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The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes...
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Climate grids for the extent of the GNLCC study area saved as asciis with a 2km resolution. These grids are saved in in the Albers Equal Area Conic projection. Summer is defined as months 7-9, while winter is defined as months 1-3. All grids with the exception of cmi.asc, dd5.asc, & growingsl.asc were produced in the program ClimateWNA, which downscales PRISM climate grids using a digital elevation model. Mean annual precipitation (mm) - aprec.asc Annual Climate moisture index (cm/year) - cmi.asc Degree-days > 5°C - dd5.asc Growing season length - growingsl.asc Isothermality (°C) - isotherm.asc Mean annual temperature (°C) - mat.asc Maximum temperature warmest month (°C) - maxtw.asc Minimum temperature coldest...
From May 2017 to November 2019, the U.S. Geological Survey conducted bathymetric surveys of New York City's East of Hudson Reservoirs. Bathymetry data were collected at Kirk Lake during June 2017. Depth data were collected primarily with a multibeam echosounder. Quality assurance points were measured with a single-beam echosounder. Water surface elevations were established using real-time kinematic (RTK) and static global navigation satellite system (GNSS) surveys and submersible pressure transducers. Measured sound velocity profiles were used to correct echosounder depth measurements for thermal stratification. Digital elevation models were created by combining the measured bathymetry data with lidar elevation...
From May 2017 to November 2019, the U.S. Geological Survey conducted bathymetric surveys of New York City's East of Hudson Reservoirs. Bathymetry data were collected at Lake Gleneida during May 2017. Depth data were collected primarily with a multibeam echosounder. Quality assurance points were measured with a single-beam echosounder. Water surface elevations were established using real-time kinematic (RTK) and static global navigation satellite system (GNSS) surveys and submersible pressure transducers. Measured sound velocity profiles were used to correct echosounder depth measurements for thermal stratification. Digital elevation models were created by combining the measured bathymetry data with lidar elevation...
Static flood inundation boundary extents were created along the entire shoreline of Lake Ontario in Cayuga, Jefferson, Monroe, Niagara, Orleans, Oswego, and Wayne Counties in New York by using recently acquired (2007, 2010, 2014, and 2017) light detection and ranging (lidar) data. The flood inundation maps, accessible through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and water depth of shoreline flooding in 8 segments corresponding to adjacent water-surface elevations (stages) at 8 USGS lake gages on Lake Ontario. This item includes data sets for segment B - Lake Ontario...
Static flood inundation boundary extents were created along the entire shoreline of Lake Ontario in Cayuga, Jefferson, Monroe, Niagara, Orleans, Oswego, and Wayne Counties in New York by using recently acquired (2007, 2010, 2014, and 2017) light detection and ranging (lidar) data. The flood inundation maps, accessible through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and water depth of shoreline flooding in 8 segments corresponding to adjacent water-surface elevations (stages) at 8 USGS lake gages on Lake Ontario. This item includes data sets for segment G - Lake Ontario...
Aerial images in the vicinity of USGS gaging station #07094500 Arkansas River at Parkdale, Colorado were collected on March 20-22, 2018, using Unmanned Aircraft Systems (UAS, or "drones"). Data were processed using structure-from-motion analysis to generate a three-dimensional point cloud that identifies pixels from multiple images representing the same object and calculates the x, y, and z coordinates of that object/pixel. The point cloud was processed to create a digital surface model of the site. Finally, source images were stitched together based on shared pixels and orthogonally adjusted to create a high resolution (approximately 2 cm pixel size) orthoimage for the study area. The orthomosaic image captures...
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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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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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMHRP, Coastal Erosion, All tags...
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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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMGP, Coastal Erosion, All tags...
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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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMHRP, Cape Cod, All tags...
From May 2017 to November 2019, the U.S. Geological Survey conducted bathymetric surveys of New York City's East of Hudson Reservoirs. Bathymetry data were collected at Middle Branch Reservoir during July and August, 2017. Depth data were collected primarily with a multibeam echosounder. Quality assurance points were measured with a single-beam echosounder. Water surface elevations were established using real-time kinematic (RTK) and static global navigation satellite system (GNSS) surveys and submersible pressure transducers. Measured sound velocity profiles were used to correct echosounder depth measurements for thermal stratification. Digital elevation models were created by combining the measured bathymetry...
From May 2017 to November 2019, the U.S. Geological Survey conducted bathymetric surveys of New York City's East of Hudson Reservoirs. Bathymetry data were collected at West Branch Reservoir during September 2017, October 2017, and October 2019. Depth data were collected primarily with a multibeam echosounder; additional bathymetry points were measured using an acoustic Doppler current profiler (ADCP). Quality assurance points were measured with a single-beam echosounder. Water surface elevations were established using real-time kinematic (RTK) and static global navigation satellite system (GNSS) surveys and submersible pressure transducers. Measured sound velocity profiles were used to correct echosounder depth...
From May 2017 to November 2019, the U.S. Geological Survey conducted bathymetric surveys of New York City's East of Hudson Reservoirs. Bathymetry data were collected at Boyd Corners Reservoir during September 2017. Depth data were collected primarily with a multibeam echosounder. Quality assurance points were measured with a single-beam echosounder. Water surface elevations were established using real-time kinematic (RTK) and static global navigation satellite system (GNSS) surveys and submersible pressure transducers. Measured sound velocity profiles were used to correct echosounder depth measurements for thermal stratification. Digital elevation models were created by combining the measured bathymetry data with...
