Data

Western U.S. rangelands have been quantified as six fractional cover (0-100%) components over the Landsat archive (1985-2018) at 30-m resolution, termed the "Back-in-Time" (BIT) dataset. Robust validation through space and time is needed to quantify product accuracy. We leverage field data observed concurrently with HRS imagery over multiple years and locations in the Western U.S. to dramatically

NASS USDA estimates the irrigated croplands at county level every five years. But this estimation does not provide the geospatial information of the irrigated croplands. To provide a comprehensive, consistent, and timely geospatially detailed information about irrigated cropland conterminous U.S. (CONUS), the "Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for

This data release has been superseded by version 3.0, available here: https://doi.org/10.5066/P9MJVQSQ Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrubl

Daily SSEBop evapotranspiration at the Moderate Resolution Imaging Spectroradiometer (MODIS) scale was created for the CONUS. These data are published on the USGS earlywarning site (https://earlywarning.usgs.gov/ssebop/modis/daily). The first phase included the creation on historical actual daily ET data from 2000 to 2018. The second phase will create the ET product operationally on a daily time s

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in U.S. Landsat Analysis Ready Data (ARD) tiles to produce Landsat Burned Area Products. The algorithm makes use of predictors derived from individual Landsat ARD tiles, lagged reference conditions, and change metrics between the tile and reference conditions. Tile-level products include pixel

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies the spatial and temporal distribution of surface water in U.S. Landsat Analysis Ready Data (ARD) tiles to produce Landsat Dynamic Surface Water Extent (DSWE) Products. These acquisition based products are available for the conterminous U.S. (CONUS), Alaska, and Hawaii from 1982 to present. The DSWE package

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that calculates statistics from the Landsat fractional Snow Covered Area (fSCA) Science Product, which is derived from U.S. Landsat Analysis Ready Data (ARD) tiles. These tile-based fSCA statistics packages include monthly, annual, and mean annual snow cover fractions as well as monthly and annual clear pixel counts. 5-ye

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies the spatial and temporal distribution of snow covered area in U.S. Landsat Analysis Ready Data (ARD) tiles to produce Landsat fractional Snow Covered Area (fSCA) Science Products. The fSCA packages include per-pixel percentages of snow cover (SNOW) as well as a revised cloud mask (REVCM) which flags variou

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 research objectives are to (1) estimate biomass expected at a certain location under specific weather condition

Understanding how different crops use water over time is essential for planning and managing water allocation, water rights, and agricultural production. The main objective of this paper is to characterize the spatiotemporal dynamics of crop water use in the Central Valley of California using Landsat-based annual actual evapotranspiration (ETa) from 2008-2018 derived from the Operational Simplifie

This dataset provides a near-real-time estimate of 2019 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data g

The Majuro Atoll inundation grids are useful for characterizing and quantifying inundation exposure and related vulnerability of the atoll's low-relief lands and their population, buildings, infrastructure, and natural resources. The grids represent various scenarios of inundation and different approaches to mapping the inundation levels. The inundation scenarios include static inundation (without