100+ datasets found
  1. d

    Affordable Housing

    • catalog.data.gov
    • opendata.dc.gov
    • +4more
    Updated May 21, 2025
    + more versions
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    City of Washington, DC (2025). Affordable Housing [Dataset]. https://catalog.data.gov/dataset/affordable-housing
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    Dataset updated
    May 21, 2025
    Dataset provided by
    City of Washington, DC
    Description

    Affordable housing production and preservation projects are managed by the Department of Housing and Community Development (DHCD), the Deputy Mayor for Planning and Economic Development (DMPED), the DC Housing Authority, the DC Housing Finance Agency and DC's Inclusionary Zoning program. This dataset comprehensively covers affordable housing projects which started (i.e. reached financial closing and/or started construction) or completed since January of 2015. The data includes affordable housing projects (production and preservation, rental and for-sale) which were subsidized by DMPED, DHCD, DCHFA, or DCHA, and those which were produced as a result of Planned Unit Development (PUD) proffers or Inclusionary Zoning (IZ) requirements.

  2. Housing Disadvantaged Tracts (Archive)

    • hub.arcgis.com
    • gis-request-management-6-government.hub.arcgis.com
    Updated May 31, 2022
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    Urban Observatory by Esri (2022). Housing Disadvantaged Tracts (Archive) [Dataset]. https://hub.arcgis.com/maps/889da6a248024b7fb659e0e639d9b496
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    Dataset updated
    May 31, 2022
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map uses an archive of Version 1.0 of the CEJST data as a fully functional GIS layer. See an archive of the latest version of the CEJST tool using Version 2.0 of the data released in December 2024 here.This map assesses and identifies communities that are Housing Disadvantaged according to Justice40 Initiative criteria. "Communities are identified as disadvantaged if they are in census tracts that:Experienced historic underinvestment OR are at or above the 90th percentile for the housing cost OR lack of green space OR lack of indoor plumbing OR lead paintAND are at or above the 65th percentile for low income"Census tracts in the U.S. and its territories that meet the criteria are shaded in blue colors. Suitable for dashboards, apps, stories, and grant applications.Details of the assessment are provided in the popup for every census tract in the United States and its territories American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. This map uses 2010 census tracts from Version 1.0 of the source data downloaded November 22, 2022.Use this map to help plan for grant applications, to perform spatial analysis, and to create informative dashboards and web applications.From the source:This data "highlights disadvantaged census tracts across all 50 states, the District of Columbia, and the U.S. territories. Communities are considered disadvantaged:If they are in census tracts that meet the thresholds for at least one of the tool’s categories of burden, orIf they are on land within the boundaries of Federally Recognized TribesCategories of BurdensThe tool uses datasets as indicators of burdens. The burdens are organized into categories. A community is highlighted as disadvantaged on the CEJST map if it is in a census tract that is (1) at or above the threshold for one or more environmental, climate, or other burdens, and (2) at or above the threshold for an associated socioeconomic burden.In addition, a census tract that is completely surrounded by disadvantaged communities and is at or above the 50% percentile for low income is also considered disadvantaged.Census tracts are small units of geography. Census tract boundaries for statistical areas are determined by the U.S. Census Bureau once every ten years. The tool utilizes the census tract boundaries from 2010. This was chosen because many of the data sources in the tool currently use the 2010 census boundaries."PurposeThe goal of the Justice40 Initiative is to provide 40 percent of the overall benefits of certain Federal investments in [eight] key areas to disadvantaged communities. These [eight] key areas are: climate change, clean energy and energy efficiency, clean transit, affordable and sustainable housing, training and workforce development, the remediation and reduction of legacy pollution, [health burdens] and the development of critical clean water infrastructure." Source: Climate and Economic Justice Screening tool"Sec. 219. Policy. To secure an equitable economic future, the United States must ensure that environmental and economic justice are key considerations in how we govern. That means investing and building a clean energy economy that creates well‑paying union jobs, turning disadvantaged communities — historically marginalized and overburdened — into healthy, thriving communities, and undertaking robust actions to mitigate climate change while preparing for the impacts of climate change across rural, urban, and Tribal areas. Agencies shall make achieving environmental justice part of their missions by developing programs, policies, and activities to address the disproportionately high and adverse human health, environmental, climate-related and other cumulative impacts on disadvantaged communities, as well as the accompanying economic challenges of such impacts. It is therefore the policy of my Administration to secure environmental justice and spur economic opportunity for disadvantaged communities that have been historically marginalized and overburdened by pollution and underinvestment in housing, transportation, water and wastewater infrastructure, and health care." Source: Executive Order on Tackling the Climate Crisis at Home and AbroadUse of this Data"The pilot identifies 21 priority programs to immediately begin enhancing benefits for disadvantaged communities. These priority programs will provide a blueprint for other agencies to help inform their work to implement the Justice40 Initiative across government." Source: The Path to Achieving Justice 40