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Live tree species basal area from 2000 - 2009 for loblolly pine (Pinus taeda), longleaf pine (Pinus palustris), shortleaf pine (Pinus echinata), and slash pine (Pinus elliottii) clipped to the Gulf Coastal Plains and Ozarks LCC geography.Data were derived from the USFS live tree species basal area of the contiguious United States (2000-2009) Wilson, Barry T.; Lister, Andrew J.; Riemann, Rachel I.; Griffith, Douglas M. 2013. Live tree species basal area of the contiguous United States (2000-2009). Newtown Square, PA: USDA Forest Service, Northern Research Station. Abstract from html metadata for USFS live tree species basal area of the contiguious United States (2000-2009). This data product contains raster maps...
Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service, Raster; Tags: BIOSPHERE, BIOSPHERE, Basal Area, Conservation planning, Data, All tags...
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The Arizona Game and Fish Department (AGFD) recognizes the need for a strong data foundation to inform science-based decisions for fisheries management at a watershed level. In preparation for a shift towards comprehensive watershed-scale planning, AGFD is developing a fisheries data management system with an initial focus on compiling and formatting several hundred thousand fish survey and stocking records. Fish data will be integrated within a Geographic Information System (GIS) by georeferencing observations to an existing national spatial framework (National Hydrography Dataset), which will allow for broader transferability to watersheds shared with neighboring states, creating a seamless layer not limited by...
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This publication provides digital flight line data for a high-resolution magnetic and radiometric survey over an area of southeast Illinois, western Kentucky, and southern Indiana. The survey includes airborne geophysical data collected as part of the U.S. Geological Survey (USGS) Earth Mapping Resource Initiative (Earth MRI) effort (Day, 2019). Earth MRI is a cooperative effort between the USGS, the Association of American State Geologists, and other Federal, State, and private sector organizations to improve our knowledge of the geologic framework of the United States. Data for this survey were collected by EON Geosciences under contract with the USGS using a fixed wing aircraft with a magnetometer mounted in...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service, Raster; Tags: AASG, Association of American State Geologists, Ballard County, Caldwell County, Carlisle County, All tags...
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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...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMHRP, Coastal Erosion, All tags...
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Summary This data release contains postprocessed model output from a simulation of hypothetical rapid motion of landslides, subsequent wave generation, and wave propagation. A simulated displacement wave was generated by rapid motion of unstable material into Barry Arm fjord. We consider the wave propagation in Harriman Fjord and Barry Arm, western Prince William Sound (area of interest and place names depicted in Figure 1). We consider only the largest wave-generating scenario presented by Barnhart and others (2021a, 2021b). As in Barnhart and others (2021c), we used a simulation setup similar to Barnhart and others (2021a, 2021b), but our results differ because we used different topography and bathymetry datasets....
map background search result map search result map A Landscape Approach for Fisheries Database Compilation and Predictive Modeling (Not listed in the LCC Science Catalog due to Desert LCC co-funding and catalog administering) TIGER/Line Shapefile, 2013, county, Lemhi County, ID, All Roads County-based Shapefile Great northern landscape conservation cooperative climate grids Live Pine Tree Species Basal Area (2000 -2009) in the GCPO LCC (Loblolly, Longleaf, Shortleaf, Slash) points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore 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 Hicks Dome Magnetic Data Orthorectified Mosaic Photograph of a Portion of the Arkansas River at Parkdale, Colorado, March, 2018 Geospatial bathymetry datasets for Boyd Corners Reservoir, New York, 2017 Geospatial bathymetry datasets for Kirk Lake, New York, 2017 Geospatial bathymetry datasets for Lake Gleneida, New York, 2017 Geospatial bathymetry datasets for Middle Branch Reservoir, New York, 2017 Geospatial bathymetry datasets for West Branch Reservoir, New York, 2017 to 2019 Segment B - Flood inundation map geospatial datasets for Lake Ontario, New York Segment G - Flood inundation map geospatial datasets for Lake Ontario, New York Simulated inundation extent and depth in Harriman Fjord and Barry Arm, western Prince William Sound, Alaska, resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Orthorectified Mosaic Photograph of a Portion of the Arkansas River at Parkdale, Colorado, March, 2018 Geospatial bathymetry datasets for Lake Gleneida, New York, 2017 Geospatial bathymetry datasets for Boyd Corners Reservoir, New York, 2017 Geospatial bathymetry datasets for Kirk Lake, New York, 2017 Geospatial bathymetry datasets for Middle Branch Reservoir, New York, 2017 Geospatial bathymetry datasets for West Branch Reservoir, New York, 2017 to 2019 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 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014 Segment B - Flood inundation map geospatial datasets for Lake Ontario, New York points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 Simulated inundation extent and depth in Harriman Fjord and Barry Arm, western Prince William Sound, Alaska, resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska Segment G - Flood inundation map geospatial datasets for Lake Ontario, New York points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014 Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Hicks Dome Magnetic Data TIGER/Line Shapefile, 2013, county, Lemhi County, ID, All Roads County-based Shapefile Great northern landscape conservation cooperative climate grids A Landscape Approach for Fisheries Database Compilation and Predictive Modeling (Not listed in the LCC Science Catalog due to Desert LCC co-funding and catalog administering) Live Pine Tree Species Basal Area (2000 -2009) in the GCPO LCC (Loblolly, Longleaf, Shortleaf, Slash)