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Data

EROS is home to the world's largest collection of remotely sensed images of the Earth’s land surface and the primary source of Landsat satellite images and data products. NASA’s Land Processes Distributed Active Archive Center (LP DAAC) is also located at EROS. Use the links below to explore and access our data holdings.

Filter Total Items: 111

Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2022 (ver 2.0, May 2022)

These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and a native perennial grass predicted on May 6th using satellite observation data available no later than April 29th. Four fractional cover maps comprise this release, along with the corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusa

Black Hills Region South Dakota 2017 Legion Lake Fire Burned and Unburned Plot Measurements

U.S Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of September 5 - 14, 2018, November 8 - 13, 2018, June 18 - 27, 2019, July 30 - August 8, 2019, September 13 - 19, 2019, and June 23 - July 1, 2020. These efforts used a combination of technologies to map twenty burned and twelve unburned forest plots at eleven sites in the Black Hills of South

Projections of Rangeland Fractional Component Cover Across the Sagebrush Biome for Representative Concentration Pathways (RCP) 4.5 and 8.5 Scenarios for the 2020s, 2050s, and 2080s Time-Periods (ver. 1.1, April 2022)

Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are unknown. While a number of studies have projected the impacts of climate change using several modeling approaches, none has evaluated impacts to fractional component cover at a 30-m resolution

Chesapeake Bay Region Virginia River Bluff and Wetland Extent Mapping

The Chesapeake Bay Estuary is the largest estuary in the United States and provides habitats for diverse wildlife and aquatic species, protects communities against flooding, reduces pollution to waterways, and supports local economies through commercial and recreational activities. In the Spring of 2018, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Pro

Global gray-sky dT: the inverse of the surface psychrometric constant parameter in the SSEBop evapotranspiration model

The surface psychrometric constant (spc) is a key model parameter in actual evapotranspiration modeling using the Operational Simplified Surface Energy Balance (SSEBop) model for establishing model boundary limits for the dry/bare and wet/vegetated surface conditions. The inverse of the constant (1/spc) represents the temperature difference (dT) between the bare/dry surface and the air temperature

A circa 2010 global land cover reference dataset from commercial high resolution satellite data

The data are 475 thematic land cover raster?s at 2m resolution. Land cover classification was to the land cover classes: Tree (1), Water (2), Barren (3), Other Vegetation (4) and Ice & Snow (8). Cloud cover and Shadow were sometimes coded as Cloud (5) and Shadow (6), however for any land cover application would be considered NoData. Some raster?s may have Cloud and Shadow pixels coded or recod

Topobathymetric Model of the Coastal Carolinas, 1851 to 2020

To support Hurricane Florence impact modeling of storm-induced flooding and sediment transport, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for coastal North Carolina, and South Carolina. High-resolution coastal topobathymetric data are required to characterize f

2020 Niobrara River Topobathymetric Lidar Validation – USGS Field Survey Data

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between August 17th and 28th, 2020 over a large stretch of the Niobrara River in Nebraska using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data. The goal was to compare and validate the airborne lidar d

LCMAP CONUS Geographic Assessment Data Tables v1.0 1985-2016

This is a collection of data tables supporting the LCMAP CONUS Geographic Assessment v1.0. The data used to generate these tables come from the USGS LCMAP reference dataset and the map products released by LCMAP. Tables include annual land cover class composition and annual rate of land cover change metrics developed with a post-stratified estimator. Other tables including annual gross change of s

Unit hydrographs of evolving urban watersheds across the United States

The dataset contains the land cover, climate (precipitation and air temperature), unit hydrograph and its characteristics (peak and time to peak), and study watershed boundaries. These data were applied to investigate the impacts of changes in land cover and climate on stormflow of evolving six urban watersheds, representing six different hydroclimate of the conterminous United States. Overall, th

Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Annual Land Cover and Land Cover Change Validation Tables (2000-2019) for Hawaii

A validation assessment of Land Cover Monitoring, Assessment, and Projection annual land cover products (2000-2019) for Hawaii was conducted with an independently collected reference data set. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (2000-2019) to a reference sample of 600 Landsat resolution (30m x 30m) pixels. The interpreted lan

Land surface thermal feature change monitoring in urban and urban wild land interface (ver. 3.0, August 2020)

We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in selected metropolitan areas in the United States by using Landsat surface temperature product in a time series manner. Landsat land surface temperature from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature and change from 1985 to the current. These data were used to calculate the tempera