98 datasets found
  1. d

    Community Planning and Development (CPD) Maps System

    • catalog.data.gov
    • datasets.ai
    Updated Mar 11, 2026
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    U.S. Department of Housing and Urban Development (2026). Community Planning and Development (CPD) Maps System [Dataset]. https://catalog.data.gov/dataset/the-cpd-maps-system
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    Dataset updated
    Mar 11, 2026
    Dataset provided by
    U.S. Department of Housing and Urban Development
    Description

    CPD Maps includes data on the locations of existing CDBG, HOME, public housing and other HUD-funded community assets, so that users can view past investments geographically when considering various strategies for future funding. CPD Maps offers a large amount of data in a way that is easy to access. The website allows grantees and the general public to easily search, query, and display information to identify trends and analyze the needs of their community.

  2. Estimated Housing Authority Service Areas

    • hudgis-hud.opendata.arcgis.com
    • data.lojic.org
    • +2more
    Updated Aug 7, 2023
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    Department of Housing and Urban Development (2023). Estimated Housing Authority Service Areas [Dataset]. https://hudgis-hud.opendata.arcgis.com/datasets/HUD::estimated-housing-authority-service-areas-1/about
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    Dataset updated
    Aug 7, 2023
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    The data provided herein denotes the estimated service areas for all Public Housing Authorities (PHA) receiving assistance through the U.S. Department of Housing and Urban Development (HUD) (excluding Guam, the Marshall Islands, and the U.S. Virgin Islands). HUD’s Office of Policy Development and Research (PD&R) developed this dataset in response to repeated requests from HUD staff, researchers, and external partners. This is an experimental dataset that is designed to aid researchers in studying the HUD-funded Public Housing and Housing Choice Voucher programs. The methodology and the service areas themselves have not been validated by HUD’s Office of Public and Indian Housing (PIH) or the Public Housing Agencies. PD&R welcomes engagement from internal and external stakeholders on the continued refinement and development of this dataset. Please send any comments or questions to GISHelpDesk@hud.gov. Standards used to estimate PHA primary service areas are as follows: State-Level Public Housing Authorities:For the purposes of this dataset State-Level PHAs are identified through either their name, or their PHA Code also known as the Participant Code. Any PHA whose name contains the word “State”, or whose PHA Code begins with a ‘9’ (not including the two-character state code that begins the PHA code) is considered a State-Level PHA, and the service area therefore includes the entirety of that state. County-Level Public Housing Authorities:For the purposes of this dataset County-Level PHAs are identified as any PHA containing the word ‘County’ or ‘COUNTY’ in the organization’s formal name. The service area of a County-Level PHA includes the entire county after which the PHA is named, or the county which contains the majority of the units (combined low-rent and voucher) administered by the PHA. Moreover, a PHA that administers units located in jurisdictions outside the county for which the PHA is named, or the county which contains the majority of the units administered by the PHA, does not include those extraterritorial jurisdictions as part of its service area . Subsequently, the estimated service areas of housing authorities operating at a regional level, that is operating in multiple counties (contiguous or otherwise), are relegated to a single county. Local-Level Public Housing Authorities:For the purposes of this dataset Local-Level PHAs are identified as any PHA that does not fall into the category of State-Level or County-Level Public Housing Authority as described above. The service area for a Local-Level PHA is first defined as the primary Unit of General Local Government (UGLG) served by the PHA. The primary local government jurisdiction is defined as the UGLG that contains the largest share of total units (combined low-rent and voucher) administered by that PHA. However, in cases where greater than 20% of units administered by that PHA are located outside of the primary local government jurisdiction served by the PHA, the PHA’s service area is defined as the entirety of the county that the primary local government is located in.Please note, that the methods used to compile the estimated local PHA service areas illustrated in this dataset remain the same regardless of a state’s allowance for state-wide voucher portability.

