Filters: partyWithName: U.S. Geological Survey - ScienceBase (X) > Categories: Data Release - Revised (X) > partyWithName: Geosciences and Environmental Change Science Center (X)
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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/...
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 uses predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions. Scene-level products include pixel-level burn probability (BP) and burn classification (BC) images corresponding to each Landsat image in the ARD time series. Annual composite products are also available by summarizing the scene-level products. Prior to generating annual composites, individual scenes that had > 0.010 burned proportion...
Categories: Data,
Data Release - Revised;
Tags: Burned area,
Landsat,
Prescribed fire,
USGS Science Data Catalog (SDC),
United States,
Ecosystems benefit people in many ways, but these contributions do not appear in traditional national or corporate accounts so are often left out of policy- and decision-making. Ecosystem accounts, as formalized by the System of Environmental-Economic Accounting Experimental Ecosystem Accounts (SEEA EEA), track the extent and condition of ecosystem assets and the flows of ecosystem services they provide to people and the economy. While ecosystem accounts have been compiled in a number of countries, there have been few attempts to develop them for the United States. We explore the potential for ecosystem accounting in the United States by compiling ecosystem condition and ecosystem services supply and use accounts...
Categories: Data Release - Revised;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Alabama,
Arkansas,
Ecology,
Environmental Health,
Florida,
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...
This release provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2019; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this release also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall...
Categories: Data,
Data Release - Revised;
Tags: Alaska,
Arctic National Wildlife Refuge,
CLIMATE,
MONITORING,
National Petroleum Reserve,
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,
This dataset contains argon-argon and U-Pb geochronologic data collected from igneous rocks in the Stillwater Range, Clan Alpine, and Desatoya Mountains, western Nevada, USA First posted - November 16, 2017 Revised - February 26, 2019 (version 2.0) Revised - December 12, 2023 (version 3.0)
Categories: Data,
Data Release - Revised;
Tags: Clan Alpine Mountains,
Desatoya Mountains,
Geochemistry,
Geochronology,
Stillwater Range,
Although ecosystem service (ES) modeling has progressed rapidly in the last 10-15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study we apply inter- and intra-model comparisons to address these questions at national and provincial scales in Rwanda. We compare results of (1) carbon, annual, and seasonal water yield using InVEST and WASSI models, and the above plus the InVEST sediment regulation model using (2) 30- and 300 m resolution data and (3) three different input land cover datasets. For the inter-model comparison, we found the two...
Categories: Data Release - Revised;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Burundi,
Ecosystem Service,
Rwanda,
USGS Science Data Catalog (SDC),
biophysical,
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