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Data includes satellite derived pre-fire functional group cover of annual and perennial herbaceous, shrubs, bareground and litter across four rangeland megafires in the Western US, as well as field estimated invasive annual grass measurements from the 2nd to 3rd years post-fire. Additional landscape and restoration treatment covariates hypothesized to influence post-fire invasive annual grass cover are included.
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This dataset is a file of contour lines representing the estimated altitude of the water table in western Sarpy County. This dataset was developed as part of a cooperative study between the Papillion-Missouri River Natural Resources District (PMRNRD) and USGS which began in 2017. The goal of this study was to develop a hydrogeologic visualization model of western Sarpy County using GeoScene3D. In 2016, the PMRNRD contracted airborne electromagnetic surveys (AEM) of the area to be completed to better understand the stratigraphy and hydrogeology of the western Sarpy County area. The PMRNRD determined that they wanted to incorporate the AEM data into a visualization tool that would allow PMRNRD staff to easily interact...
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LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
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LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
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LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
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Using publicly available data for Albany and Schenectady counties, New York, a series of geospatial overlays were created at 1:24,000 scale to examine the bedrock geology, groundwater table, soils, and surficial geology. Bedrock and surficial geology were refined using extant bedrock maps, well and borehole data from water- and gas-wells, soil data, and lidar data. Groundwater data were collected from New York State Department of Environmental Conservation and U.S. Geological Survey water-well databases to estimate the groundwater table. Soil data were used to examine soil thickness over bedrock and infiltration. An inventory of closed depressions was created using reconditioned lidar-derived bare-earth digital...
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Using publicly available data for Erie and Niagara counties, New York, a series of geospatial overlays were created at 1:24,000 scale to examine the bedrock geology, groundwater table, soils, and surficial geology. Bedrock and surficial geology were refined using extant bedrock maps, well and borehole data from water- and gas-wells, soil data, and lidar data. Groundwater data were collected from New York State Department of Environmental Conservation and U.S. Geological Survey water-well databases to estimate the groundwater table. Soil data were used to examine soil thickness over bedrock and infiltration. An inventory of closed depressions was created using reconditioned lidar-derived bare-earth digital elevation...
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The Colorado Plateau structural province features long monoclinal flexures between uplifts and basins that are the major lines of deformation within and marginal to the Plateau. These folds are named, well-known, and have been described as part of several previous tectonic syntheses of the Colorado Plateau (Kelley, 1955; Davis, 1978; 1999). However, no digital data have ever been created that locate these folds in digital map space. This digital dataset compiles mapped locations of monoclinal folds from several geologic maps from the Colorado Plateau, most released only in “paper”, non-vector format. Fold names and their general map trace were guided by regional-scale maps that synthesize the tectonic elements of...
This data release documents proposed updates to geologic inputs (faults) for the upcoming 2023 National Seismic Hazard Model (NSHM). This version (1.0) conveys differences between 2014 NSHM fault sources and those recently released in the earthquake geology inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 data release by Hatem et al. (2021). A notable difference between the 2014 and 2023 datasets is that slip rates are provided at points for 2023 instead of generalized along the entire fault section length as in 2014; consequently, slip rates are not provided for fault sections in the draft 2023 dataset. Geospatial data (shapefile, kml and geojson) are provided in this data release with...
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Time series data of water surface elevation and wave height were acquired at ten locations for 517 days (in three separate deployments) off the north coast of Roi-Namur Island, Kwajalein Atoll, Marshall Islands, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reefs were as follows: ROI13W1 and ROI13E1 – fore reef ROI13W2 and ROI13E2 – outer reef flat ROI13W1 and ROI13E1 – middle reef flat ROI13W1 and ROI13E1 – inner reef flat
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These data are estimates of den emergence date, den site departure dates, and duration at den sites as well as post-emergence observations for female polar bears sampled in the southern Beaufort Sea subpopulation 1985-2016 and the Chukchi Sea subpopulation 2008-2017. The data were used to better understand the importance of time spent at the den site post-emergence. Emergence dates and departure dates were determined using collar temperature sensor data.
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The Murderer’s Creek mule deer herd winters south of U.S. Route 26 in river valleys near Canyon Creek, Murderer’s Creek, and the South Fork John Day River. The herd’s winter ranges are characterized by western juniper, big sagebrush, and Columbia Basin grassland communities, with medusahead and other non-native grasses invading lower elevations. In the spring, mule deer mainly migrate southeast to summer ranges distributed throughout Gilbert Ridge and the Aldrich Mountains, some traveling as far south as Devon Ridge and east to Ironside Mountain. Summer ranges in these areas contain mixed-conifer forests, ponderosa pine, and low sagebrush communities. A smaller portion of this herd migrates northeast in the spring,...
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This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. These data represent the flowline network in the Green Bay Restoration Assessment (GBRA). It is attributed with the number of disconnections (e.g., road crossings) between the reach and Lake Ontario. The more road crossings on a flowline the more disconnected that area is from the lake and the less suitable it will be for restoration. These data help identify the condition of hydrologic separation between potential restoration areas and Lake Ontario. Low numbers represent fewer disconnections, such as culverts, between the reach and the water body requiring no flow network modification...