  3. HUD Section 202 Properties

    • data.lojic.org
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +2more
    Updated Aug 11, 2023
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    Department of Housing and Urban Development (2023). HUD Section 202 Properties [Dataset]. https://data.lojic.org/items/822a5ca2f29e4ecb8ffd80b90c89b729
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    Dataset updated
    Aug 11, 2023
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    This map denotes the locations of HUD assisted Multi-Family properties that primarily serve elderly residents. In addition, each property illustrated through this service has at least one active Service Coordinator contract or grant, Section 236 loan, Section 8 202 contract, Section 8 Farmers Home Administration (FMHA) 515 contract, Section 8 New Construction contract, Section 202 Project Assistance Contracts (PAC) contract, and Section 202 Project Rental Assistance Contract (PRAC).Please note that the data provided through this map only includes location data and attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to a ZIP+4 centroid location. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD.To learn more about the Section 202 Program visit: https://www.hud.gov/program_offices/housing/mfh/progdesc/eld202Data Dictionary: DD_Multifamily Properties Date of Coverage: 12/2025 Data Updated: 01/2026

  4. c

    HUD Revitalization Areas by Census Block Group

    • data.cityofrochester.gov
    • hub.arcgis.com
    Updated Feb 7, 2022
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    Open_Data_Admin (2022). HUD Revitalization Areas by Census Block Group [Dataset]. https://data.cityofrochester.gov/datasets/hud-revitalization-areas-by-census-block-group
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    Dataset updated
    Feb 7, 2022
    Dataset authored and provided by
    Open_Data_Admin
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This map is made using content created and owned by the federal Department of Housing and Urban Development (Esri user HUD.Official.Content). The map uses their Revitalization Areas layer and their Revitalization Areas by Block Group layer, centered on Rochester, NY, with the City of Rochester, NY border added for context. Users can zoom out to see the Revitalization Areas for other geographies.Revitalization Areas are HUD-designated geographic areas authorized by Congress under provisions of the National Housing Act intended to promote "revitalization, through expanded homeownership opportunities.” HUD-owned single-family properties located in a Revitalization Areas are eligible for discounted sale through special programs, including the Asset Control Areas (ACA) Program, and the Good Neighbor Next Door (GNND) Program.Revitalization Areas are determined by comparing a block group's median household income and home ownership rate to the respective rates of the surrounding area. If the block group is located in a CBSA Metropolitan area, then the metro area is used. However, if the block group is located in a Non-Metro area, then the state rate is used.To learn more about the HUD FHA Revitalization Areas Program visit: https://www.hud.gov/program_offices/housing/sfh/reo/abtrevt/Data Dictionary: DD_Revitalization Areas by Block GroupDate of Coverage: 12/2018Data Updated: Quarterly

  5. Extensions to Estimated Housing Authority Service Areas Methodology

    • data.lojic.org
    Updated Mar 21, 2024
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    Department of Housing and Urban Development (2024). Extensions to Estimated Housing Authority Service Areas Methodology [Dataset]. https://data.lojic.org/maps/5fd9d5a4915c4d5189d04676343e4c64
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    Dataset updated
    Mar 21, 2024
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    The data provided here denotes the authors’ revised service areas for a subset of 377 Public Housing Authorities (PHAs) for which HUD previously estimated service areas. Using HUD administrative data on the location of Housing Choice Voucher holders, HUD’s estimated service areas were revised to better capture voucher activity. Specifically, the authors developed two different tests and correction procedures. The first assesses if the estimated service area omits a sizable share of voucher holder locations (so is “too small”), and if so, adjusts to include census designated places or counties containing at least 5 percent of a PHA’s voucher holders. The second test checks whether the estimated service boundary includes areas the PHA does not appear to serve and that are clearly served by another PHA (so is “too large”), in this case adjusting by removing those areas. 148 of the 377 PHA estimated service areas were found to be too small, too large, or both, and so have revised service areas that differ from HUD’s estimated service areas. The detailed methodology is provided below. Additionally, a spreadsheet is supplied that identifies geographies that were added to and dropped from HUD’s estimated services to create the revised service areas for affected PHAs.

    This is an experimental dataset that is designed to aid researchers in studying the HCV program. The methodology and the service areas themselves have not been validated by HUD’s Office of Public and Indian Housing (PIH) or the Public Housing Agencies. For additional discussion of the approach, see Tauber et al. (2024); please contact the authors with any questions or comments.Data Dictionary: DD_Extensions to Estimated Housing Authority Service Areas MethodologyMethodology: Extensions to Estimated Housing Authority Service Areas Methodology

    Reference:Tauber, Kristen, Ingrid Gould Ellen, and Katherine O’Regan. 2024. “Whom Do We Serve? Refining Public Housing Agency Service Areas.” Cityscape 26(1) (2024): 395-400.

