Inactive

The USCB Awarded a firm-fixed-price contract on a sole source basis to Loveland Technologies LLC Doing Business As (DBA Regrid) for the purchase of combined parcel and building footprint data. This ac... The USCB Awarded a firm-fixed-price contract on a sole source basis to Loveland Technologies LLC Doing Business As (DBA Regrid) for the purchase of combined parcel and building footprint data. This acquisition is conducted under the authority of 41 U.S.C. 3304(a)(1) as implemented by the Federal Acquisition Regulation (FAR) 6.302-1 entitled, “Only one responsible source and no other supplier or services will satisfy agency requirements.” The United States Census Bureau’s Geography Division (GEO) is responsible for collecting and maintaining the geographic data necessary to support agency programs and initiatives. Over 40,000 tribal, state, and local governments contribute to the geographic information managed by the USCB by providing regular input and feedback on the USCB’s boundaries, streets, and addresses. GEO analyzes and updates the geospatial data (address and spatial) for the Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) system and in support of all USCB censuses and surveys. This geographic base contributes to the efficient and accurate collection and tabulation of data for the Decennial Census, the American Community Survey (ACS), the Economic Census, and annual estimates and surveys such as the Population Estimates Program (PEP). GEO is responsible for the analysis of numerous geographic data inputs to enhance the MAF/TIGER system. Rich property-level attribution and spatial precision of the parcel data offers us the opportunity to isolate, prioritize, and correct problematic areas within the Master Address File (MAF), thus reducing the need for field work prior to the 2030 Census. This dataset also provides a significant opportunity to automate portions of the existing in-office Parcel Address Matching Service (PAMS) project by leveraging the links provided between structures and parcels, improving the geocoding of addresses, and ensuring more accurate locations for those addresses which we already have in the MAF/TIGER system.