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The Trout Creek mule deer herd is composed of residents and migrants that make short-range elevational migrations. Mule deer mainly winter at lower elevations surrounding Blue Mountain and the slopes of the Oregon Canyon Mountains. In spring, some of these mule deer migrate to higher elevations in the Oregon Canyon Mountains. Other members of the herd winter in the southwestern portion of the herd’s range, inhabiting areas near Hawks Mountain, the Pueblo Mountains, and the foothills of the Trout Creek Mountains. These mule deer migrate to summer ranges on the crests of Holloway Mountain and the Trout Creek Mountains. Notably, one mule deer formerly wintering on the Trout Creek Mountains migrated south from a summer...
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The Trout Creek mule deer herd is composed of residents and migrants that make short-range elevational migrations. Mule deer mainly winter at lower elevations surrounding Blue Mountain and the slopes of the Oregon Canyon Mountains. In spring, some of these mule deer migrate to higher elevations in the Oregon Canyon Mountains. Other members of the herd winter in the southwestern portion of the herd’s range, inhabiting areas near Hawks Mountain, the Pueblo Mountains, and the foothills of the Trout Creek Mountains. These mule deer migrate to summer ranges on the crests of Holloway Mountain and the Trout Creek Mountains. Notably, one mule deer formerly wintering on the Trout Creek Mountains migrated south from a summer...
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These data were compiled to provide a resource for other researchers interested in water-surface elevations and flow velocity across a wide range of discharge in the study reach for the project. Objective(s) of our study were to construct a two-dimensional hydrodynamic model for the 15.8 mile tailwater reach of the Colorado River in Glen Canyon between Glen Canyon Dam and Lees Ferry, Arizona. These data represent the results of the two-dimensional modeling effort with each data table (50) including the results of each run of the model. Additionally, other data represent a comparison of modeled water surface elevations to measured water surface elevations for historic Bureau of Reclamation cross sections in the study...
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South of Interstate 40 elk reside primarily in Arizona’s Game Management Unit (GMU) 8. Upon completing population surveys in 2021, approximately 4,000 elk were estimated to inhabit GMU 8. Their summer range is primarily characterized by high-elevation ponderosa pine forests and grasslands. The elk radiate out from various origin points within their summer range to their winter range, comprised of rims of canyons in the area, including Sycamore Canyon, Tule Canyon, and Government Canyon. This series of canyons creates an impermeable southern boundary for this herd. Their winter range along the rim country is primarily characterized by pinyon-juniper, manzanita, and scrub oak. Interstate 40 is the primary threat to...
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These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
Tags: Arizona, Botany, Cloud Optimized GeoTIFF data, Colorado River, Ecology, All tags...
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This data release links benthic macroinvertebrate sites to both the NHDPlus Version 2 and NHDPlus High Resolution Region 02 networks, hereafter referred to as V2 and HR, using the hydrolink methodology. Linked benthic macroinvertebrate sites are those included in the Chesapeake Bay Basin-wide Index of Biotic Integrity (Chessie BIBI) developed by the Interstate Commission on the Potomac River Basin (ICPRB) and available from the Chesapeake Bay Program (https://datahub.chesapeakebay.net/LivingResources). The data set contains a unique sample identifier created by ICPRB, survey program, coordinates of sample, linked V2 COMID and HR Permanent Identifier, and information regarding uncertainty in the attribution. We strongly...


map background search result map search result map Roi-Namur Island, Marshall Islands, wave and water level data, 2013-2015 Geospatial datasets to assess karst aquifer systems in Albany and Schenectady counties, New York Summary of proposed changes to geologic inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 Geospatial datasets to assess karst aquifer systems in Erie and Niagara counties, New York NOAA’s National Coral Reef Monitoring Program (NCRMP) Coral Demographic Data Interpolated groundwater-levels, western Sarpy County, eastern Nebraska Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Green Bay, U.S.: Degree Flowlines Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA LANDFIRE 2022 Existing Vegetation Cover (EVC) AK Pre-fire satellite derived and field calculated functional cover across Great Basin megafires Attribution of benthic macroinvertebrate sampling data to NHDPlus V2 and NHDPlus HR catchments within the Chesapeake Bay Watershed LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Digital location of monoclines and structural uplifts of the Colorado Plateau, Arizona, Colorado, New Mexico, and Utah Arizona Elk South of Interstate 40 Corridors Oregon Mule Deer Murderer's Creek Winter Ranges Oregon Mule Deer Trout Creek Migration Corridors Oregon Mule Deer Trout Creek Stopovers Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: tables of model results and accuracy assessment Estimated Post-Emergence Period for Denning Polar Bears of the Chukchi and Beaufort Seas Roi-Namur Island, Marshall Islands, wave and water level data, 2013-2015 Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA Hydrodynamic model of the Colorado River, Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: tables of model results and accuracy assessment Interpolated groundwater-levels, western Sarpy County, eastern Nebraska Geospatial datasets to assess karst aquifer systems in Albany and Schenectady counties, New York Oregon Mule Deer Trout Creek Stopovers Oregon Mule Deer Trout Creek Migration Corridors Oregon Mule Deer Murderer's Creek Winter Ranges Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Green Bay, U.S.: Degree Flowlines Pre-fire satellite derived and field calculated functional cover across Great Basin megafires LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Attribution of benthic macroinvertebrate sampling data to NHDPlus V2 and NHDPlus HR catchments within the Chesapeake Bay Watershed Digital location of monoclines and structural uplifts of the Colorado Plateau, Arizona, Colorado, New Mexico, and Utah NOAA’s National Coral Reef Monitoring Program (NCRMP) Coral Demographic Data Summary of proposed changes to geologic inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 LANDFIRE 2022 Existing Vegetation Cover (EVC) AK Estimated Post-Emergence Period for Denning Polar Bears of the Chukchi and Beaufort Seas