Publications

High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within-season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibl

Landsat Collection 2 (C2) U.S. Analysis Ready Data (U.S. ARD) are bundles of tiled Landsat data that make the Landsat archive easier to analyze and reduce the amount of time users spend on data processing for time-series analysis. Landsat C2 was released in 2020 and includes improvements over Landsat Collection 1 data, including better geometric accuracy, which increases the number of available C2

Floods have become increasingly prominent in recent decades, especially in urban areas causing devastating effects on lives and livelihoods worldwide. Efficient tools to assess the drivers of floods, such as increasing urbanization could help to minimize flood hazards. A Google Earth Engine (GEE) application was developed to explore the potential changes (1985-2020) in design peak-flow of urban ar

ContextYellow sweetclover (Melilotus officinalis; YSC) is an invasive biennial legume that bloomed across the Northern Great Plains in 2018–2019 in response to above-average precipitation. YSC can increase nitrogen (N) levels and potentially cause substantial changes in the composition of native plant species communities. There is little knowledge of the spatiotemporal variability and conditions c

The dimethyl sulfoxide reductase (or MopB) family is a diverse assemblage of enzymes found throughout Bacteria and Archaea. Many of these enzymes are believed to have been present in the last universal common ancestor (LUCA) of all cellular lineages. However, gaps in knowledge remain about how MopB enzymes evolved and how this diversification of functions impacted global biogeochemical cycles thro

This research builds upon the extensive body of work to model exotic annual grass (EAG) characteristics and invasion. EAGs increase wildland fire risk and intensifies wildland fire behavior in western U.S. rangelands. Therefore, understanding characteristics of EAG growth increases understanding of its dynamics and can inform rangeland management decisions. To better understand EAG phenology and s

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and ap

Executive SummaryThe U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team

The National Land Cover Database (NLCD), a product suite produced through the MultiResolution Land Characteristics (MRLC) consortium, is an operational land cover monitoring program. Starting from a base year of 2001, NLCD releases a land cover database every 2–3-years. The recent release of NLCD2019 extends the database to 18 years. We implemented a stratified random sample to collect land cover

Remotely sensed surface temperature (ST) has been widely used to monitor and assess landscape thermal conditions, hydrologic modeling, and surface energy balance. Landsat thermal sensors have continuously measured the Earth surface thermal radiance since August 1982. The thermal radiance measurements are atmospherically compensated and converted to Landsat STs and delivered as part of the U.S. Geo

We proposed a new image compositing algorithm (MAX-RNB) based on the maximum ratio of Near Infrared (NIR) to Blue band (RNB), and evaluated it together with nine other compositing algorithms: MAX-NDVI (maximum Normalized Difference Vegetation Index), MED-NIR (median NIR band), WELD (conterminous United States Web-Enabled Landsat Data), BAP (Best Available Pixel), PAC (Phenology Adaptive Composite)

The use of remote sensing in time series analysis enables wall-to-wall monitoring of the land surface and is critical for assessing and understanding land cover and land use change and for understanding the Earth system as a whole. However, variability in remote sensing observation frequency through time and across space presents challenges for producing consistent change detection results through