Filters: System Type: Data Release (X) > Categories: NOT Data Release - In Progress (X) > Tags: {"scheme":"Common geographic areas","name":"united states"} (X) > Extensions: Raster (X)
16 results (12ms)
Filters
Date Range
Extensions Types Contacts
Categories Tag Types Tags (with Scheme=Common geographic areas) |
This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
These data depict reptile species richness within the range of the Greater Sage-grouse. Species boundaries were defined as the total extent of a species geographic limits. This raster largely used species range data from "U.S. Geological Survey - Gap Analysis Project Species Range Maps CONUS_2001", however in order for a more complete picture of species richness, additional sources were used for species missing from the Gap Analysis program.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Class Chelonia,
Class Reptilia,
Class Testudines,
These datasets provide early estimates of 2021 fractional cover for exotic annual grass (EAG) species and a native perennial grass predicted on July 1 using satellite observation data available no later than June 28th. Four fractional cover maps comprise this release, along with the corresponding confidence maps, for: 1) a group of 17 species of EAGs (i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus hordeaceus spp. hordeaceus, Bromus japonicus, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus tectorum L., Bromus texensis (Shear) Hitchc.,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
This dataset release provides historical (2016 - 2022) estimates of fractional cover for exotic annual grass (EAG) species and a native perennial bunch grass in the arid and semi-arid rangelands of the western United States. The dataset includes four fractional cover maps per year, accompanied by corresponding confidence maps, for a group of 16 species of EAGs, cheatgrass (Bromus tectorum); medusahead (Taeniatherum caput-medusae); and Sandberg bluegrass (Poa secunda). The data were generated using a combination of field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) plots; remotely sensed data from the Harmonized Landsat and Sentinel-2 (HLS) product (specifically Normalized...
Categories: Data,
Data Release - Revised;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Potentially suitable habitat for the American burying beetle (Nicrophorus americanus) was identified within the Southern Plains. The American burying beetle (ABB) is listed as endangered under the Endangered Species Act, but in 2019 the U.S. Fish and Wildlife Service proposed to reclassify this species as threatened. We applied a deductive model for the ABB that identified potentially suitable habitat using LANDFIRE Existing Vegetation Types (EVT). The habitat model ranked each EVT using one of four categories: (1) favorable; suitable vegetation to support all or critical portions of the ABB life cycle, (2) conditional; favorable only under certain conditions including seasonality of flooding and land management...
Categories: Data,
Data Release - Revised;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: American burying beetle,
Arkansas,
Kansas,
LANDFIRE,
Missouri,
These data represent occupancy estimates for western bumble bee across the western continental United States and the spatial variation in detection probabilities that occur during bumble bee surveys. This product contains five raster layers (appearing as separate bands in a multi-band raster). The first two bands represent the predicted occupancy of western bumble bee in 1998 and 2018. We modeled western bumble bee occupancy as a function of: latitude, longitude, elevation, year, and land cover. The last three bands represent the spatial variation in detection probabilities predicted to occur for surveys conducted across the western United States on three dates (May 15, July 15, and September 15). We modeled detection...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
Bombus occidentalis,
California,
Colorado,
Detection Probability,
This data release is a re-release of an airborne geophysical survey carried out for the United States Geological Survey (USGS) by Spectra Exploration Geoscience Corp., from November 2000 to February 2001. The purpose of this survey was to acquire high-resolution, high-sensitivity aeromagnetic data over an area in northeast and north-central North Dakota and assess the area for anomalies and magnetic features pertaining to the local geology. To achieve this purpose, the survey area was systematically traversed by an aircraft carrying geophysical instruments along parallel flight lines (traverses) spaced 0.25 miles (400 meters) apart in an east-west alignment. Tie lines were flown normal to the traverses spaced at...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: <1GB,
Cavalier County,
Earth Mapping Resources Initiative,
EarthMRI,
Geology, Geophysics, and Geochemistry Science CenterGGGSC,
Defining site potential for an area establishes its possible long-term vegetation growth productivity in a relatively undisturbed state, providing a realistic reference point for ecosystem performance. Modeling and mapping site potential helps to measure and identify naturally occurring variations on the landscape as opposed to variations caused by land management activities or disturbances (Rigge et al. 2020). We integrated remotely sensed data (250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) (https://earthexplorer.usgs.gov/)) with land cover, biogeophysical (i.e., soils, topography) and climate data into regression-tree software (Cubist®). We...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arid,
Arizona,
Colorado,
Ecology,
Geography,
Location of all big sagebrush land cover obtained from the LANDFIRE Existing Vegetation Type dataset.