  6. l

    TRIBE CONTACT COUNTY VW

    • data.lojic.org
    • opendata.atlantaregional.com
    • +2more
    Updated Mar 6, 2019
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    Department of Housing and Urban Development (2019). TRIBE CONTACT COUNTY VW [Dataset]. https://data.lojic.org/datasets/HUD::tribe-contact-county-vw
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    Dataset updated
    Mar 6, 2019
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    These data were developed by the Office of Environment and Energy (OEE) to help users identify tribes that may have an interest in the location of federally funded projects and provides tribal contact information to assist users with initiating Section 106 consultation under the National Historic Preservation Act (54 U.S.C. § 300101 et seq.).For questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov.

  7. Tribal Contact Data

    • hudgis-hud.opendata.arcgis.com
    Updated Mar 6, 2019
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    Department of Housing and Urban Development (2019). Tribal Contact Data [Dataset]. https://hudgis-hud.opendata.arcgis.com/maps/77572a4428384d2697c476564dcf53f0
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    Dataset updated
    Mar 6, 2019
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    These data were developed by the Office of Environment and Energy (OEE) to help users identify tribes that may have an interest in the location of federally funded projects and provides tribal contact information to assist users with initiating Section 106 consultation under the National Historic Preservation Act (54 U.S.C. § 300101 et seq.).For questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov.

  8. l

    HUD Empowerment Zones (EZ)

    • geohub.lacity.org
    • visionzero.geohub.lacity.org
    • +4more
    Updated Nov 14, 2015
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    lahub_admin (2015). HUD Empowerment Zones (EZ) [Dataset]. https://geohub.lacity.org/datasets/hud-empowerment-zones-ez
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    Dataset updated
    Nov 14, 2015
    Dataset authored and provided by
    lahub_admin
    Area covered
    Description

    The Department of Housing and Urban Development identifies distressed urban and rural communities that may be eligible for a combination of grants, tax credits for businesses, bonding authority and other benefits.

  9. HUD - Section 811 Properties

    • opendata.atlantaregional.com
    • data.lojic.org
    • +2more
    Updated Aug 26, 2020
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    Department of Housing and Urban Development (2020). HUD - Section 811 Properties [Dataset]. https://opendata.atlantaregional.com/datasets/HUD::hud-section-811-properties/explore
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    Dataset updated
    Aug 26, 2020
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    This feature service denotes the locations of HUD assisted Multi-Family properties that primarily serve disabled residents. In addition, each property illustrated through this service has at least one active Service Coordinator contract or grant, Section 8 New Construction contract, Section 811 Project Assistance Contracts (PAC) contract, or Section 811 Project Rental Assistance Contract (PRAC). Please note that the data provided through this service only includes location data and attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to a ZIP+4 centroid location. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD.

    To learn more about the Section 811 Program visit: https://www.hud.gov/program_offices/housing/mfh/progdesc/disab811

    Data Dictionary: DD_Multifamily Properties Date of Coverage: 03/2020

    Data Updated: Quarterly

  10. t

    Opportunity Zones (HUD)

    • data.tacoma.gov
    • hub.arcgis.com
    Updated Jan 30, 2026
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    City of Tacoma GIS (2026). Opportunity Zones (HUD) [Dataset]. https://data.tacoma.gov/datasets/tacoma::opportunity-zones-hud
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    Dataset updated
    Jan 30, 2026
    Dataset authored and provided by
    City of Tacoma GIS
    Area covered
    Description

    For questions about Tacoma and Qualified Opportunity Zones, please contact the City of Tacoma Community and Economic Development Department.This service provides spatial data for all U.S. Decennial Census tracts designated as Qualified Opportunity Zones (QOZs) for purposes of §§ 1400Z–1 and 1400Z–2 of the Internal Revenue Code (the Code). Source: US Department of Housing and Urban Development (HUD). Section 1400Z–1(b)(1)(A) of the Code allowed the Chief Executive Officer (CEO) of each State to nominate a limited number of population census tracts to be designated as Zones for purposes of §§ 1400Z–1 and 1400Z–2. Revenue Procedure 2018–16, 2018–9 I.R.B. 383, provided guidance to State CEOs on the eligibility criteria and procedure for making these nominations. Section 1400Z–1(b)(1)(B) of the Code provides that after the Secretary receives notice of the nominations, the Secretary may certify the nominations and designate the nominated tracts as Zones. Section 1400Z–2 of the Code allows the temporary deferral of inclusion in gross income for certain realized gains to the extent that corresponding amounts are timely invested in a qualified opportunity fund. Investments in a qualified opportunity fund may also be eligible for additional tax benefits. See the source dataset here: https://hudgis-hud.opendata.arcgis.com/datasets/ef143299845841f8abb95969c01f88b5_0/aboutDate of Coverage: 12/2019Data Dictionary: DD Opportunity Zone Eligible Census Tracts

