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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 digital elevation model provides a tool for calibrating tsunami risk to observations of the 1945 Makran tsunami in Karachi Harbour. The DEM bathymetry is derived from soundings made mainly during the first eight years after the tsunami. Although deficient in portraying intertidal backwaters and upland topography, the DEM accurately depicts the sheltered setting of one of the two tide gauges that recorded the 1945 tsunami.
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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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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 Freshwater Introduction South of Highway 82 (ME-16) 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...
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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 Oyster Bayou Marsh Creation and Terracing (CS-59) 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...
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This data set consists of digital data describing wetlands and uplands habitats for the Mississippi Coastal Improvements Program (MsCIP) area, consisting of Cat, Ship, Horn and Petit Bois Islands for the year 2020. Wetlands were classified using the Cowardin, et al., wetlands classification scheme to the level of freshwater and tidal, salinity modifiers. Uplands were classified using a customized classification scheme which can be cross-referenced to Anderson, et. al. For this dataset, upland dunes were delineated as areas at or above 1.524 meters (5 feet) as determined in the Lidar data that was referenced without modification for this classification. With this elevation criteria some delineated upland dune features...
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The Mississippi Coastal Improvements Program (MsCIP) has developed a Comprehensive Barrier Island Restoration Plan containing options to ensure the integrity of the Mississippi barrier islands through restoration efforts. Any restoration activities implemented must have minimal adverse impacts to critical habitat for various marine, terrestrial and avian resources. Documenting the success of restoration activities in meeting this requirement requires habitat monitoring. In recent communications with MsCIP personnel, the MsCIP lacks a remotely sensed component to its habitat monitoring plan. Additionally, MsCIP personnel have expressed a need for data pertaining to critical habitat utilized by species of interest...
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The Louisiana State Legislature created 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 Highway 384 Hydrologic Restoration (CS-21) project for 2015. 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 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 East Sabine Lake Hydrologic Restoration (CS-32) project for 2015. 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 Bayou Dupont Marsh and Ridge Creation (BA-48) 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...
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This data set contains shoreline rate of change statistics for New York State coastal wetlands. Analysis was performed using the Digital Shoreline Analysis System (DSAS), created by U.S. Geological Survey, version 5.0, an extension for ArcMap. A reference baseline was used as the originating point for orthogonal transects cast by the DSAS software. The transects intersect each polyline vector shoreline establishing intersection measurement points, which were then used to calculate the rates of change. End-point rates, calculated by dividing the distance of shoreline movement by the time elapsed between the oldest and the most recent shoreline, were generated for wetlands where fewer than three historic shorelines...
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In cooperation with the South Carolina Department of Transportation (SCDOT), the U.S. Geological Survey prepared geospatial layers illustrating the boundaries of the regions used in the South Carolina (SC) Stream Hydrograph Methods presented in Bohman (1990,1992). The region limits were described in written text and depicted in figures in Bohman (1990, 1992), but have not been provided as geospatial layers (due to the age of the original publications). This project used best-available geospatial data from the U.S. Environmental Protection Agency (USEPA) ecoregions (2013) to create equivalent geospatial representations of the Bohman (1990, 1992) region boundaries for the SC Stream Hydrograph Methods. These layers...
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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 documents results from 1,041 groundwater samples collected during 1986‒2015 from 16 geologic units in Pennsylvania associated with 25 or more groundwater samples with activities or concentrations of radon-222. Radon-222 is hereafter referred to as “radon.” These 16 geologic units were evaluated in an effort to identify variations in radon concentrations and to classify potential radon exposure from groundwater and indoor air. This dataset was developed for the Pennsylvania Environmental Public Health Tracking (PAEPHT) Program to describe the spatial distribution of radon concentrations in groundwater in Pennsylvania and to illustrate data gaps that exist throughout the State. The PAEPHT Program is part...
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Introduction In 2012, Hurricane Sandy created an open breach in the barrier island system along the south shore of Long Island, N.Y. This breach formed at a location known as Old Inlet and migrated rapidly westward over the winter storm season following Hurricane Sandy. In response, the National Park Service sought assistance from the USGS New York Water Science Center to help evaluate the hydrodynamics and geomorphology of the breach. The evaluation is centered on measurement of water velocities and depths within the breach, and collection of water levels with the Great South Bay adjacent to the breach. This project is part of a larger ongoing study prepared in coordination with the National Park Service...
