Geographer
Email:
bwsmith@usgs.gov
ORCID:
0000-0003-1556-2383
Location
Tucson
, AZ
85719
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This dataset is support materials for the publication "Crop type classification, trends, and patterns of central California agricultural fields from 2005 – 2020". This data release is comprised of two child datasets. The first dataset, 'Labeled_CropType_Points', is a shapefile that consists of randomly selected point locations in which crop types were verified using high resolution imagery for each examined year across the study period (2005 - 2020). The second dataset, 'Central_CA_Classified_Croplands', is also a shapefile, but contains polygons of 9 classified crop types derived from a random forest machine learning classifier for central California for each examined year across the study period (2005 - 2020).
Tags: California,
Central Valley,
Geography,
Land Use Change,
Landsat, All tags...
NAIP,
Remote Sensing,
USGS Science Data Catalog (SDC),
agriculture,
biota,
crop type,
image classification,
machine learning, Fewer tags
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This dataset represents a summary of potential cropland inundation for the state of California applying high-frequency surface water map composites derived from two satellite remote sensing platforms (Landsat and Moderate Resolution Imaging Spectroradiometer [MODIS]) with high-quality cropland maps generated by the California Department of Water Resources (DWR). Using Google Earth Engine, we examined inundation dynamics in California croplands from 2003 –2020 by intersecting monthly surface water maps (n=216 months) with mapped locations of precipitation amounts, rice, field, truck (which comprises truck, nursery, and berry crops), deciduous (deciduous fruits and nuts), citrus (citrus and subtropical), vineyards,...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Shapefile;
Tags: California,
Geography,
Hydrology,
Landsat,
MODIS, All tags...
Remote Sensing,
USGS Science Data Catalog (SDC),
agricultural sites,
agriculture,
controlled flooding,
farming,
floods,
hazard preparedness,
image collections,
imageryBaseMapsEarthCover,
irrigation,
multispectral imaging, Fewer tags
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We created a single map of surface water presence by intersecting water classes from available land cover products (National Wetland Inventory, Gap Analysis Program, National Land Cover Database, and Dynamic Surface Water Extent) across the U.S. state of Arizona. We derived classified samples for four wetland classes from the harmonized map: water, herbaceous wetlands, wooded wetlands, and non-wetland cover. In Google Earth Engine (GEE) we developed a random forest model that combined the training data with spatially explicit predictor variables of vegetation greenness indices, wetness indices, seasonal index variation, topographic variables, and hydrologic parameters. The final product is a wall-to-wall map of...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Raster;
Tags: Arizona,
Ecology,
Geography,
Hydrology,
Land Use and Land Cover Map, All tags...
Remote Sensing,
USGS Science Data Catalog (SDC),
desert ecosystems,
deserts,
imageryBaseMapsEarthCover,
land use and land cover,
wetlands,
wetlands, Fewer tags
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