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
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