  11. l

    HUD Qualified Census Tracts 2025

    • data.lacounty.gov
    • geohub.lacity.org
    • +3more
    Updated Jun 21, 2022
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    County of Los Angeles (2022). HUD Qualified Census Tracts 2025 [Dataset]. https://data.lacounty.gov/datasets/hud-qualified-census-tracts-2025/about
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    Dataset updated
    Jun 21, 2022
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    The U.S. Housing and Urban Development (HUD) maintains data for Qualified Census Tracts (QCT). Low-Income Housing Tax Credit Qualified Census Tracts must have 50 percent of households with incomes below 60 percent of the Area Median Gross Income (AMGI) or have a poverty rate of 25 percent or more. This layer contains all Census Tracts in LA County, with QCT marked as "Yes" and tracts that are not QCT as "No."This layer is an export of the 2025 data. Source data is updated annually. Data are at the 2020 census tract geography level. These have been joined to Supervisorial Districts 2021 and SPAs 2022, based on a "majority in" spatial join.To learn more: https://www.huduser.gov/portal/datasets/qct.htmlFor more information, please contact egis@isd.lacounty.gov.

  12. l

    Location Affordability Index v.3

    • data.lojic.org
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +2more
    Updated Jan 24, 2025
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    Department of Housing and Urban Development (2025). Location Affordability Index v.3 [Dataset]. https://data.lojic.org/maps/HUD::location-affordability-index-v-3/about
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    Dataset updated
    Jan 24, 2025
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    First launched by the U.S. Department of Housing and Urban Development (HUD) and Department of Transportation (DOT) in November 2013, the Location Affordability Index (LAI) provides ubiquitous, standardized household housing and transportation cost estimates for all 50 states and the District of Columbia. Because what is affordable is different for everyone, users can choose among eight household profiles—which vary by household income, size, and number of commuters—and see the impact of the built environment on affordability in a given location while holding household demographics constant.

    Version 3 updates the constituent data sets with 2012-2016 American Community Survey data and makes several methodological tweaks, most notably moving to modeling at the Census tract level rather at the block group. As with Version 2, the inputs to the simultaneous equation model (SEM) include six endogenous variables—housing costs, car ownership, and transit usage for both owners and renters—and 18 exogenous variables, with vehicle miles traveled still modeled separately due to data limitations.To learn more about the Location Affordability Index (v.3) visit: https://www.hudexchange.info/programs/location-affordability-index/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 2012-2016 Data Dictionary: DD_Location Affordability Indev v.3.0LAI Version 3 Data and MethodologyLAI Version 3 Technical Documentation

  13. D

    HUD-USPS ZIP Crosswalk Files

    • datalumos.org
    Updated Feb 13, 2025
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    United States Department of Housing and Urban Development (2025). HUD-USPS ZIP Crosswalk Files [Dataset]. http://doi.org/10.3886/E219325V1
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    Dataset updated
    Feb 13, 2025
    Dataset authored and provided by
    United States Department of Housing and Urban Development
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2010 - 2024
    Area covered
    United States of America
    Description

    One of the many challenges that social science researchers and practitioners face is the difficulty of relating data between census tracts which are re-delineated with each decennial census. While some methods of harmonizing or crosswalking data between census tracts exist, to provide additional avenues for merging these data, PD&R has released the HUD-USPS Census Tract Crosswalk Files. These unique files are derived from the USPS Vacancy Data which are regularly updated by the USPS which makes them uniquely positioned to describe human settlements patterns between census tract delineations. These data use the locations of ZIP+4 centroids, an extremely granular level of geography, the number of addresses of various types (residential, business, other, and total), and do not rely on ancillary data to map where population or households might be located.There are twelve types of crosswalk files available for download. The first six crosswalk files are used to allocate ZIP codes to Census Bureau geographies such as census tracts, counties, county subdivisions, Core Based Statistical Areas (CBSAs), CBSA Divisions, and Congressional Districts. The last six are used to allocate from those same Census Bureau geographies to ZIP Codes. It is important to note that the relationship between the two types of crosswalk files is not perfectly inverse. That is to say, the ZIP to Tract crosswalk file cannot be used to allocate data from census tract geographies to ZIP codes. Instead, the Tract to ZIP crosswalk file must be used in that specific scenario.In addition to the crosswalk files, this dataset also includes screenshots of HUDs documentation and FAQ pages.

