AndreaBozzo/ceres-open-data-index huggingface dataset:
Wildfire Risk to Communities Community Wildfire Risk Reduction Zones (4-Category)

<div style='text-align:Left;'><div><div><p><span>This data publication includes Community Wildfire Risk Reduction Zone rasters, products delivered as part of the Wildfire Risk to Communities project. There are two types of data included: 1) raster spatial data that delineate Community Wildfire Risk Reduction Zones for all populated areas in the continental United States (CONUS), Alaska, and Hawaii; and 2) tabular summaries by communities, counties, tribal areas, and states of wildfire hazard and risk produced as part of the Wildfire Risk to Communities (WRC) project.</span></p><p><span>The Community Wildfire Risk Reduction Zones (CWiRRZ) product is a 30-m raster delineating areas where mitigation activities will be most effective at protecting homes from most types of wildfire. The zones are determined by the spatial coincidence of wildfire likelihood (Burn Probability), and populated areas. There are four Risk Reduction Zones: Minimal Exposure Zone, Indirect Exposure Zone, Direct Exposure Zone, and Wildfire Transmission Zone. However, the CWiRRZ raster can be further deconstructed into ten zones, wherein the Wildfire Transmission Zone is separated into the following surface fuel types: Tree, Shrub, Grass, Agriculture, Non-Vegetated, Water, and Outlying Wildlands (area beyond 2400-m from buildings).</span></p><div><div><p><span>Additional methodology documentation is provided with the data publication download. (</span><a target='_blank' href='https://www.fs.usda.gov/rds/archive/Catalog/RDS-2024-0030' rel='nofollow ugc noopener noreferrer'><span>https://www.fs.usda.gov/rds/archive/Catalog/RDS-2024-0030</span></a><span>)</span></p><p><span>Note: Pixel values in this image service have been altered from the original raster dataset due to data requirements in web services. The service is intended primarily for data visualization. Relative values and spatial patterns have been largely preserved in the service, but users are encouraged to download the source data for quantitative analysis.</span></p></div></div></div></div></div>

Tags: alaska, burn-probability, conterminous-united-states, conus, ecology, ecosystems, environment, environment-and-people, fire, fire-detection, fire-ecology, fire-effects-on-environment, fire-likelihood, fire-planning, fire-suppression, forest-management, fuels-management, geoscientificinformation, hawaii, hazard, landscape-management, pre-suppression, prescribed-fire, risk-assessment, society, structure, wildfire-hazard-potential
Organization: Department of Agriculture
Wildfire Risk to Communities Community Wildfire Risk Reduction Zones (10-Category)

<div style='text-align:Left;'><div><div><p><span>This data publication includes Community Wildfire Risk Reduction Zone rasters, products delivered as part of the Wildfire Risk to Communities project. There are two types of data included: 1) raster spatial data that delineate Community Wildfire Risk Reduction Zones for all populated areas in the continental United States (CONUS), Alaska, and Hawaii; and 2) tabular summaries by communities, counties, tribal areas, and states of wildfire hazard and risk produced as part of the Wildfire Risk to Communities (WRC) project.</span></p><p><span>The Community Wildfire Risk Reduction Zones (CWiRRZ) product is a 30-m raster delineating areas where mitigation activities will be most effective at protecting homes from most types of wildfire. The zones are determined by the spatial coincidence of wildfire likelihood (Burn Probability), and populated areas. There are four Risk Reduction Zones: Minimal Exposure Zone, Indirect Exposure Zone, Direct Exposure Zone, and Wildfire Transmission Zone. However, the CWiRRZ raster can be further deconstructed into ten zones, wherein the Wildfire Transmission Zone is separated into the following surface fuel types: Tree, Shrub, Grass, Agriculture, Non-Vegetated, Water, and Outlying Wildlands (area beyond 2400-m from buildings).</span></p><p><span>Additional methodology documentation is provided with the data publication download. (</span><a target='_blank' href='https://www.fs.usda.gov/rds/archive/Catalog/RDS-2024-0030' rel='nofollow ugc noopener noreferrer'><span>https://www.fs.usda.gov/rds/archive/Catalog/RDS-2024-0030</span></a><span>)</span></p><p><span>Note: Pixel values in this image service have been altered from the original raster dataset due to data requirements in web services. The service is intended primarily for data visualization. Relative values and spatial patterns have been largely preserved in the service, but users are encouraged to download the source data for quantitative analysis.</span></p></div></div></div>

