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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.
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...
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...
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...
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...
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...
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...
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...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Arizona,
California,
Colorado,
Idaho,
Nevada,
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
FDEM Methodology For this project frequency domain electromagnetic (FDEM) data were collected with a GEM-2, a broadband, multifrequency, fixed-coil electromagnetic induction unit (Geophex, 2015). Both in-phase and quadrature data were collected on 15 channels from a frequency of 810 Hz to 66,090 Hz. This system was carried along profiles that followed the axis of the dam and along tie lines that were perpendicular to the axis of the dam. Each data point was located using a backpack mounted GPS. To correct the drift of the instrument, a base station was established on the east side of the dam. Each survey started and ended with an occupation of the base station. These occupations occur as even line numbers...
Categories: Data
This data release documents three Microsoft Excel tables (and corresponding comma separated data files) that contain estimates of tritium in precipitation data for the continental United States. Versions of this data release contain additional tritium data for more recent years. The current version has tritium data through 2022. Table 1 contains estimates of tritium in precipitation for precipitation stations located in the continental United States. Measured precipitation data are formatted in regular font while correlated data are italicized. Table 2 contains tritium in precipitation for ninety-six 2-degree latitude by 5-degree longitude quadrangles covering the continental U.S. Latitudes are north of the equator...
Categories: Data,
Data Release - In Progress;
Tags: Tritium,
USGS Science Data Catalog (SDC),
continental United States,
groundwater,
groundwater age,
These data support a paired USGS publication and document the use of retention ponds on commercial poultry farms by wild waterfowl.
Categories: Data;
Tags: Chesapeake Bay,
USGS Science Data Catalog (SDC),
Wildlife Disease,
avian influenza,
biota,
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,...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: John Day,
Oregon,
United States,
animal behavior,
biota,
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...
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...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Fields,
Oregon,
United States,
animal behavior,
biota,
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...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Fields,
Oregon,
United States,
animal behavior,
biota,
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...
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...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Arizona,
Flagstaff,
United States,
animal behavior,
biota,
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...
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