Skip to main content
Advanced Search

Filters: Tags: Validation (X) > partyWithName: U.S. Geological Survey (X)

5 results (34ms)   

View Results as: JSON ATOM CSV
thumbnail
Western U.S. rangelands have been quantified as six fractional cover (0-100%) components over the Landsat archive (1985-2018) at 30-m resolution, termed the “Back-in-Time” (BIT) dataset. Robust validation through space and time is needed to quantify product accuracy. We leverage field data observed concurrently with HRS imagery over multiple years and locations in the Western U.S. to dramatically expand the spatial extent and sample size of validation analysis relative to a direct comparison to field observations and to previous work. We compare HRS and BIT data in the corresponding space and time. Our objectives were to evaluate the temporal and spatio-temporal relationships between HRS and BIT data, and to compare...
thumbnail
Land Change Monitoring, Assessment, and Projection (LCMAP) represents a new generation of land cover mapping and change monitoring from the U.S. Geological Survey’s Earth Resources Observation and Science (EROS) Center. LCMAP answers a need for higher quality results at greater frequency with additional land cover and change variables than previous efforts. By utilizing a suite of operational automated algorithms to identify different forms of change and to characterize the large variety of land cover types, uses, and conditions that exist across the United States and beyond, LCMAP products provide land change science information in understanding changes in the type, intensity, condition, location, and time of...
thumbnail
U.S. Geological Survey (USGS) scientists conducted field data collection efforts between March 8th and 25th, 2021 at four sites along coastal North Carolina and South Carolina using high accuracy surveying technologies. The work was initiated as an effort to validate a topobathymetric digital elevation model (TBDEM) produced for the area that was directly impacted by Hurricane Florence in 2018. The goal was to compare the airborne lidar and sonar derived TBDEM to data collected through more traditional means (e.g. Global Navigational Satellite System (GNSS) surveying). In addition, coastal dunes were mapped with ground based lidar (GBL) for computation of dune metrics. The Hurricane Florence TBDEM will support the...
Categories: Data; Tags: 3D Elevation Program, 3DEP, CMHRP, Cape Hatteras National Seashore, CoNED, All tags...
thumbnail
Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential Climate Variable (BAECV) algorithm. We present the BA algorithm and products, changes relative to the BAECV algorithm and products, and updated validation metrics. We also present spatial and temporal patterns of burned area across the conterminous U.S. and a comparison with other burned area datasets. The BA algorithm identifies burned areas in analysis ready data (ARD) time-series of Landsat imagery from 1984...
thumbnail
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 recoded to NoData already. Commercial high-resolution satellite data was used to create the classifications. Usable image data for the target year (2010) was acquired for 475 of the 500 primary sample locations, with 90% of images acquired within ±2 years of the 2010 target. The remaining 25 of the 500 sample blocks had no usable...


    map background search result map search result map Data Release for the validation of the USGS Landsat Burned Area Product across the conterminous U.S. (ver. 2.0, May 2020) Temporal and Spatio-Temporal High-Resolution Satellite Data for the Validation of a Landsat Time-Series of Fractional Component Cover Across Western United States (U.S.) Rangelands Coastal Carolinas Topobathymetric Model: Field Validation Data, 2021 Coastal Carolinas Topobathymetric Model: Field Validation Data, 2021 Temporal and Spatio-Temporal High-Resolution Satellite Data for the Validation of a Landsat Time-Series of Fractional Component Cover Across Western United States (U.S.) Rangelands Data Release for the validation of the USGS Landsat Burned Area Product across the conterminous U.S. (ver. 2.0, May 2020)