  3. D

    Map of Affordable Housing Pipeline

    • data.sfgov.org
    application/rdfxml +5
    Updated May 13, 2025
    + more versions
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    Mayor's Office of Housing and Community Development (2025). Map of Affordable Housing Pipeline [Dataset]. https://data.sfgov.org/w/d4zr-mbcm/ikek-yizv?cur=j-Nu0JirWHH
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    csv, json, xml, application/rssxml, application/rdfxml, tsvAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset authored and provided by
    Mayor's Office of Housing and Community Development
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    As of November 2023, this map has been updated to use a new format. For details, please see here.
    Snapshot of the Mayor’s Office of Housing and Community Development (MOHCD) and the Office of Community Investment and Infrastructure (OCII) affordable housing pipeline projects. The projects listed are in the process of development--or are anticipated to be developed--in partnership with non-profit or for-profit developers and financed through city funding agreements, ground leases, disposition and participation agreements and conduit bond financing. The Affordable Housing Pipeline also includes housing units produced by private developers through the Inclusionary Affordable Housing Program. Data reflects all projects as of June 30, 2023.

  4. e

    Map Viewing Service (WMS) of the dataset: Municipalities subject to the law...

    • data.europa.eu
    wms
    + more versions
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    Map Viewing Service (WMS) of the dataset: Municipalities subject to the law Solidarity and Urban Renewal (SRU) in Provence Alpes Côte d’Azur [Dataset]. https://data.europa.eu/data/datasets/fr-120066022-srv-5e3f63b0-51f7-4247-bca7-cf108746f7c2
    Explore at:
    wmsAvailable download formats
    Description

    Adopted on 13 December 2000, the Law on Solidarity and Urban Renewal (SRU) aims to restore social balance in each territory and to address the shortage of social housing. Article 55 requires certain municipalities to have a minimum number of social housing units, proportional to their residential stock. Pursuant to Law No. 2013-61 of 18 January 2013, the requirements for the production of social housing have been strengthened. Municipalities with more than 3,500 inhabitants — and 1 500 inhabitants in Île-de-France — belonging to agglomerations or intercommunalities with more than 50,000 inhabitants, comprising at least one municipality with more than 15,000 inhabitants, must thus have 25 % social housing in relation to the main residences by 2025.

  5. g

    Housing Database by Community District (Map)

    • gimi9.com
    + more versions
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    Housing Database by Community District (Map) [Dataset]. https://gimi9.com/dataset/ny_m8qf-ycd5
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    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Net change in housing units arising from new buildings, demolitions, or alterations for NYC Community Districts since 2010. The NYC Department of City Planning’s (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at a BYTES of the BIG APPLE- Archive

  6. a

    Housing and Urban Development Area Map

    • gis-jcgis.opendata.arcgis.com
    • gis.jacksoncountyor.gov
    Updated Sep 1, 2015
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    Jackson County GIS (2015). Housing and Urban Development Area Map [Dataset]. https://gis-jcgis.opendata.arcgis.com/datasets/c25859746ee8410aac17075a01733799
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    Dataset updated
    Sep 1, 2015
    Dataset authored and provided by
    Jackson County GIS
    Description

    This map shows the Housing and Urban Development Areas in Jackson County and was Map 12 in the Jackson County Community Fire Plan. The page size is 11 inches by 17 inches.

