Data

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

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

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

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

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

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

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

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

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

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

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

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