,

Data are derived from 2015-2019 (0 - 5 years) aerial detection surveys for tree defoliation and mortality from the USFS Forest Health Assessment and Applied Sciences Team (FHAAST) National Forest Pest Conditions Database. Polygons are created by aerial sketch mapping, and coded for defoliation and mortality, in addition to other damage codes. Defoliation and mortality layers were created from the polygon data and the attribute codes. The layers were merged to compensate for difficulties in identifying defoliation separately from mortality in hardwoods vs. conifer forests. Areas that were defoliated during three of the years recorded in the five-year dataset are thought to have significant impacts and likely mortality, so these polygons were added to the mortality layer. The layer includes areas with mortality classed as very light.

Data are derived from 2010-2014 (6-10 years) aerial detection surveys for tree defoliation and mortality from the USFS Forest Health Assessment and Applied Sciences Team (FHAAST) National Forest Pest Conditions Database. Polygons are created by aerial sketch mapping, and coded for defoliation and mortality, in addition to other damage codes. Defoliation and mortality layers were created from the polygon data and the attribute codes. The layers were merged to compensate for difficulties in identifying defoliation separately from mortality in hardwoods vs. conifer forests. Areas that were defoliated during three of the years recorded in the five-year dataset are thought to have significant impacts and likely mortality, so these polygons were added to the mortality layer. The layer includes areas with mortality classed as very light .

The percent area of a landscape analysis unit that has been identified as having tree mortality or defoliation 3 out of 5 years from USFS Forest Health Areal Detection Surveys (2015-2019).

The percent area of a landscape analysis unit that has been identified as having tree mortality or defoliation 3 out of 5 years from USFS Forest Health Areal Detection Surveys (2010-2014).

,

The 2018 National Insect and Disease Risk Map (NIDRM) developed by USFS-FHAAST indicates locations where forests are stressed and susceptible to outbreaks of native and non-native insects and diseases. These include forests with overly high stand densities, and where soil/site conditions contribute to drought. The basis for assigning risk is the expectation that 25% or more of live basal area (three times the natural background rate of mortality) will die over the next 15 years due to insects and diseases.

The USDA Forest Service (USFS) builds two versions of percent tree canopy cover (TCC) data to serve needs of multiple user communities. These datasets encompass the 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 raw model outputs referred to as the annual Science data; and - A modified version built for the National Land Cover Database referred to as NLCD data. They are available at the following locations: https://data.fs.usda.gov/geodata/rastergateway/treecanopycover https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_LandscapeAndWildlife NLCD: https://www.mrlc.gov/datahttps://apps.fs.usda.gov/fsgisx01/rest/services/RDW_LandscapeAndWildlife. 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 nominal years of 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 in unsigned 16 bit space (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.

The USDA Forest Service (USFS) builds two versions of percent tree canopy cover (TCC) data to serve needs of multiple user communities. These datasets encompass the 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 raw model outputs referred to as the annual Science data; and - A modified version built for the National Land Cover Database referred to as NLCD data. They are available at the following locations: https://data.fs.usda.gov/geodata/rastergateway/treecanopycover https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_LandscapeAndWildlife NLCD: https://www.mrlc.gov/datahttps://apps.fs.usda.gov/fsgisx01/rest/services/RDW_LandscapeAndWildlife. 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 nominal years of 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 in unsigned 16 bit space (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.

,