Oak Ridge National Laboratory 20230831 AS_Structures vector digital data Federal Emergency Management Agency FEMA 20230831 USA Structure Inventory GIS Data Project/Collection This feature class contains structure (building) polygons for the state/territory of Americansamoa. This update (as of 8/31/2023) is provided with additional attributions, where available: OCC_CLS, PRIM_OCC, PROP_ADDR, PROP_CITY, PROP_ZIP, and PROP_ST. They have been populated with the best available data from sources cited in the source section. The structures (buildings) are represented by polygon geometries with an attribute table described elsewhere in the metadata. This dataset was created to inventory all structures in the US and its territories whose size is greater than 450 square feet. It provides cartographic context for urban density, patterns of use, visual reference, and navigation support. 20130101 20200520 Time period date range corresponds to the IM_DATE field of the feature class. Complete As Needed -171.088269171 -169.42060225 -11.05585234 -14.363202835 None homeland security homeland defense emergency response structures building outlines USA structures None United States and Territories USA Americansamoa None None Federal Emergency Management Agency – Response Geospatial Office Mailing and Physical
500 C St SW
Washington DC DC 20024 United States 202-341-1426 Oak Ridge National Laboratory Mailing and Physical
One Bethel Valley Rd, MS-6017
Oak Ridge TN 37831 United States 865-341-0013 865-241-6261 Oak Ridge National Laboratory (ORNL); Federal Emergency Management Agency (FEMA) Geospatial Response Office Version 6.2 (Build 9200) ; Esri ArcGIS 10.5.1.7333 No formal attribute accuracy test was conducted. Data from the authoritative sources are assumed to be correct and accurate. No formal logical consistency tests were conducted. No formal completeness tests were conducted; however, data capture is complete as of the most recent date indicated in the Time Period section. None; however, the horizontal positional accuracy of derived features is directly correlated to the accuracy of the imagery used to extract the feature. WorldView-2 and WorldView-3 sensors have a reported geolocation accuracy of less than 3.5 meters. NAIP reports a horizontal accuracy of at least 5 meters within a 1 meter ground sample distance. None; however, the vertical positional accuracy correlates to the accuracy of LiDAR and other elevation sources used to derive vertical information. National Geospatial-Intelligence Agency 20160101 Building Footprints vector digital data Observed 133 Cities Geometries and height information were included U.S. Department of Agriculture 20030101 NAIP Digital Ortho Photo Image remote-sensing image Observed NAIP Input Imagery from which features were extracted Maxar 20140813 WorldView-3 remote-sensing image 20130101 20200520 Observed WV03 Input Imagery from which features were extracted Maxar 20091108 WorldView-2 remote-sensing image 20130101 20200520 Observed WV02 Input Imagery from which features were extracted LightBox 20210601 SmartParcels vector digital data 20210601 20210601 publication date LBPD A spatial intersection for occupancy classification with aggregated land use codes where appropriate Homeland Infrastructure Foundation-Level Data (HIFLD) 20230301 HIFLD Open Data vector digital data 20090101 20220608 publication date HIFLD A spatial intersection for occupancy classification U.S. Census Bureau 20211229 Census Housing Unit Data vector digital data 20100101 20100101 publication date Census HU A spatial intersection for occupancy classification U.S. Census Bureau 20211229 TIGER/Line Shapefiles vector digital data 20210201 20210201 publication date Census tracts GEOID and FIPS included via spatial join U.S. Department of Transportation 20230312 National Address Database Digital N/A N/A Publication Date NAD Street Number, Street Name, Zip, and City where appropriate Scalable High-Resolution Imagery-Based Building Extraction Pipeline (SCRIBE): High-resolution multispectral imagery is obtained for the area of interest. The raw imagery (Level-1B product) is then pan-sharpened and orthorectified. Complete coverage with minimal cloud cover includes overhead imagery and LiDAR-derived footprints with a spatial resolution less than 0.7 meters. Once imagery pre-processing completes, high performance computing (HPC) environments at ORNL are used to apply a convolutional neural network (CNN) model to the imagery to automatically extract structure boundaries. 