Data

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 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

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

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

The dataset provides a spatially explicit estimate of 2019 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The estimate is based on the mean output of two regression-tree models. For one model, we include, as an independent variable amongst other independent variables, a dataset that is the mean of 17-years of annual herbaceous percent cover (https://doi.or

Evaluation of historical water use in the Upper Rio Grande Basin (URGB) using Landsat-derived actual evapotranspiration (ETa) from 1986 to 2015 is presented here as a first of its kind study applying satellite observations for quantifying long term, basin-wide crop consumptive use at a large basin. The rich archive of Landsat imagery combined with the Operational Simplified Surface Energy Balance

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation's land cover and land cover change. To continue the legacy of NLCD and further establish a long-term

The Land Change Monitoring Assessment and Projection (LCMAP) sample raster dataset is a suite of five spectral change and five land cover (and land cover derivative) products. The LCMAP approach is the foundation for an integrated land change science framework led by the U.S. Geological Survey (USGS). The sample data represent prototype products that are examples of a new generation of integrated