Filters: partyWithName: Southwest Biological Science Center (X) > Types: Downloadable (X) > Types: Raster (X)

Filters Date Range Past year (2) Past month (1) Past week (0) Past day (0) Custom range... To   Search Extensions Raster (2) Types GeoTIFF (2) Map Service (2) Contacts John B Bradford Pamela L Nagler U.S. Geological Survey U.S. Geological Survey - ScienceBase Ecosystems Kamel Didan Daniel R Schlaepfer Categories Data (2) Tag Types Theme (2) Place (2) USGS Scientific Topic Keyword (2) Harvest Set (2) Tag Schemes None (2) USGS Thesaurus (2) Geographic Names Information System (GNIS) (2) ISO 19115 Topic Categories (2) USGS information products (2) 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 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