Categories: Data;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Artemisia spp.,
Botany,
Colorado,
Ecology,
Idaho,
These data represent occupancy estimates for western bumble bee across the western conterminous United States. This product contains five raster layers (appearing as separate bands in a multi-band raster). The first two bands represent the predicted occupancy of western bumble bee in 1998 and 2020. We modeled western bumble bee occupancy as a function of climate and land cover. The last three bands represent future occupancy projections of western bumble bee into the mid-century (2050s). The future projections cover a range of expected changes in climate and land cover and are ranked as best-case (band 3), middle-case (band 4), and worst-case (band 5).
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Ecology,
Idaho,
Invasion of exotic annual grass (EAG), such as cheatgrass (Bromus tectorum), red brome (Bromus rubens), and medusahead (Taeniatherum caput-medusae), could have irreversible degradation impact to arid and semiarid rangeland ecosystems in the western United States. The distribution and abundance of these EAG species are highly influenced by weather variables such as temperature and precipitation. We set out to develop a machine learning modelling approach using a lightGBM algorithm to predict how changes in annual and immediate past precipitation regimes impact the abundance of EAG in the study area. The predictive model primarily utilized edaphic and weather variables and a seed source proxy from previous years to...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Ecology,
Great Basin,
This Data Release accompanies the publication "State of stress in areas of active unconventional oil and gas development in North America" by J.-E. Lund Snee (now J.-E. Lundstern) and M.D. Zoback (2022) in the AAPG Bulletin. This dataset provides maximum horizontal stress (SHmax) orientation and relative stress magnitude (faulting regime) information that comprise a new-generation crustal stress map for North America. Relative stress magnitudes are presented using the Aϕ (A_phi) parameter, a single scalar that represents the ratio of the three principal stress magnitudes. Data were collected between 2015 and 2022. Data points for SHmax orientations, relative stress magnitudes, and the earthquake focal mechanisms...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Canada,
Caribbean Islands,
Caribbean Sea,
Holocene,
NCCWSC,
Location of agricultural land cover obtained from the LANDFIRE Existing Vegetation Type dataset.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster,
Shapefile;
Tags: Colorado,
Idaho,
Land Use Change,
Montana,
USGS Science Data Catalog (SDC),
This data release comprises a georeferenced raster layer depicting the estimated susceptibility to intense rainfall-induced landslides in Puerto Rico, which is a supplement to: Hughes, K.S., and Schulz, W.H., 2020, Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico: U.S. Geological Survey Open-File Report 2020–1022, 91 p., 1 plate, scale 1:150,000, https://doi.org/10.3133/ofr20201022. Users of this layer are strongly encouraged to read the text herein and available with Open-File Report 2020-1022. DEVELOPMENT OF THE LANDSLIDE SUSCEPTIBILITY MAP Landslides commonly occur in Puerto Rico during or soon after intense rainfall and present significant hazards to the built environment...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: GHSC,
Geomorphology,
Golden,
Puerto Rico,
USGS,
Proportion of agricultural land cover within 18-km radius developed using a circular focal moving window analysis.
Categories: Data,
pre-SM502.8;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Colorado,
Idaho,
Land Use Change,
Montana,
USGS Science Data Catalog (SDC),
Management and disturbances have significant effects on grassland forage production. When using satellite remote sensing to monitor climate impacts such as drought stress on annual forage production, minimizing these effects provides a clearer climate signal in the productivity data. The use of an ecosystem performance approach for assessment of seasonal and interannual climate impacts on forage production in semi-arid grasslands proved to be a successful method in a case study covering the Nebraska Sandhills. In this study we developed a time series (2000-2018) of the Expected Ecosystem Performance (EEP), which serves as a proxy for annual forage production after accounting for non-climatic influences, while minimizing...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Land Use Change,
NDVI,
USGS Science Data Catalog (SDC),
United States,
biomass,
|
|