  7. ACS Housing Units Occupancy Variables - Boundaries

    • heat.gov
    • opendata.suffolkcountyny.gov
    • +4more
    Updated Oct 20, 2018
    + more versions
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    Esri (2018). ACS Housing Units Occupancy Variables - Boundaries [Dataset]. https://www.heat.gov/maps/4a7ee18ac4f7414ca61b8598f3ea2ccd
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    Dataset updated
    Oct 20, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows housing occupancy, tenure, and median rent/housing value. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Homeownership rate on Census Bureau's website is owner-occupied housing unit rate (called B25003_calc_pctOwnE in this layer). This layer is symbolized by the overall homeownership rate. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B25002, B25003, B25058, B25077, B25057, B25059, B25076, B25078Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  8. f

    CHDO and CDBG DR

    • gisdata.fultoncountyga.gov
    • hub.arcgis.com
    • +2more
    Updated Feb 13, 2020
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    Georgia Department of Community Affairs (2020). CHDO and CDBG DR [Dataset]. https://gisdata.fultoncountyga.gov/datasets/Georgia-DCA::chdo-and-cdbg-dr/about
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    Dataset updated
    Feb 13, 2020
    Dataset authored and provided by
    Georgia Department of Community Affairs
    Area covered
    Description

    At least 15 percent of HOME Investment Partnerships Program (HOME) funds must be set aside for specific activities to be undertaken by a special type of nonprofit called a Community Housing Development Organization (CHDO). A CHDO is a private nonprofit, community-based organization that has staff with the capacity to develop affordable housing for the community it serves. In order to qualify for designation as a CHDO, the organization must meet certain requirements pertaining to their legal status, organizational structure, and capacity and experience.HUD exchangeThis layer is used in the Map(s): Multifamily Affordable Housing Properties

  9. c

    When was the housing stock built?

    • hub.scag.ca.gov
    • regionaldatahub-brag.hub.arcgis.com
    • +3more
    Updated Feb 1, 2022
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    rdpgisadmin (2022). When was the housing stock built? [Dataset]. https://hub.scag.ca.gov/maps/ef22f5bda61a43e1a9b77a5541c373f6
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    Dataset updated
    Feb 1, 2022
    Dataset authored and provided by
    rdpgisadmin
    Area covered
    Description

    Use this map to understand the age of housing stock in your community. Dark red areas have predominantly older housing, whereas yellow areas have newer housing. The size of the symbol depicts the count of all housing units. Click on an area to view the pop-up which provides more context.The mix of housing stock is an integral component in many programs such as HUD's Fair Market Rents, Community Development Block Grant (CDBG), HOME Investment Partnerships Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and more.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

  10. Data from: Public Housing Developments

    • data-lojic.hub.arcgis.com
    • opendata.atlantaregional.com
    • +3more
    Updated Nov 12, 2024
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    Department of Housing and Urban Development (2024). Public Housing Developments [Dataset]. https://data-lojic.hub.arcgis.com/items/5c96143f79c940a0a8cedae99a1ac562
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    Dataset updated
    Nov 12, 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

    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/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Public Housing Developments Date Updated: Q1 2025

  11. Households who spend more than 30 percent of income on housing

    • data.amerigeoss.org
    esri rest, html
    Updated Jan 7, 2020
    + more versions
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    ESRI (2020). Households who spend more than 30 percent of income on housing [Dataset]. https://data.amerigeoss.org/id/dataset/households-who-spend-more-than-30-percent-of-income-on-housing
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    esri rest, htmlAvailable download formats
    Dataset updated
    Jan 7, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description

    This map shows households that spend more than 30 percent of their income on housing, a threshold widely used by many affordable housing advocates and official government sources including Housing and Urban Development. Census asks about income and housing costs to understand whether housing is affordable in local communities. When housing is not sufficient or not affordable, income data helps communities:

    • Enroll eligible households in programs designed to assist them.
    • Qualify for grants from the Community Development Block Grant (CDBG), HOME Investment Partnership Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and other programs.
    When rental housing is not affordable, the Department of Housing and Urban Development (HUD) uses rent data to determine the amount of tenant subsidies in housing assistance programs.

