Grid of population density in the conterminous United States at a resolution of one kilometer. The grid was converted from an ASCII file obtained from the Consortium for International Earth Science Information Network (CIESIN).

The SACS Population Index depicts the 2015 Census – American Community Survey data as population density. This population density is calculated as persons per square mile, per census tract. The census tracts depicted are within the USACE South Atlantic Coastal Study boundaries with an inland extent of NOAA’s Category 5 Maximum of Maximum Storm Surge Hazard Layer. The index ranks all census tracts within the SACS study area on a percentile index by population density. These data are represented on a normalized scale of 0 to 1, with 1 being the most densely populated census tract in the study area, and zero being the least densely populated census tract. The census tract feature dataset is converted to a 30m-by-30m raster grid for aggregation with other SACS datasets.This Tier 1 dataset is available for download here:Tier 1 Risk Assessment Download

The USACE SACS Population and Infrastructure Exposure Index combines the normalized score of each Infrastructure and Population Index, and then re-normalizes these values across the study area.The SACS Infrastructure Exposure Index was created by spatially joining 52 infrastructure datasets from DHS’s HIFLD database and Military Installation Ranges and Training Areas from the DOD OSD to census tracts across the study area. The infrastructure elements were assigned a weighting value consistent with the NACCS Tier 1 Methodology (URL). The weighted infrastructure element values were then aggregated by count within each census tract, and then divided by the census tract area to generate an infrastructure density value. This infrastructure density value was then enumerated and ranked across all census tracts, and normalized to 0 to 1 using these rankings. The census tract feature dataset was then converted to a grid using these normalized values for aggregation with other SACS datasets.The SACS Population Exposure Index depicts the 2015 Census – American Community Survey data as population density. This population density is calculated as persons per square mile, per census tract. The census tracts depicted are within the USACE South Atlantic Coastal Study boundaries with an inland extent of NOAA’s Category 5 Maximum of Maximum Storm Surge Hazard Layer. The index ranks all census tracts within the SACS study area on a percentile index by population density. These data are represented on a normalized scale of 0 to 1, with 1 being the most densely populated census tract in the study area, and zero being the least densely populated census tract. The census tract feature dataset was then converted to a grid using these normalized values for aggregation with other SACS datasets.References:DHS HIFLDhttps://gii.dhs.gov/hifld/DOD OSDhttps://www.acq.osd.mil/dodsc/fast41_gisdatasets.htmlUS Censushttps://www.census.gov/NACCS (appendix C, page 107)https://www.nad.usace.army.mil/Portals/40/docs/NACCS/NACCS_Appendix_C.pdfThis Tier 1 dataset is available for download here:Tier 1 Risk Assessment Download

The data included in this publication depict components of wildfire risk specifically for populated areas in the United States. These datasets represent where people live in the United States and the in situ risk from wildfire, i.e., the risk at the location where the adverse effects take place.National wildfire hazard datasets of annual burn probability and fire intensity, generated by the USDA Forest Service, Rocky Mountain Research Station and Pyrologix LLC, form the foundation of the Wildfire Risk to Communities data. Vegetation and wildland fuels data from LANDFIRE 2020 (version 2.2.0) were used as input to two different but related geospatial fire simulation systems. Annual burn probability was produced with the USFS geospatial fire simulator (FSim) at a relatively coarse cell size of 270 meters (m). To bring the burn probability raster data down to a finer resolution more useful for assessing hazard and risk to communities, we upsampled them to the native 30 m resolution of the LANDFIRE fuel and vegetation data. In this upsampling process, we also spread values of modeled burn probability into developed areas represented in LANDFIRE fuels data as non-burnable. Burn probability rasters represent landscape conditions as of the end of 2020. Fire intensity characteristics were modeled at 30 m resolution using a process that performs a comprehensive set of FlamMap runs spanning the full range of weather-related characteristics that occur during a fire season and then integrates those runs into a variety of results based on the likelihood of those weather types occurring. Before the fire intensity modeling, the LANDFIRE 2020 data were updated to reflect fuels disturbances occurring in 2021 and 2022. As such, the fire intensity datasets represent landscape conditions as of the end of 2022. The data products in this publication that represent where people live, reflect 2021 estimates of housing unit and population counts from the U.S. Census Bureau, combined with building footprint data from Onegeo and USA Structures, both reflecting 2022 conditions.The specific raster datasets included in this publication include:Building Count: Building Count is a 30-m raster representing the count of buildings in the building footprint dataset located within each 30-m pixel.Building Density: Building Density is a 30-m raster representing the density of buildings in the building footprint dataset (buildings per square kilometer [km²]). Building Coverage: Building Coverage is a 30-m raster depicting the percentage of habitable land area covered by building footprints.Population Count (PopCount): PopCount is a 30-m raster with pixel values representing residential population count (persons) in each pixel.Population Density (PopDen): PopDen is a 30-m raster of residential population density (people/km²).Housing Unit Count (HUCount): HUCount is a 30-m raster representing the number of housing units in each pixel.Housing Unit Density (HUDen): HUDen is a 30-m raster of housing-unit density (housing units/km²).Housing Unit Exposure (HUExposure): HUExposure is a 30-m raster that represents the expected number of housing units within a pixel potentially exposed to wildfire in a year. This is a long-term annual average and not intended to represent the actual number of housing units exposed in any specific year.Housing Unit Impact (HUImpact): HUImpact is a 30-m raster that represents the relative potential impact of fire to housing units at any pixel, if a fire were to occur. It is an index that incorporates the general consequences of fire on a home as a function of fire intensity and uses flame length probabilities from wildfire modeling to capture likely intensity of fire.Housing Unit Risk (HURisk): HURisk is a 30-m raster that integrates all four primary elements of wildfire risk - likelihood, intensity, susceptibility, and exposure - on pixels where housing unit density is greater than zero.Additional methodology documentation is provided with the data publication download. Metadata and Downloads: (https://www.fs.usda.gov/rds/archive/catalog/RDS-2020-0060-2).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.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.