  14. h

    Sandy Damage Estimates by Block Group

    • huduser.gov
    • data.lojic.org
    • +2more
    Updated Aug 4, 2023
    + more versions
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    Department of Housing and Urban Development (2023). Sandy Damage Estimates by Block Group [Dataset]. https://www.huduser.gov/maps/map_sandy_blockgroup.html
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    Dataset updated
    Aug 4, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    A FEMA housing inspection for renters is used to assess personal property loss and for owners to assess damage to their home as well as personal property. This inspection is done to determine eligibility for FEMA Individual Assistance. For both rental and owner inspections, if the property has flood damage the inspector measures the height of the flooding. They indicate the highest floor of the flooding (for example, Basement, 1st floor, 2nd floor, etc…) and the extent of the flooding in that room. In addition, for the units without flooding, HUD has estimated minor/major/severe damage based on the damage inspection estimates for real property (owner) and personal property (renter).In an effort to maintain the confidentiality of residents this file only presents data on block groups with ten or more damaged housing units. The suppression of block groups with fewer than ten damaged housing units results in an exclusion of approximately 6% of the total flooded units. These data reflect Hurricane Sandy damage in the states of New York, New Jersey, Connecticut, and Rhode Island. These data are incomplete, as each day there are additional registrants and inspections. This should be a viewed as a preliminary snapshot to assist with planning.To learn more about HUD's long-term recovery efforts for victims of Hurricane Sandy visit: https://www.hud.gov/sandyrebuilding, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov.

  15. Data from: Public Housing Developments

    • opendata.atlantaregional.com
    • data.lojic.org
    • +1more
    Updated Mar 2, 2016
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    Department of Housing and Urban Development (2016). Public Housing Developments [Dataset]. https://opendata.atlantaregional.com/datasets/5c96143f79c940a0a8cedae99a1ac562
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    Dataset updated
    Mar 2, 2016
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    HUD furnishes technical and professional assistance in planning, developing and managing these developments. Public Housing Developments are depicted as a distinct address chosen to represent the general location of an entire Public Housing Development, which may be comprised of several buildings scattered across a community. The building with the largest number of units is selected to represent the location of the development. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information (PII), the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10. To learn more about Public Housing visit: https://www.hud.gov/program_offices/public_indian_housing/programs/ph/ Data Dictionary: DD_Public Housing Developments

  16. l

    Low Poverty Index

    • data.lojic.org
    • hudgis-hud.opendata.arcgis.com
    • +2more
    Updated Jul 5, 2023
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    Department of Housing and Urban Development (2023). Low Poverty Index [Dataset]. https://data.lojic.org/datasets/HUD::low-poverty-index/api
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    Dataset updated
    Jul 5, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    LOW POVERTY INDEXSummary The low poverty index captures poverty in a given neighborhood. The index is based on the poverty rate (pv). The mean and standard error are estimated over the national distribution.The poverty rate is determined at the census tract level.InterpretationValues are inverted and percentile ranked nationally. The resulting values range from 0 to 100. The higher the score, the less exposure to poverty in a neighborhood.

    Data Source: American Community Survey, 2011-2015. Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 12. School Proficiency Index.

    To learn more about the Low Poverty Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020

  17. l

    Low Transportation Cost Index

    • data.lojic.org
    • hudgis-hud.opendata.arcgis.com
    • +2more
    Updated Jul 5, 2023
    + more versions
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    Department of Housing and Urban Development (2023). Low Transportation Cost Index [Dataset]. https://data.lojic.org/datasets/HUD::low-transportation-cost-index
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    Dataset updated
    Jul 5, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    LOW TRANSPORTATION COST INDEXSummaryThe Low Transportation Cost Index is based on estimates of transportation expenses for a family that meets the following description: a 3-person single-parent family with income at 50% of the median income for renters for the region (i.e. CBSA). The estimates come from the Location Affordability Index (LAI). The data correspond to those for household type 6 (hh_type6_) as noted in the LAI data dictionary. More specifically, among this household type, we model transportation costs as a percent of income for renters (t_rent). Neighborhoods are defined as census tracts. The LAI data do not contain transportation cost information for Puerto Rico.InterpretationValues are inverted and percentile ranked nationally, with values ranging from 0 to 100. The higher the transportation cost index, the lower the cost of transportation in that neighborhood. Transportation costs may be low for a range of reasons, including greater access to public transportation and the density of homes, services, and jobs in the neighborhood and surrounding community.