20200430 Verification and Validation Model (VVM): Verification and validation of the output produced from SCRIBE is conducted by a machine learning model to remove potential false positives. 20200506 Regularization: The visual representation of the structures has been improved to represent structure geometry more accurately as compared to the imagery-derived raster representations from the SCRIBE pipeline. This step also reduces the number of vertices represented by a structure, thus reducing file size and improving render speeds. 20200506 Attribution and Metadata: Population of some attributes is incomplete and identified in the Entity and Attribute Information section of this metadata. 20211229 Phase 2 attribute expansion: Population of OCC_CLS, PRIM_OCC, PROP_ADDR, PROP_CITY, PROP_ZIP, and PROP_ST with best available data. Coverage of address related fields maybe incomplete. 20230831 Vector Simple FALSE 0 TRUE FALSE 8.983152841195215e-009 8.983152841195215e-009 Decimal Degrees D WGS 1984 WGS 1984 6378137.0 298.257223563 AS_Structures NA NA Feature Class 0 OBJECTID Internal feature number. Esri Sequential unique whole numbers that are automatically generated. OBJECTID OID 4 0 0 Shape Feature geometry. Esri Coordinates defining the features. SHAPE Geometry 0 0 0 BUILD_ID Unique ID for each feature. Oak Ridge National Laboratory BUILD_ID Integer 4 0 0 OCC_CLS This identifies the top level building occupancy class as defined by Locations: Building Occupancy Classification; FEMA Data Standard; July 31, 2018. Oak Ridge National Laboratory Locations: Building Occupancy Classification; FEMA Data Standard; July 31, 2018 Contact FEMA at 500 C Street SW, Washington, DC 20024, 202-341-1426 OCC_CLS String 20 0 0 PRIM_OCC This identifies the primary descriptor for a building's usage for each top level building occupancy class as defined by Locations: Building Occupancy Classification; FEMA Data Standard; July 31, 2018. Oak Ridge National Laboratory Locations: Building Occupancy Classification; FEMA Data Standard; July 31, 2018 Contact FEMA at 500 C Street SW, Washington, DC 20024, 202-341-1426 PRIM_OCC String 35 0 0 SEC_OCC This describes the range of units within Multi Family Dwelling and Temporary Lodging descriptors for Residential building occupancy class as defined by Locations: Building Occupancy Classification; FEMA Data Standard; July 31, 2018. NONE. NOT CURRENTLY POPULATED Locations: Building Occupancy Classification; FEMA Data Standard; July 31, 2018 Contact FEMA at 500 C Street SW, Washington, DC 20024, 202-341-1426 SEC_OCC String 13 0 0 PROP_ADDR Primary street address for a structure (i.e. 5th Avenue and Main Street). National Address Database PROP_ADDR String 80 0 0 PROP_CITY City name. National Address Database PROP_CITY String 50 0 0 PROP_ST State name. Census 2020 tiger shapefiles PROP_ST String 50 0 0 PROP_ZIP Zip code (5 digit). National Address Database US Postal Zip Codes United States Postal Service (https://www.usps.com) PROP_ZIP String 50 0 0 OUTBLDG A non-primary structure or outbuilding such as a garage, shed or other accessory building. NONE. NOT CURRENTLY POPULATED OUTBLDG String 13 0 0 HEIGHT This is a measure of the height (in meters) of the structure as determined from LiDAR or other source data. LiDAR-derived footprints where available provided by NGA HEIGHT Single 4 0 0 SQMETERS This is the two-dimensional area of the building in square meters. Field populated using PCS:USA_Contiguous_Albers_Equal_Area_Conic_USGS based on pre-regularized geometries Oak Ridge National Laboratory SQMETERS Single 4 0 0 SQFEET This is the two-dimensional area of the building in square feet. Field populated using PCS:USA_Contiguous_Albers_Equal_Area_Conic_USGS based on pre-regularized geometries Oak Ridge National Laboratory SQFEET Single 4 0 0 H_ADJ_ELEV This is the highest elevation (in meters) of the ground adjacent to the structure as estimated from available elevation data. NONE. NOT CURRENTLY POPULATED H_ADJ_ELEV Single 4 0 0 L_ADJ_ELEV This is the lowest elevation (in meters) of the ground adjacent to the structure as estimated from available elevation data. NONE. NOT CURRENTLY POPULATED L_ADJ_ELEV Single 4 0 0 FIPS US County Federal Information Processing Standards (FIPS) Code (5 digit). Oak Ridge National Laboratory 2020 FIPS Codes for Counties and County Equivalent Entities FIPS/Census (http://www.census.gov/geo/reference/codes/cou.html) FIPS String 13 0 0 CENSUSCODE Census tract identifier; a concatenation of current state Federal Information Processing Series (FIPS) code, county FIPS code, and census tract code. Oak Ridge National Laboratory United States Census Tracts 2020 Census (https://www.census.gov/geo/reference/gtc/gtc_ct.html) CENSUSCODE String 20 0 0 PROD_DATE The date that the structure/feature was captured using automated methods (MM/DD/YYYY). Oak Ridge National Laboratory PROD_DATE Date 8 0 0 SOURCE This is the name of the contractor or the government agency that created the feature. Oak Ridge National Laboratory SOURCE String 50 0 0 USNG United States National Grid Coordinate. Oak Ridge National Laboratory USNG String 50 0 0 LONGITUDE Longitude of located point on centroid of structure in millionths of decimal degrees. Oak Ridge National Laboratory LONGITUDE Double 8 0 0 LATITUDE Latitude of located point on centroid of structure in millionths of decimal degrees. Oak Ridge National Laboratory LATITUDE Double 8 0 0 IMAGE_NAME The catalog ID from the Maxar commercial imagery, or the name of the image from National Agriculture Imagery Program (NAIP) imagery used to extract structures. LiDAR-derived footprints provided by the National Geospatial Intelligence Agency (NGA). For LiDAR-derived footprints, the first portion of the name ('LiXXX') denotes the Homeland Infrastructure Foundation-Level Data (HIFLD) production code while the latter portion is the city/project covered. Maxar, USDA, or NGA IMAGE_NAME String 50 0 0 IMAGE_DATE This is the date of the imagery or LiDAR from which the building outline was captured (MM/DD/YYYY). Maxar, USDA, or NGA IMAGE_DATE Date 8 0 0 VAL_METHOD Methodology used to validate building outline as a true positive. Oak Ridge National Laboratory Manual A manual visual inspection using the image in IMAGE_NAME to validate building outline as a true positive. Oak Ridge National Laboratory Automated Feature was evaluated by an algorithm. The algorithm generates probabilities representing the likelihood of each feature being a true positive. Features that have a 50% or higher chance of being a true positive are excluded from the review process and are assumed to be valid. Oak Ridge National Laboratory Unverified Feature has not been formally reviewed. Oak Ridge National Laboratory VAL_METHOD String 50 0 0 REMARKS This is comments that cannot be captured by existing data fields. Oak Ridge National Laboratory REMARKS String 500 0 0 UUID Universally Unique Identifier (method 4); a 128-bit id label coded in hexadecimal as a string in '{8-4-4-4-12}' format. Each structure within the complete USA Structures database will have a unique UUID. https://datatracker.ietf.org/doc/html/rfc4122.html Oak Ridge National Laboratory UUID String 50 0 0 Shape_Length Length of feature in internal units. Esri Positive real numbers that are automatically generated. SHAPE_Length Double 8 0 0 Shape_Area Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. SHAPE_Area Double 8 0 0 20230331 Oak Ridge National Laboratory Mailing and Physical
One Bethel Valley Rd, MS-6017
Oak Ridge TN 37831 USA 865-341-0013 865-241-6261 FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time Esri ArcGIS 13.1.3.41833 AS_Tsunami_NonInundatedStructures_CopyFeatures 1 -171.088269 -169.420602 -11.055852 -14.363203 This Feature Layer contains modeled tsunami inundation for structures on American Samoa. It is based on modeling on the September 2009 Tsunami that impacted American Samoa and contains FEMA's structures dataset.  (Scenario) Modeled tsunami inundatin for American Samoa's Non Inundated Structures NOAA, FEMA FEMA R9American SamoaStructuresNOAATsunami AS_Tsunami_NonInundatedStructures_CopyFeatures 002 -171.088269 -169.420602 -14.363203 -11.055852 1 Geographic GCS_WGS_1984 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' 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