Oak Ridge National Laboratory
20230331
DC_Structures
vector digital data
Federal Emergency Management Agency FEMA
20230331
USA Structure Inventory
GIS Data Project/Collection
This feature class contains structure (building) polygons for the state/territory of Districtofcolumbia. This update (as of 3/31/2023) 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.
20080312
20191104
Time period date range corresponds to the IM_DATE field of the feature class.
As Needed
-77.115089792
-76.909713404
38.99553671
38.793069427
None
homeland security
homeland defense
emergency response
structures
building outlines
USA structures
None
United States and Territories
USA
Districtofcolumbia
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
20080312
20120925
Observed
133 Cities
Geometries and height information were included
U.S. Department of Agriculture
20030101
NAIP Digital Ortho Photo Image
remote-sensing image
20140927
20140927
Observed
NAIP
Input Imagery from which features were extracted
Maxar
20140813
WorldView-3
remote-sensing image
20190219
20191104
Observed
WV03
Input Imagery from which features were extracted
Maxar
20091108
WorldView-2
remote-sensing image
20190219
20191104
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
20221031
20221031
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.
20230331
Vector
Simple
FALSE
0
TRUE
FALSE
D WGS 1984
WGS 1984
6378137.0
298.257223563
DC_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
Building 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
Building Occupancy Classification
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
Primary Occupancy
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
Secondary Occupancy
String
13
0
0
PROP_ADDR
Primary street address for a structure (i.e. 5th Avenue and Main Street).
National Address Database
Address
String
80
0
0
PROP_CITY
City name.
National Address Database
City
String
50
0
0
PROP_ST
State name.
Census 2020 tiger shapefiles
State
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)
ZIP Code
String
50
0
0
OUTBLDG
A non-primary structure or outbuilding such as a garage, shed or other accessory building.
NONE. NOT CURRENTLY POPULATED
Outbuilding or Non-Primary Structure
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 (meters)
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
Square Meters
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
Square Feet
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
Highest Elevation (in Meters) of the Ground Adjacent to the Structure
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
Lowest Elevation (in Meters) of the Ground Adjacent to the Structure
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)
County Federal Information Processing Standards (FIPS) Code
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)
Census Tract Identifier
String
20
0
0
PROD_DATE
The date that the structure/feature was captured using automated methods (MM/DD/YYYY).
Oak Ridge National Laboratory
Production 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
United States National Grid (USNG) Coordinates
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
Methodology Used to Validate Building Outline
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
Universally Unique Identifier (UUID)
String
50
0
0
STATE_FIPS
State FIPS
String
255
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 13.1.2.41833
Structures
This feature class contains structure (building) polygons for the state/territory of Districtofcolumbia. This update (as of 3/31/2023) 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.
FEMA
Structures
Buildings
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.
<div><div><b><i><span style='font-size:11.0pt; color:black;'>Disclaimer:</span></i></b><i><span style='font-size:11.0pt; color:black;'> Please be advised that the data contained
in Walla Walla County’s Geographic Information System (GIS) is subject to
constant change and that Walla Walla County, its agents, consultants, contractors,
or employees collectively referred to as “the County” do not guarantee that the
information presented is accurate or complete. All data contained in the
County’s GIS is provided by the County AS IS without warranty of any kind,
implied or express, as to the information being accurate or complete. With
knowledge of the foregoing, by proceeding to use the County’s GIS, each user agrees
to waive, release and indemnify Walla Walla County, its agents, consultants,
contractors or employees from any and all claims, actions, or causes of action
for damages or injury to persons or property arising from the use or inability
to use Walla Walla County’s GIS data. Walla Walla County will not be
responsible for any data distributed by others. The release of data to the
requestor does not authorize the party to redistribute or resell or act as an
agent for any data received from the County.</span></i></div></div>
-119.025994946436
-117.994752058223
46.5953317472418
46.0006603747221
Structures
002
Projected
GCS_WGS_1984
Linear Unit: Meter (1.000000)
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WGS_1984_Web_Mercator_Auxiliary_Sphere
20230828
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20230828
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File Geodatabase Feature Class
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