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Filters Date Range Past year (3) Past month (1) Past week (0) Past day (0) Custom range... To   Search Types Downloadable (5) GeoTIFF (5) Map Service (5) Raster (5) Citation (1) Contacts U.S. Geological Survey - ScienceBase U.S. Geological Survey Forest and Rangeland Ecosystem Science Center John B Bradford Pamela L Nagler More... Categories Data (5) Tag Types Theme (5) Place (5) USGS Scientific Topic Keyword (5) Harvest Set (5) Tag Schemes USGS Thesaurus (5) None (3) Geographic Names Information System (GNIS) (3) ISO 19115 Topic Category (3) Common geographic areas (1) ISO 19115 Topic Categories (2) Common Geograhic Areas (1) More... View Results as: JSON ATOM CSV

Random forest classification data developed from multitemporal Landsat 8 spectral data and phenology metrics for a subregion in Sonoran and Mojave Deserts, April 2013 – December 2020 These data were compiled for the creation of a continuous, transboundary land cover map of Bird Conservation Region 33, Sonoran and Mojave Deserts (BCR 33). Objective(s) of our study were to, 1) develop a machine learning (ML) algorithm trained to classify vegetation land cover using remote sensing spectral data and phenology metrics from 2013-2020, over a large subregion of the Sonoran and Mojave Deserts BCR, 2) Calibrate, validate, and refine the final ML-derived vegetation map using a collection of openly sourced remote sensing and ground-based ancillary data, images, and limited fieldwork, and 3) Harmonize a new transboundary classification system by expanding existing land cover mapping resources from the United... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Arizona, Baja California, Botany, California, Ecology, All tags... Forestry, Geography, Hermosillo, Information Sciences, Landsat images, Mexico, Mojave Desert, Phoenix, Remote Sensing, Sonora, Sonoran Desert, Southwest, US-Mexico Transboundary region, USGS Science Data Catalog (SDC), United States, artificial intelligence, biogeography, biota, classification, conservation, data release, desert ecosystems, ecosystem management, imageryBaseMapsEarthCover, land use and land cover, machine learning, modeling, natural resource management, phenology, phenology metrics, random forest model, remote sensing, remote sensing spectral data, time series datasets, transboundary, vegetation, Fewer tags All Big Sagebrush Species Land Cover in the Wyoming Basins Ecoregional Assessment area 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, All tags... Land Use Change, Montana, USGS Science Data Catalog (SDC), United States, Utah, Wyoming, Wyoming Basins Ecoregional Assessment, big sagebrush, biota, conservation, environment, land use and land cover, vegetation, Fewer tags Data for Use in poscrptR Post-fire Conifer Regeneration Prediction Model These data support poscrptR (Wright et al. 2021). poscrptR is a shiny app that predicts the probability of post-fire conifer regeneration for fire data supplied by the user. The predictive model was fit using presence/absence data collected in 4.4m radius plots (60 square meters). Please refer to Stewart et al. (2020) for more details concerning field data collection, the model fitting process, and limitations. Learn more about shiny apps at https://shiny.rstudio.com. The app is designed to simplify the process of predicting post-fire conifer regeneration under different precipitation and seed production scenarios. The app requires the user to upload two input data sets: 1. a raster of Relativized differenced Normalized... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Botany, California, Forestry, Oregon, USGS Science Data Catalog (SDC), All tags... biota, elevation, environment, forest ecosystems, geoscientificInformation, geospatial datasets, gymnosperms, imageryBaseMapsEarthCover, topography, Fewer tags Observed wildfire frequency, modelled wildfire probability, climate, and fine fuels across the big sagebrush region in the western United States These data were compiled so that annual wildfire could be modelled across the sagebrush region in the western United States. Our goal was to understand how wildfire probability relates to climate and fuel conditions across the entire sagebrush region. To do this we developed a statistical model that represents the relationship between annual wildfire probability and a small number of climate and fuel variables. Specifically, created predictions of wildfire probability using a biologically plausible logistic regression model that related wildfire probability to mean temperature, annual precipitation, the proportion summer precipitation (PSP), and aboveground biomass of annual herbaceous plants and perennial herbaceous... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Arizona, Botany, California, Climatology, Colorado, All tags... Ecology, Forestry, Geography, Idaho, Information Sciences, Land Use Change, Montana, Nebraska, Nevada, New Mexico, North Dakota, Oregon, Remote Sensing, South Dakota, USGS Science Data Catalog (SDC), Utah, Washington, Wyoming, aboveground biomass, air temperature, annual plants, annual-grass fire cycle, atmospheric and climatic processes, biogeography, biota, data release, ecology, environment, fine fuel availability, fire occurrence, fires, herbacious plants, human impacts, logistic regression model, mathematical modeling, perennial plants, plants (organisms), precipitation (atmospheric), sagebrush region, vegetation, vegetation data, western United States, widlfire probability, wildfires, Fewer tags Land Cover Basin Characteristics Rasters from NLCD 2019 for South Carolina StreamStats In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey calculated four land cover basin characteristics rasters from the National Land Cover Database (NLCD) 2019 as part of updating the South Carolina StreamStats application. These datasets are raster representations of impervious surface, developed, forested, and storage land cover attributes within the South Carolina StreamStats study area, and will be served in the South Carolina StreamStats application (https://www.usgs.gov/streamstats) to describe delineated watersheds. The StreamStats application provides access to spatial analytical tools that are useful for water-resources planning and management, and for engineering... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Botany, Ecology, Forestry, Hydrology, Land Use Change, All tags... South Carolina, USGS Science Data Catalog (SDC), Water Quality, Water Resources, biota, environment, forest ecosystems, geoscientificInformation, geospatial datasets, human impacts, hydrology, image analysis, imageryBaseMapsEarthCover, inlandWaters, land use and land cover, runoff, vegetation, Fewer tags