Tags: alaska, burn-probability, conterminous-united-states, conus, ecology, ecosystems, environment, environment-and-people, fire, fire-detection, fire-ecology, fire-effects-on-environment, fire-likelihood, fire-planning, fire-suppression, forest-management, fuels-management, geoscientificinformation, hawaii, hazard, landscape-management, pre-suppression, prescribed-fire, risk-assessment, society, structure, wildfire-hazard-potential
Organization: Department of Agriculture
Monitoring Trends in Burn Severity (MTBS) Alaska

<div style='text-align:Left;'><div><div><p><span>The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in Alaska. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires were not discernable from available imagery.</span></p></div></div></div>

Tags: ak, alaska, burn-severity, burned-area, continental-u-s, conus, differenced-normalized-burn-ratio, fire-location, fire-occurrence, hawaii, hi, imagerybasemapsearthcover, landsat, location, mtbs, normalized-burn-ratio, pr, prescribed-fire, puerto-rico, sentinel, united-states, us, wildfire, wildland-fire
Organization: Department of Agriculture
Monitoring Trends in Burn Severity (MTBS) Conterminous United States

<div style='text-align:Left;'><div><div><p><span>The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in CONUS. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires were not discernable from available imagery.</span></p></div></div></div>

Tags: ak, alaska, burn-severity, burned-area, continental-u-s, conus, differenced-normalized-burn-ratio, fire-location, fire-occurrence, hawaii, hi, imagerybasemapsearthcover, landsat, location, mtbs, normalized-burn-ratio, pr, prescribed-fire, puerto-rico, sentinel, united-states, us, wildfire, wildland-fire
Organization: Department of Agriculture
ROSETTA-ORBITER STEINS OSINAC 3 AST1 RDR V2.0

This CODMAC level 3 data set contains radiometric calibrated image data in W/m^2/sr/nm,  acquired by the OSIRIS Narrow Angle Camera on the Rosetta spacecraft  during the STEINS FLY-BY mission phase, covering the period  from 2008-08-04T00:00:00.000 to 2008-10-05T23:59:59.000. The prime target is asteroid 2867 Steins. This version V2.0 supersedes previous deliveries of the same dataset with the following changes since the last version: Reprocessed dataset after October 2018 PSA/PDS external peer review.

Tags: 16-cyg-b, 2867-steins, international-rosetta-mission, starfield, vega
Organization: National Aeronautics and Space Administration
Monitoring Trends in Burn Severity (MTBS) Puerto Rico

<div style='text-align:Left;'><div><div><p><span>The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in Puerto_Rico. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires were not discernable from available imagery.</span></p></div></div></div>

Tags: ak, alaska, burn-severity, burned-area, continental-u-s, conus, differenced-normalized-burn-ratio, fire-location, fire-occurrence, hawaii, hi, imagerybasemapsearthcover, landsat, location, mtbs, normalized-burn-ratio, pr, prescribed-fire, puerto-rico, sentinel, united-states, us, wildfire, wildland-fire
Organization: Department of Agriculture
Next Generation Fire Severity Mapping (Image Service)