    Map opens in Atlanta. Use the bookmarks or search bar to view other cities. Data is symbolized to show the relationship between burdensome housing costs for owner households with a mortgage and renter households:

    legned

    This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

  12. Colonias Communities

    • catalog.data.gov
    • data.lojic.org
    • +4more
    Updated Mar 1, 2024
    + more versions
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    U.S. Department of Housing and Urban Development (2024). Colonias Communities [Dataset]. https://catalog.data.gov/dataset/colonias-communities
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Description

    This service denotes the locations of colonias communities as defined in Section 916 of the Cranston-Gonzalez National Affordable Housing Act of 1990. In order to better serve colonia residents, the National Affordable Housing Act of 1990 (as amended) included Section 916 which called for the border states of Arizona, California, New Mexico and Texas to set aside a percentage of their annual State CDBG allocations for use in the colonias. The use of these set aside funds is to help meet the needs of the colonias residents in relationship to the need for potable water, adequate sewer systems, or decent, safe and sanitary housing. Therefore, the set-aside funds may be utilized for any CDBG eligible activity that is, or is in conjunction with, a potable water, sewer or housing activity.

  13. e

    Households who spend 30 percent or more of income on housing

    • coronavirus-resources.esri.com
    • coronavirus-disasterresponse.hub.arcgis.com
    • +2more
    Updated Dec 21, 2018
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    Urban Observatory by Esri (2018). Households who spend 30 percent or more of income on housing [Dataset]. https://coronavirus-resources.esri.com/maps/f9a964e38eae479dbe0b71ad6067e5f2
    Explore at:
    Dataset updated
    Dec 21, 2018
    Dataset authored and provided by
    Urban Observatory by Esri
    Area covered
    Description

    This map shows households that spend 30 percent or more of their income on housing, a threshold widely used by many affordable housing advocates and official government sources including Housing and Urban Development. Census asks about income and housing costs to understand whether housing is affordable in local communities. When housing is not sufficient or not affordable, income data helps communities: Enroll eligible households in programs designed to assist them.Qualify for grants from the Community Development Block Grant (CDBG), HOME Investment Partnership Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and other programs.When rental housing is not affordable, the Department of Housing and Urban Development (HUD) uses rent data to determine the amount of tenant subsidies in housing assistance programs.Map opens in Atlanta. Use the bookmarks or search bar to view other cities. Data is symbolized to show the relationship between burdensome housing costs for owner households with a mortgage and renter households:This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

  14. d

    Housing - ACS 2017-2021 - Tempe Tracts

    • catalog.data.gov
    • performance.tempe.gov
    • +11more
    Updated Sep 20, 2024
    + more versions
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    City of Tempe (2024). Housing - ACS 2017-2021 - Tempe Tracts [Dataset]. https://catalog.data.gov/dataset/housing-acs-2017-2021-tempe-tracts-5afee
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    Dataset updated
    Sep 20, 2024
    Dataset provided by
    City of Tempe
    Area covered
    Tempe
    Description

    This layer shows occupied housing units broken down by renter-occupied and owner-occupied status.Data is from the US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percent of occupied housing units that is renter-occupied. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2017-2021ACS Table(s): S2502, DP04 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data downloaded and joined with Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: December 8, 2022National Figures: S2502: data.census.gov; DP04 data.census.gov

  15. e

    Map Viewing Service (WMS) of the dataset: Municipalities of Indre and Loire...

