Skip to main content
Advanced Search

Filters: Tags: Geospatial Analysis (X)

808 results (24ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
These data identify the time (0-1 min, 1-2 min,or 2-3 min) and distance (≤50 meters, >50 meters) category when birds were first detected during 3-minutes point counts at stop locations associated with North American Breeding Bird Survey routes or route equivalents that were surveyed on dates between 2009 and 2016 and provide point location coordinates of stop locations along North American Breeding Bird Survey routes or route equivalents within (or within 60 miles) the Gulf Coastal Plains & Ozarks Landscape Conservation Cooperative boundary.
thumbnail
The High Plains aquifer extends from approximately 32 to 44 degrees north latitude and 96 degrees 30 minutes to 106 degrees west longitude. The aquifer underlies about 175,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital dataset consists of a raster of water-level changes for the High Plains aquifer, predevelopment (about 1950) to 2019. It was created using water-level measurements from 2,741 wells measured in both the predevelopment period (about 1950) and in 2019, the latest available static water level measured in 2015 to 2018 from 71 wells in New Mexico and using other published information on water-level change in areas with few water-level...
thumbnail
These data include 217 median groundwater elevations computed from compiled measurements made in the year 2010 within the transboundary Mesilla/Conejos-Médanos Basin, United States and Mexico, along with their corresponding interpolated groundwater elevations and standard errors from the application of kriging. Of the 217 median groundwater elevation locations, 109 were in the United States and 108 were in Mexico. Considered measurements were limited to wells thought to be completed in the basin-fill/Santa Fe Group aquifer based on well records. This dataset includes a comma-separated values file (Control_points.csv) that provides the median groundwater elevations that were kriged to yield rasters of estimated groundwater...
thumbnail
Digital flood-inundation maps for a 3.4-mile reach of Fourmile Creek at Silver Grove, Kentucky (Ky.), were created by the U.S. Geological Survey (USGS) in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District. Because the City of Silver Grove is subject to flooding from Fourmile Creek and the Ohio River (backwater flooding up Fourmile Creek), a set of flood-inundation maps was created for each flooding source independently and for combinations of possible flooding scenarios. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of different gage heights (gage height is commonly referred to as “stage,” or the water-surface...
thumbnail
This dataset contains a thematic [classified] image derived from supervised classification of WorldView-3 satellite imagery. This data release contains a geospatial thematic (raster) image derived from a supervised classification of WorldView-3 satellite imagery obtained during 2020–21. Arundo donax (Arundo cane, giant reed, or Carrizo cane), is an invasive bamboo-like perennial grass most common to riparian areas throughout the southwestern United States. Because it displaces native riparian vegetation, Arundo cane has greatly disrupted the health of riparian ecosystems in the southwestern United States and northern Mexico during the past 50 years. Arundo cane also has created border security problems along the...
thumbnail
This dataset contains a thematic [classified] image derived from supervised classification of WorldView-3 satellite imagery. This data release contains a geospatial thematic (raster) image derived from a supervised classification of WorldView-3 satellite imagery obtained during 2020–21. Arundo donax (Arundo cane, giant reed, or Carrizo cane), is an invasive bamboo-like perennial grass most common to riparian areas throughout the southwestern United States. Because it displaces native riparian vegetation, Arundo cane has greatly disrupted the health of riparian ecosystems in the southwestern United States and northern Mexico during the past 50 years. Arundo cane also has created border security problems along the...
Well-established conservation planning principles and techniques framed by geodesign were used to assess the restorability of areas that historically supported coastal wetlands along the U.S. shore of Saginaw Bay. The resulting analysis supported planning efforts to identify, prioritize, and track wetland restoration opportunity and investment in the region. To accomplish this, publicly available data, criteria derived from the regional managers and local stakeholders, and geospatial analysis were used to form an ecological model for spatial prioritization.
thumbnail
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the National Hydrography Dataset (NHD), National Watershed Boundary Dataset (WBD), and 3D Elevation Program Digital Elevation Model (3DEP DEM). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to a data suite that includes the NHD stream network with linear referencing functionality, the WBD hydrologic units, elevation-derived catchment areas for each stream segment, "value added attributes" (VAAs), and other features that enhance hydrologic data analysis and routing.
Tags: 4-digit hydrologic unit, Addison County, Bennington County, Berkshire County, CT, All tags...
thumbnail
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the best available National Hydrography Dataset (NHD), the 10-meter 3D Elevation Program Digital Elevation Model (3DEP DEM), and the National Watershed Boundary Dataset (WBD). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to create a stream network with linear referencing, feature naming, "value added attributes" (VAAs), elevation-derived catchments, and other features for hydrologic data analysis. The stream network with linear referencing is a system of data relationships applied to hydrographic systems so that one stream reach "flows" into another and "events" can be tied to and traced...
Tags: AK, Alaska, Anchorage County, Downloadable Data, FileGDB, All tags...
thumbnail
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the National Hydrography Dataset (NHD), National Watershed Boundary Dataset (WBD), and 3D Elevation Program Digital Elevation Model (3DEP DEM). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to a data suite that includes the NHD stream network with linear referencing functionality, the WBD hydrologic units, elevation-derived catchment areas for each stream segment, "value added attributes" (VAAs), and other features that enhance hydrologic data analysis and routing.
Tags: Belknap, Carroll, Cheshire, Downloadable Data, Esri File GeoDatabase 10, All tags...
thumbnail
The High Resolution National Hydrography Dataset Plus (NHDPlus HR) is an integrated set of geospatial data layers, including the best available National Hydrography Dataset (NHD), the 10-meter 3D Elevation Program Digital Elevation Model (3DEP DEM), and the National Watershed Boundary Dataset (WBD). The NHDPlus HR combines the NHD, 3DEP DEMs, and WBD to create a stream network with linear referencing, feature naming, "value added attributes" (VAAs), elevation-derived catchments, and other features for hydrologic data analysis. The stream network with linear referencing is a system of data relationships applied to hydrographic systems so that one stream reach "flows" into another and "events" can be tied to and traced...
Tags: CharlotteCounty, CitrusCounty, DeSotoCounty, Downloadable Data, FL, All tags...