<div style='text-align:Left;'><div><div><p><span>The geospatial products described and distributed here depict the probability of high-severity fire, if a fire were to occur, for several ecoregions in the contiguous western US.        </span></p><p><span>The ecological effects of wildland fire – also termed the fire severity – are often highly heterogeneous in space and time. This heterogeneity is a result of spatial variability in factors such as fuel, topography, and climate (e.g. mean annual temperature). However, temporally variable factors such as daily weather and climatic extremes (e.g. an unusually warm year) also may play a key role.     </span></p><p><span>Scientists from the US Forest Service Rocky Mountain Research Station and the University of Montana conducted a study in which observed data were used to produce statistical models describing the probability of high severity fire as a function of fuel, topography, climate, and fire weather. Observed data from over 2000 fires (from 2002-2015) were used to build individual models for each of 19 ecoregions in the contiguous US (see Parks et al. 2018, Figure 1). High severity fire was measured using a fire severity metric termed the relativized burn ratio, which uses pre- and post-fire Landsat imagery to measure fire-induced ecological change. Fuel included pre-fire metrics of live fuel amount such as NDVI. Topography included factors such as slope and potential solar radiation. Climate summarized 30-year averages of factors such as mean summer temperature that spatially vary across the study area. Lastly, fire weather incorporated temporally variable factors such as daily and annual temperature.    </span></p><p><span>In turn, these statistical models were used to generate "wall-to-wall" maps depicting the probability of high severity fire, if a fire were to occur, for 13 of the 19 ecoregions. Maps were not produced for ecoregions in which model quality was deemed inadequate. All maps use fuel data representing the year 2016 and therefore provide a fairly up-to-date assessment of the potential for high severity fire. For those ecoregions in which the relative influence of fire weather was fairly strong (n=6), two additional maps were produced, one depicting the probability of high severity fire under moderate weather and the other under extreme weather. An important consideration is that only pixels defined as forest were used to build the models; consequently maps exclude pixels considered non-forest.</span></p></div></div></div>

Tags: apache-highlands, arizona, arizona-new-mexico-mountains, burn-severity, california, california-north-coast, california-south-coast, canadian-rockies, colorado, colorado-plateau, environment, fire, fire-ecology, fire-effects, fire-effects-in-the-environment, fire-severity, great-basin, jfsp, joint-fire-science-program, middle-rockies, new-mexico, southern-rockies, utah, utah-high-plateaus, utah-wyoming-rockies, west-cascades, western-contiguous-united-states, wildland-fire, wyoming
Organization: Department of Agriculture
National Land Cover Database (NLCD) Tree Canopy Cover (TCC) Conterminous United States

<div style='text-align:Left;'><div><div><p><span>The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2023-5 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The NLCD product suite includes data for years 1985 through 2023. The NCLD data are processed to mask TCC from non-treed features such as water and non-tree crops, and to reduce interannual noise and smooth the NLCD time series. TCC pixel values range from 0 to 100 percent. The non-processing area is represented by value 254, and the background is represented by the value 255. The Science and NLCD tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms. For information on the Science data and processing steps see the Science metadata. Information on the NLCD data and processing steps are included here. </span><span>Data Download and Methods Documents: </span><span> - https://data.fs.usda.gov/geodata/rastergateway/treecanopycover/ </span></p></div></div></div>

Tags: 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, basemaps, continuous, conus, digital-spatial-data, earthcover, environment, gis, imagery, national-geospatial-data-asset, ngda, nlcd, percent-tree-canopy, remote-sensing, tcc, tree-canopy-cover
Organization: Department of Agriculture
Science Tree Canopy Cover (TCC) Conterminous United States

<div style='text-align:Left;'><div><div><p><span>The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2023-5 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The Science data - the focus of this metadata - are the initial annual model outputs that consist of two images: percent tree canopy cover (TCC) and standard error. These data are best suited for users who will carry out their own detailed statistical and uncertainty analyses on the dataset, and place lower priority on the visual appearance of the dataset for cartographic purposes. Datasets for the years 1985 through 2023 are available. The Science data were produced using a random forest regression algorithm. TCC pixel values range from  0 to  100 percent. The value 254 represents the non-processing area mask where no cloud or cloud shadow-free data are available to produce an output, and 255 represents the background value. The Science data are accessible for multiple user communities, through multiple channels and platforms. For information on the NLCD TCC data and processing steps see the NLCD metadata. Information on the Science data and processing steps are included here. </span><span>Data Download and Methods Documents: </span><span> - https://data.fs.usda.gov/geodata/rastergateway/treecanopycover/ </span></p></div></div></div>

