Data

Area estimates of land cover and land cover change are often based on reference class labels determined by analysts interpreting satellite imagery and aerial photography. Different interpreters may assign different reference class labels to the same sample unit. This dataset include land cover attributes for the year 2000 assigned by 7 image analysts, working independently of each other...

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 use of an ecosystem performance approach for assessment of seasonal and interannual climate impacts...

The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error...

The estimation and mapping of actual evapotranspiration (ETa) is an active area of applied research in the fields of agriculture and water resources. Thermal remote sensing-based methods, using coarse resolution satellites, have been successful at estimating ETa over the conterminous United States (CONUS) and other regions of the world. In this study, we present CONUS-wide ETa from...

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD developed a cloud validation dataset from 48 unique Landsat 8 Collection 2 images. These images were selected at random from the Landsat 8 archive from various locations around the world. While these validation images were subjectively designed by a single analyst, they provide...

Information on the spatio-temporal distribution of rainfall is very critical for addressing water related disasters, especially in the arid to semi-arid regions of the Middle East and North Africa region. However, availability of reliable rainfall datasets for the region is limited. In this study we combined observation from satellite-based rainfall data, in situ rain gauge observation...

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation...

CONUS-wide acutal ET (ETa) from Landsat thermal imagery-using the Operational Simplified Surface Energy Balance (SSEBop) model in the Google Earth Engine (GEE) cloud computing platform. Over 150,000 Landsat satellite images were used to produce 10 years of annual ETa (2010-2019).

LCMAP Science Products are developed by applying time-series modeling to U.S. Landsat Analysis Ready Data (ARD) to detect land surface change. An application of the Continuous Change Detection and Classification (CCDC, Zhu and Woodcock 2014) was developed by the LCMAP Science Team at the USGS Earth Resources Observation and Science (EROS) Center (Brown et al., 2020). LCMAP Collection v1...

We developed a 30-m spatial resolution forest regrowth time map for CONUS over 1985–2017. This map is the first attempt, as far as we know, to quantify tree regrowth rate at a national extent in the United States. The method used all available Landsat images to detect disturbances over forest lands and classify grass/shrub to tree class transitions on an annual basis. The average...

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD developed a cloud validation dataset from 48 unique Landsat 8 Collection 1 images. These images were selected at random from the Landsat 8 archive from various locations around the world. While these validation images were subjectively designed by a single analyst, they provide...

This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L...