydrologic Restoration (CS-27) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their...
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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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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 Monticello 30 x 60 minute quadrangle in New York and covers part of the Delaware River Basin. The source data used to construct this imagery consists of 1-meter and 2-meter resolution Lidar-derived digital elevation models (DEM). The Lidar source data were compiled from different acquisitions published between 2005 and 2019 from New York state. The data were processed using geographic information systems (GIS) software. The data is projected in North America Datum (NAD) UTM Zone 18 North. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief according to a topographic position index...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Pittsburgh East 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 2020 and 2021 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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This imagery dataset consists of 3 meter resolution, Lidar-derived imagery of the Winchester 30 x 60 minute quadrangle in northern Virginia, West Virginia, and western Maryland. The source data used to construct this imagery consists of 1 meter resolution lidar-derived digital elevation models (DEM). The lidar source data were compiled from different acquisitions published between 2011 and 2019. The data were processed using geographic information systems (GIS) software. The data is projected in North America Datum (NAD) UTM Zone 17 North. 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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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Northwest Turtle Bay Marsh Creation) project for 2021. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their project...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Reading 30 x 60 minute quadrangle in Pennsylvania and parts New Jersey. It also covers part of the Delaware River Basin. The source data used to construct this imagery consists 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...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Johnstown 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 in 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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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Lewisburg 30 x 60 minute quadrangle in Virginia and West Virginia. 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 2020 and 2021. 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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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...


map background search result map search result map Historical Time-series Classification of Habitat for 1957, 1980 and 2015 in the Nisqually River Delta, Washington DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2010–2011 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2010 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2012 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2010–2011 Lake Hermitage Marsh Creation (BA-0042): 2016 land-water classification DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Monomoy Island, MA, 2013-2014 Jonathan Davis Wetland Restoration (BA-20): 2018 land-water classification Using Targeted Training Data to Develop Site Potential for the Upper Colorado River Basin from 2000 - 2018 Enhanced Terrain Imagery of the Winchester 30 x 60 Minute Quadrangle from Lidar-derived Elevation Models at 3 Meter Resolution Enhanced Terrain Imagery of the Monticello 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Naomi Outfall Management (BA-0003c), Barataria Bay Waterway East Side Shoreline Protection (BA-0026), and Naomi Freshwater Diversion (BA-0003): 2018 land-water classification Enhanced Terrain Imagery of the Reading 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Black Bayou Hydrologic Restoration (CS-27): 2018 land-water classification West Lake Boudreaux Shoreline Protection and Marsh Creation (TE-46): 2021 land-water classification Digital terrain model of upper North Fork Toutle River valley, Washington, derived from historical topographic maps Enhanced Terrain Imagery of the Johnstown 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Pittsburgh East 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Lewisburg 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Northwest Turtle Bay Marsh Creation (BA-0125): 2021 land-water classification West Lake Boudreaux Shoreline Protection and Marsh Creation (TE-46): 2021 land-water classification Northwest Turtle Bay Marsh Creation (BA-0125): 2021 land-water classification Lake Hermitage Marsh Creation (BA-0042): 2016 land-water classification Jonathan Davis Wetland Restoration (BA-20): 2018 land-water classification Black Bayou Hydrologic Restoration (CS-27): 2018 land-water classification DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2010 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2012 Digital terrain model of upper North Fork Toutle River valley, Washington, derived from historical topographic maps Enhanced Terrain Imagery of the Pittsburgh East 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Johnstown 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Lewisburg 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Reading 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Monticello 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Enhanced Terrain Imagery of the Winchester 30 x 60 Minute Quadrangle from Lidar-derived Elevation Models at 3 Meter Resolution Historical Time-series Classification of Habitat for 1957, 1980 and 2015 in the Nisqually River Delta, Washington Using Targeted Training Data to Develop Site Potential for the Upper Colorado River Basin from 2000 - 2018