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MTBS Wildfire Burn Severity Mosaics
Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.�Map Services
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Monitoring Trends in Burn Severity Conterminous United States (Map Service)
공공데이터포털
Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.,
Monitoring Trends in Burn Severity Hawaii (Map Service)
공공데이터포털
Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.�Direct Download
Monitoring Trends in Burn Severity Alaska (Map Service)
공공데이터포털
Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.
Monitoring Trends in Burn Severity Puerto Rico (Map Service)
공공데이터포털
Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.�Direct Download
MTBS Wildfire Occurrence
공공데이터포털
The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2018. 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 vector point of the location of all currently inventoried and mappable fires occurring between calendar year 1984 and 2018 for the continental United States, Alaska, Hawaii and Puerto Rico. The point location represents the geographic centroid for the _BURN_AREA_BOUNDARY polygon(s) associated with each fire. Map Service Feature Layer
MTBS Wildfire Burned Area Boundaries
공공데이터포털
The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period between 1984 and the current MTBS release. 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 vector polygon of the location of all currently inventoried and mappable MTBS fires occurring between calendar year 1984 and the current MTBS release for the continental United States, Alaska, Hawaii and Puerto Rico. Map Service Feature Layer
Terrestrial Condition Assessment (TCA) Uncharacteristic Fire Severity Moderate (Map Service)
공공데이터포털
The LANDFIRE Percent Mixed-Severity Fire (PMS) raster dataset (LF US_120_PMS) was combined with the Monitoring Trends in Burn Severity (MTBS) data (1984-2017) to identify areas that have experienced unnaturally severe wildfires in the recent past (1984-2017). Areas mapped are greater than 50% Mixed-Severity Fire and a high severity fire MTBS mapped fire at the same location.
LANDFIRE Remap Forest Canopy Cover (CC) Marshall Islands
공공데이터포털
LANDFIRE's (LF) 2016 Remap (Remap) Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand, CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. In disturbed locations CC is calculated from linear regression equations derived from Forest Vegetation Simulator (FVS) plot data output, but at non-disturbed locations it is assigned the midpoint of Fuel Vegetation Cover (FVC) forested classes. In some instances, LF Remap assumes the potential burnable biomass in the tree canopy has been accounted for in the surface fuel model. For example, young or short conifer stands where the trees are represented by a shrub type fuel model will not have canopy characteristics. LF Remap Annual Disturbance products are incorporated into CC to provide informed changes by disturbance type, severity, and time since disturbance (TSD). Annual Disturbance products provide a pre-disturbance scenario represented by LF Remap existing vegetation products. Reporting of the pre-disturbance scenario helps to calculate CC, by providing information about vegetation impacted by a disturbance. Then, vegetation adjustments are modeled in disturbance areas based on disturbance type and severity. CC is then used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CC supplies information to fire behavior models in order to; determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. CC also has capable fuels functionality. Capable fuels calculate TSD assignments for disturbed areas using an "effective year." For example, year 2020 fuels may be calculated for the year 2020. the new process considers all the existing disturbances included in LF Remap and adjusts the TSD for these to the effective year (2020 in the example), making the products "2020 capable fuels." More information about capable fuels can be found at https://www.landfire.gov/lf_remap.php.
LANDFIRE Remap Forest Canopy Cover (CC) Marshall Islands
공공데이터포털
LANDFIRE's (LF) 2016 Remap (Remap) Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand, CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. In disturbed locations CC is calculated from linear regression equations derived from Forest Vegetation Simulator (FVS) plot data output, but at non-disturbed locations it is assigned the midpoint of Fuel Vegetation Cover (FVC) forested classes. In some instances, LF Remap assumes the potential burnable biomass in the tree canopy has been accounted for in the surface fuel model. For example, young or short conifer stands where the trees are represented by a shrub type fuel model will not have canopy characteristics. LF Remap Annual Disturbance products are incorporated into CC to provide informed changes by disturbance type, severity, and time since disturbance (TSD). Annual Disturbance products provide a pre-disturbance scenario represented by LF Remap existing vegetation products. Reporting of the pre-disturbance scenario helps to calculate CC, by providing information about vegetation impacted by a disturbance. Then, vegetation adjustments are modeled in disturbance areas based on disturbance type and severity. CC is then used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CC supplies information to fire behavior models in order to; determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. CC also has capable fuels functionality. Capable fuels calculate TSD assignments for disturbed areas using an "effective year." For example, year 2020 fuels may be calculated for the year 2020. the new process considers all the existing disturbances included in LF Remap and adjusts the TSD for these to the effective year (2020 in the example), making the products "2020 capable fuels." More information about capable fuels can be found at https://www.landfire.gov/lf_remap.php.
LANDFIRE Remap Forest Canopy Cover (CC) Marshall Islands
공공데이터포털
LANDFIRE's (LF) 2016 Remap (Remap) Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand, CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. In disturbed locations CC is calculated from linear regression equations derived from Forest Vegetation Simulator (FVS) plot data output, but at non-disturbed locations it is assigned the midpoint of Fuel Vegetation Cover (FVC) forested classes. In some instances, LF Remap assumes the potential burnable biomass in the tree canopy has been accounted for in the surface fuel model. For example, young or short conifer stands where the trees are represented by a shrub type fuel model will not have canopy characteristics. LF Remap Annual Disturbance products are incorporated into CC to provide informed changes by disturbance type, severity, and time since disturbance (TSD). Annual Disturbance products provide a pre-disturbance scenario represented by LF Remap existing vegetation products. Reporting of the pre-disturbance scenario helps to calculate CC, by providing information about vegetation impacted by a disturbance. Then, vegetation adjustments are modeled in disturbance areas based on disturbance type and severity. CC is then used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). CC supplies information to fire behavior models in order to; determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. CC also has capable fuels functionality. Capable fuels calculate TSD assignments for disturbed areas using an "effective year." For example, year 2020 fuels may be calculated for the year 2020. the new process considers all the existing disturbances included in LF Remap and adjusts the TSD for these to the effective year (2020 in the example), making the products "2020 capable fuels." More information about capable fuels can be found at https://www.landfire.gov/lf_remap.php.