Tags: 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, basemaps, continuous, conus, digital-spatial-data, earthcover, environment, gis, imagery, national-geospatial-data-asset, ngda, nlcd, percent-tree-canopy, remote-sensing, tcc, tree-canopy-cover
Organization: Department of Agriculture
Monitoring Trends in Burn Severity (MTBS) Hawaii

<div style='text-align:Left;'><div><div><p><span>The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of MTBS burn severity classes for all inventoried fires occurring in Hawaii during calendar year 2022. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires were not discernable from available imagery.</span></p></div></div></div>

Tags: 1992, 2000, 2002, 2003, 2005, 2007, 2009, 2012, 2015-2019, 2021-2024, ak, alaska, burn-severity, burned-area, continental-u-s, conus, differenced-normalized-burn-ratio, fire-location, fire-mapping, fire-occurrence, hawaii, hi, imagerybasemapsearthcover, landsat, location, mtbs, normalized-burn-ratio, pr, prescribed-fire, puerto-rico, sentinel, united-states, us, wildfire, wildland-fire
Organization: Department of Agriculture
Tree Canopy Cover (TCC) Science Standard Error (SE) Hawaii

<div style='text-align:Left;'><div><div><p><span>The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The Science data are the initial annual model outputs that consist of two images: percent tree canopy cover (TCC) and standard error. These data are best suited for users who will carry out their own detailed statistical and uncertainty analyses on the dataset, and place lower priority on the visual appearance of the dataset for cartographic purposes. Datasets for the years 2008 through 2021 are available. The Science data were produced using a random forests regression algorithm. For standard error data, the initial standard error estimates that ranged from 0 to approximately 45 were multiplied by 100 to maintain data precision (e.g., 45 = 4500). Therefore, standard error estimates pixel values range from 0 to approximately 4500. The value 65534 represents the non-processing area mask where no cloud or cloud shadow-free data are available to produce an output, and 65535 represents the background value. The Science data are accessible for multiple user communities, through multiple channels and platforms. For information on the NLCD TCC data and processing steps see the NLCD metadata. Information on the Science data and processing steps are included here. </span><span>Data Download and Methods Documents: </span><span> - https://data.fs.usda.gov/geodata/rastergateway/treecanopycover/ </span></p></div></div></div>

Tags: 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, basemaps, continuous, digital-spatial-data, earthcover, environment, gis, hawaii, hi, imagery, national-geospatial-data-asset, ngda, nlcd, percent-tree-canopy, remote-sensing, science, standard-error, tcc, tree-canopy-cover
Organization: Department of Agriculture
Tree Canopy Cover (TCC) Science Standard Error (SE) Puerto Rico USVI

<div style='text-align:Left;'><div><div><p><span>The USDA Forest Service (USFS) builds two versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include: The initial model outputs referred to as the Science data; And a modified version built for the National Land Cover Database and referred to as NLCD data. The Science data are the initial annual model outputs that consist of two images: percent tree canopy cover (TCC) and standard error. These data are best suited for users who will carry out their own detailed statistical and uncertainty analyses on the dataset, and place lower priority on the visual appearance of the dataset for cartographic purposes. Datasets for the years 2008 through 2021 are available. The Science data were produced using a random forests regression algorithm. For standard error data, the initial standard error estimates that ranged from 0 to approximately 45 were multiplied by 100 to maintain data precision (e.g., 45 = 4500). Therefore, standard error estimates pixel values range from 0 to approximately 4500. The value 65534 represents the non-processing area mask where no cloud or cloud shadow-free data are available to produce an output, and 65535 represents the background value. The Science data are accessible for multiple user communities, through multiple channels and platforms. For information on the NLCD TCC data and processing steps see the NLCD metadata. Information on the Science data and processing steps are included here. </span><span>Data Download and Methods Documents: </span><span> - https://data.fs.usda.gov/geodata/rastergateway/treecanopycover/ </span></p></div></div></div>

Tags: 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, basemaps, continuous, digital-spatial-data, earthcover, environment, gis, imagery, national-geospatial-data-asset, ngda, percent-tree-canopy, pr, prusvi, puerto-rico, remote-sensing, tcc, tree-canopy-cover, virgin-islands
Organization: Department of Agriculture