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Unvegetated to vegetated marsh ratio (UVVR) in the Fire Island National Seashore and Central Great South Bay salt marsh complex, is computed based on conceptual marsh units defined by Defne and Ganju (2018). UVVR was calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 1-meter resolution imagery. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands, including the Fire Island National Seashore and Central Great South Bay salt marshes, with the intent of providing Federal, State, and local managers with tools to estimate...
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The study area for this Rapid Ecoregional Assessment (REA) includes three ecoregions, as defined by Unified Ecoregions of Alaska (Nowacki et al. 2001): the Yukon River Lowlands, Kuskokwim Mountains, and Lime Hills. The borders of these ecoregions are buffered to include adjacent 5th level HUCs to ensure that this REA is contiguous with other REA efforts in Alaska. Four additional 5th level hydrologic units were included in the study area to close two gaps in the boundary. This was agreed to by the BLM to facilitate seamless integration with neighboring REA efforts and to ensure that regionally important resources that may exist just outside of the ecoregion boundaries are included in the analysis.


map background search result map search result map PaRadonGW.shp - Evaluation of Radon Occurrence in Groundwater from 16 Geologic Units in Pennsylvania, 1986–2015, with Application to Potential Radon Exposure from Groundwater and Indoor Air Bathymetric and Tidal Discharge data for Wilderness Breach, Fire Island National Seashore, Long Island, NY, May 14, 2015 Rate of shoreline change statistics for New York State coastal wetlands Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour Highway 384 Hydrologic Restoration (CS-21): 2015 land-water classification Unvegetated to vegetated marsh ratio in Fire Island National Seashore and Central Great South Bay salt marsh complex, New York Bayou Dupont Marsh and Ridge Creation (BA-48): 2016 land-water classification East Sabine Lake Hydrologic Restoration (CS-32): 2015 land-water classification DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2013–2014 BLM REA YKL 2011 Study Area Boundary for the Yukon River Lowlands - Kuskokwim Mountains - Lime Hills Rapid Ecoregional Assessment DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Myrtle Island, VA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Wreck Island, VA, 2014 December 2018 National Wetlands Inventory Mississippi Barrier Islands habitat classification: (Cat Island, Ship Island, Petit Bois Island and Horn Island) Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Oyster Bayou Marsh Creation and Terracing (CS-59): 2018 land-water classification February 2020 National Wetlands Inventory, Mississippi Barrier Islands Habitat Classification: (Cat Island, Ship Island, Petit Bois Island and Horn Island) Region Layers for USGS South Carolina Bohman Method Hydrograph in StreamStats Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Bathymetric and Tidal Discharge data for Wilderness Breach, Fire Island National Seashore, Long Island, NY, May 14, 2015 Bayou Dupont Marsh and Ridge Creation (BA-48): 2016 land-water classification Oyster Bayou Marsh Creation and Terracing (CS-59): 2018 land-water classification DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Wreck Island, VA, 2014 Highway 384 Hydrologic Restoration (CS-21): 2015 land-water classification DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Myrtle Island, VA, 2014 DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013 DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014 Bathymetric and topographic grid intended for simulations of the 1945 Makran tsunami in Karachi Harbour East Sabine Lake Hydrologic Restoration (CS-32): 2015 land-water classification Freshwater Introduction South of Highway 82 (ME-16): 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, 2013–2014 Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Rate of shoreline change statistics for New York State coastal wetlands PaRadonGW.shp - Evaluation of Radon Occurrence in Groundwater from 16 Geologic Units in Pennsylvania, 1986–2015, with Application to Potential Radon Exposure from Groundwater and Indoor Air Region Layers for USGS South Carolina Bohman Method Hydrograph in StreamStats BLM REA YKL 2011 Study Area Boundary for the Yukon River Lowlands - Kuskokwim Mountains - Lime Hills Rapid Ecoregional Assessment