DHS, FIMA, FEMA’s Response Geospatial Office, Oak Ridge National Laboratory, and the U.S. Geological Survey collaborated to build and maintain the nation’s first comprehensive inventory of all structures larger than 450 square feet for use in Flood Insurance Mitigation, Emergency Preparedness and Response.

USA StructuresThis feature layer, utilizing Federal Emergency Management Agency (FEMA) data, displays footprints for all structures (buildings) greater than 450 square feet in the United States and its territories. Per FEMA, "It provides cartographic context for urban density, patterns of use, visual reference, and navigation support."Assembly Building in Dallas County, TexasData currency: 2024Data source: FEMA's USA Structures State GDB Download SiteData modification: added a State FIPS field.For more information: USA StructuresSupport documentation:MetadataHazus Inventory Technical ManualFor feedback please contact: Esri_US_Federal_Data@esri.comFederal Emergency Management AgencyPer FEMA, "We leverage a tremendous capacity to coordinate within the federal government to make sure America is equipped to prepare for and respond to disasters."

USA StructuresFEMA GIS supports the emergency management community with world-class geospatial information, services, and technologies to prepare for, protect against, respond to, recover from and mitigate against all hazards.

USA Structures This feature layer, utilizing Federal Emergency Management Agency (FEMA) data, displays footprints for all structures (buildings) greater than 450 square feet in the United States and its territories. According to FEMA, “FEMA’s Response Geospatial Office, Oak Ridge National Laboratory, and the U.S. Geological Survey collaborated to build and maintain the nation’s first comprehensive inventory of all structures larger than 450 square feet for use in Flood Insurance Mitigation, Emergency Preparedness and Response.”Note: these states and territories were updated in this cycle: Alabama, Alaska, Connecticut, Delaware, District of Columbia, Florida, Geogia, Hawaii, Iowa, Kansas, Kentucky, Louisiana, Maine, Michigan, Minnesota, Mississippi, Montana, Nebraska, New Hampshire, New Mexico, New York, North Carolina, North Dakota, Oregon, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Washington, West Virginia, Wisconsin, Wyoming, Puerto Rico, Virginia, Virgin Islands, Guam, American Samoa, and Northern Mariana Islands.Assembly Building in Dallas County, TexasData currency: June 6, 2025Data source: FEMA's USA Structures State GDB Download SiteData modification: added State FIPS, PROP_CNTY, and Global ID fields. The field type was changed from string to integer for POP_MEDIAN, POP_CI95_lower, POP_CI95_UPPER.For more information: USA StructuresSupport documentation:MetadataHazus Inventory Technical Manual For feedback please contact: Esri_US_Federal_Data@esri.com Federal Emergency Management Agency Per FEMA, “We leverage a tremendous capacity to coordinate within the federal government to make sure America is equipped to prepare for and respond to disasters.”

USGS Structures from The National Map (TNM) consists of data to include the name, function, location, and other core information and characteristics of selected manmade facilities across all US states and territories. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations. Structures currently included are: School, School:Elementary, School:Middle, School:High, College/University, Technical/Trade School, Ambulance Service, Fire Station/EMS Station, Law Enforcement, Prison/Correctional Facility, Post Office, Hospital/Medical Center, Cabin, Campground, Cemetery, Historic Site/Point of Interest, Picnic Area, Trailhead, Vistor/Information Center, US Capitol, State Capitol, US Supreme Court, State Supreme Court, Court House, Headquarters, Ranger Station, White House, and City/Town Hall. Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. Included is a feature class of preliminary building polygons provided by FEMA, USA Structures. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The National Map viewer allows free downloads of public domain structures data in either Esri File Geodatabase or Shapefile formats. For additional information on the structures data model, go to https://www.usgs.gov/ngp-standards-and-specifications/national-map-structures-content.

USA Structures: OR (2023) Copy of https://disasters.geoplatform.gov/publicdata/Partners/ORNL/USA_Structures/ (Accessed Oct, 24,2023)

This feature layer, utilizing Federal Emergency Management Agency data, displays footprints for all structures (buildings) greater than 450 square feet in the United States and its territories. This layer is checked annually for updates.

The table VA_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 3234910 rows across 29 variables.

The table NV_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 997408 rows across 29 variables.

The table SD_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 629348 rows across 29 variables.

The table NH_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 561848 rows across 29 variables.

Building footprints from the 2011 LiDAR project. Includes outlines of buildings with an area of 40 square feet or greater. Automated classification of buildings performed using TerraScan. Manual cleanup of building classification was then carried out within point cloud data using TerraScan or LP360. Building footprints were digitized automatically using the LP360 building extraction feature. Footprints cleaned up manually using ArcGIS.This dataset is static and has not been edited since its original delivery.

The table NY_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 5015975 rows across 29 variables.

See the USA Structures Overview.Data source: FEMA's USA Structures State GDB Download Site

Medical Emergency Response StructuresThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey, displays hospitals, medical centers, ambulance services, fire stations and EMS stations in the U.S. Per the USGS, "Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations."Greendale Fire DepartmentData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Medical & Emergency Response) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 135 (USGS National Structures Dataset - USGS National Map Downloadable Data Collection)OGC API Features Link: (Medical Emergency Response Structures - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: The National MapFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Theme CommunityThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

The table MI_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 4925410 rows across 29 variables.

These data are a compilation of fishway structures collected by the Atlantic States Marine Fisheries Commission state representatives at the request of the U.S. Geological Survey. The variables included within this dataset range from locality information and structure metadata (eg. latitude/longitude and year of construction) to metrics specifically about the fishway structure (eg. fishway width). The dataset ranges in dates of construction from 1882 to 2020 and includes fishways from all states on the eastern coast of the United States.

The table TN_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 3187867 rows across 29 variables.

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.

The table TX_Structures is part of the dataset USA Structures, available at https://stanford.redivis.com/datasets/d3cy-a7gxn1165. It contains 11597857 rows across 29 variables.