    Data Source: Location Affordability Index (LAI) data, 2012-2016.Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 11.

    References: www.locationaffordability.infohttps://lai.locationaffordability.info//lai_data_dictionary.pdf

    To learn more about the Low Transportation Cost Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020

  18. A

    HUD Low and Moderate Income Areas

    • data.amerigeoss.org
    • data.wu.ac.at
    api, bin
    Updated Jul 26, 2019
    + more versions
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    United States (2019). HUD Low and Moderate Income Areas [Dataset]. https://data.amerigeoss.org/dataset/activity/hud-low-and-moderate-income-areas
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    bin, apiAvailable download formats
    Dataset updated
    Jul 26, 2019
    Dataset provided by
    United States
    Description

    This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

  19. l

    Racially or Ethnically Concentrated Areas of Poverty (R/ECAPs) 2020

    • data.lojic.org
    • hudgis-hud.opendata.arcgis.com
    • +1more
    Updated Aug 21, 2023
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    Department of Housing and Urban Development (2023). Racially or Ethnically Concentrated Areas of Poverty (R/ECAPs) 2020 [Dataset]. https://data.lojic.org/datasets/HUD::racially-or-ethnically-concentrated-areas-of-poverty-r-ecaps-2020
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    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    To assist communities in identifying racially/ethnically-concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs. The definition involves a racial/ethnic concentration threshold and a poverty test. The racial/ethnic concentration threshold is straightforward: R/ECAPs must have a non-white population of 50 percent or more. Regarding the poverty threshold, Wilson (1980) defines neighborhoods of extreme poverty as census tracts with 40 percent or more of individuals living at or below the poverty line. Because overall poverty levels are substantially lower in many parts of the country, HUD supplements this with an alternate criterion. Thus, a neighborhood can be a R/ECAP if it has a poverty rate that exceeds 40% or is three or more times the average tract poverty rate for the metropolitan/micropolitan area, whichever threshold is lower. Census tracts with this extreme poverty that satisfy the racial/ethnic concentration threshold are deemed R/ECAPs. This translates into the following equation: Where i represents census tracts, () is the metropolitan/micropolitan (CBSA) mean tract poverty rate, is the ith tract poverty rate, () is the non-Hispanic white population in tract i, and Pop is the population in tract i.While this definition of R/ECAP works well for tracts in CBSAs, place outside of these geographies are unlikely to have racial or ethnic concentrations as high as 50 percent. In these areas, the racial/ethnic concentration threshold is set at 20 percent. Data Source: Related AFFH-T Local Government, PHA Tables/Maps: Table 4, 7; Maps 1-17.Related AFFH-T State Tables/Maps: Table 4, 7; Maps 1-15, 18.References:Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.To learn more about R/ECAPs visit:https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 2017 - 2021 ACSDate Updated: 10/2023

  20. d

    Revitalization Areas

    • catalog.data.gov
    • data.amerigeoss.org
    • +1more
    Updated Mar 11, 2026
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    U.S. Department of Housing and Urban Development (2026). Revitalization Areas [Dataset]. https://catalog.data.gov/dataset/revitalization-areas
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    Dataset updated
    Mar 11, 2026
    Dataset provided by
    U.S. Department of Housing and Urban Development
    Description

    Revitalization areas are HUD-designated neighborhoods in need of economic and community development and where there is already a strong commitment by the local governments. Revitalization Areas are the basis for HUD programs such as Good Neighbor Next Door (GNND) and Asset Control Areas (ACA). To learn more, please visit: https://portal.hud.gov/hudportal/HUD?src=/program_offices/housing/sfh/reo/abtrevt

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U.S. Department of Housing and Urban Development (2026). Community Planning and Development (CPD) Maps System [Dataset]. https://catalog.data.gov/dataset/the-cpd-maps-system

Community Planning and Development (CPD) Maps System

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Dataset updated
Mar 11, 2026
Dataset provided by
U.S. Department of Housing and Urban Development
Description

CPD Maps includes data on the locations of existing CDBG, HOME, public housing and other HUD-funded community assets, so that users can view past investments geographically when considering various strategies for future funding. CPD Maps offers a large amount of data in a way that is easy to access. The website allows grantees and the general public to easily search, query, and display information to identify trends and analyze the needs of their community.

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