Filters: Categories: Data Release - Revised (X) > partyWithName: Yen-Ju G Beal (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Contacts Melanie K Vanderhoof Todd J Hawbaker Geosciences and Environmental Change Science Center U.S. Geological Survey U.S. Geological Survey - ScienceBase Joshua D Takacs John L Dwyer Categories Data (2) Tag Types Place (2) Theme (2) Harvest Set (3) Tag Schemes None (2) View Results as: JSON ATOM CSV

Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 - 2015) The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions. Outputs of the BAECV algorithm consist of pixel-level burn probabilities for each Landsat scene, and annual burn probability, burn classification, and burn date composites. These products were generated for the conterminous United States for 1984 through 2015. These data are also available for download at https://rmgsc.cr.usgs.gov/outgoing/baecv/BAECV_CONUS_v1.1_2017/... Categories: Data Release - Revised; Tags: Alabama, Arizona, Arkansas, BAECV, Burned area, All tags... California, Colorado, Connecticut, Delaware, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Landsat, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Prescribed fire, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, USGS Science Data Catalog (SDC), United States, Utah, Vermont, Virginia, Washington, West Virginia, Wildfire, Wildland fire, Wisconsin, Wyoming, Fewer tags The Landsat Burned Area products for the conterminous United States (ver. 3.0, March 2022) Starting in 2022, processing switched to the Collection 2 Landsat ARD data. Landsat Burned Area Products for 2022 based on Landsat Collection 2 data are available at: Hawbaker, T.J., Vanderhoof, M.K., Schimdt, G.L., and Picotte, J.P., 2023. The Landsat Collection 2 Burned Area Products for the conterminous United States, U.S. Geological Survey Data Release, https://doi.org/10.5066/P9F26LY6 The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference... Categories: Data, Data Release - Revised; Tags: USGS Science Data Catalog (SDC) Data Release for the validation of the USGS Landsat Burned Area Product across the conterminous U.S. (ver. 2.0, May 2020) 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... Categories: Data, Data Release - Revised; Tags: CONUS, Landsat, North America, USGS Science Data Catalog (SDC), United States, All tags... Wildfire, Wildland fire, burned area, fire, validation, Fewer tags