map background search result map search result map USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for 8-digit Hydrologic 19020401 (published 20180814) SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013 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 DisOcean: Distance to the ocean: 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): Edwin B. Forsythe NWR, NJ, 2013–2014 DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2014 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012 USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 4 - 0107 (published 20230713) FileGDB USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 4 - 0108 (published 20220324) FileGDB USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for 4-digit Hydrologic Unit - 0310 (published 20180501) Time and Distance of Detection and Stop Locations along North American Breeding Bird Survey routes within the Gulf Coastal Plains & Ozarks Landscape Conservation Cooperative. Estimated groundwater elevations and standard errors from the application of kriging to median groundwater elevation data from 2010 in the Mesilla/Conejos-Médanos Basin, United States and Mexico Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami elevation model of Half Moon Bay, California Shapefiles of the flood-inundation maps (combined flooding scenarios) for Fourmile Creek at Silver Grove, Kentucky Arundo donax (Arundo Cane) Image Classification along the Rio Grande in Webb County, Texas, September 26, 2020 Arundo donax (Arundo Cane) Image Classification along the Rio Grande in Webb County, Texas, May 07, 2021 F01_hpwicpd19t_Raster dataset of mapped water-level changes in the High Plains aquifer, predevelopment (about 1950) to 2019 Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami elevation model of Half Moon Bay, California Shapefiles of the flood-inundation maps (combined flooding scenarios) for Fourmile Creek at Silver Grove, Kentucky SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013 Arundo donax (Arundo Cane) Image Classification along the Rio Grande in Webb County, Texas, September 26, 2020 Arundo donax (Arundo Cane) Image Classification along the Rio Grande in Webb County, Texas, May 07, 2021 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011 DisOcean: Distance to the ocean: 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): Edwin B. Forsythe NWR, NJ, 2013–2014 DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2014 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 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for 8-digit Hydrologic 19020401 (published 20180814) Estimated groundwater elevations and standard errors from the application of kriging to median groundwater elevation data from 2010 in the Mesilla/Conejos-Médanos Basin, United States and Mexico USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 4 - 0107 (published 20230713) FileGDB USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for 4-digit Hydrologic Unit - 0310 (published 20180501) USGS National Hydrography Dataset Plus High Resolution (NHDPlus HR) for Hydrological Unit (HU) 4 - 0108 (published 20220324) FileGDB F01_hpwicpd19t_Raster dataset of mapped water-level changes in the High Plains aquifer, predevelopment (about 1950) to 2019 Time and Distance of Detection and Stop Locations along North American Breeding Bird Survey routes within the Gulf Coastal Plains & Ozarks Landscape Conservation Cooperative.