    • data.europa.eu
    wms
    Updated Oct 12, 2021
    + more versions
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    (2021). Map Viewing Service (WMS) of the dataset: Municipalities of Indre and Loire concerned by the obligation to provide social housing pursuant to Article 55 of the SRU Law [Dataset]. https://data.europa.eu/data/datasets/fr-120066022-srv-51c9729c-7acb-47ae-b830-b414b7de691c
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    wmsAvailable download formats
    Dataset updated
    Oct 12, 2021
    Description

    Adopted on 13 December 2000, the Law on Solidarity and Urban Renewal (SRU) aims to restore social balance in each territory and to address the shortage of social housing. Article 55 obliges certain municipalities to have a minimum number of social housing units, proportional to their residential stock.In application of Law No. 2013-61 of 18 January 2013, the requirements for the production of social housing have been strengthened. Municipalities with more than 3,500 inhabitants — and 1 500 inhabitants in Île-de-France — belonging to agglomerations or intercommunalities with more than 50,000 inhabitants, comprising at least one municipality with more than 15,000 inhabitants, must thus have 25 % social housing in relation to the main residences by 2025.

  16. e

    Visual heritage - Social housing under architecture

    • data.europa.eu
    wms
    Updated Feb 1, 2025
    + more versions
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    (2025). Visual heritage - Social housing under architecture [Dataset]. https://data.europa.eu/data/datasets/bc23eb42-056a-4250-9506-ae3902276129?locale=en
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    wmsAvailable download formats
    Dataset updated
    Feb 1, 2025
    Description

    In the map layer with social housing under architecture are several housing projects recorded. Several sources have been consulted for this, including overview works on garden cities and social housing as well as the results of the Monuments Inventory Project (MIP) of the Cultural Heritage Agency of the Netherlands and the province of South Holland. In some cases, it has been decided to include partially destroyed or demolished housing neighborhoods in the map. The map image is therefore not a complete overview (which requires more extensive research), but shows a selection of different housing projects.

  17. H

    Mapping Subsidized Housing Programs in Toronto: A Dual Map Visualization

    • dataverse.harvard.edu
    Updated Feb 21, 2025
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    Alice Jiao (2025). Mapping Subsidized Housing Programs in Toronto: A Dual Map Visualization [Dataset]. http://doi.org/10.7910/DVN/6LDQWC
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Alice Jiao
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Toronto
    Description

    Created by Alice Jiao, this interactive mapping project provides a comprehensive visualization of subsidized housing programs in Toronto, offering insights into their spatial distribution and relationship with low-income and immigrant populations. Using open-source data from Toronto (2021), the project employs a dual-map interface, allowing users to compare different socioeconomic factors across the city. The left panel displays the density of low-income and immigrant populations, while the right panel highlights subsidized housing locations and availability. Users can toggle map layers, explore detailed neighborhood statistics, and access external resources for further analysis. The synchronized maps ensure seamless interaction, making it easier to identify housing disparities and policy gaps. This project serves as a valuable tool for urban planners, policymakers, researchers, and community advocates, helping to drive data-informed decisions for affordable housing strategies in Toronto. Explore the interactive map at: https://astatinealice.github.io

  18. d

    Public Housing Areas

    • opendata.dc.gov
    • catalog.data.gov
    • +1more
    Updated Mar 21, 2014
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    City of Washington, DC (2014). Public Housing Areas [Dataset]. https://opendata.dc.gov/datasets/public-housing-areas
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    Dataset updated
    Mar 21, 2014
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    The DC Housing Authority provides quality affordable housing to extremely low- through moderate-income households, fosters sustainable communities, and cultivates opportunities for residents to improve their lives. The following is a subset of the District Government Land (Owned, Operated, and or managed) dataset that include buildings with a "public housing" use type.

  19. o

    Regulated affordable housing explorer

    • regionalbarometer.oregonmetro.gov
    Updated Nov 21, 2019
    + more versions
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    Metro (2019). Regulated affordable housing explorer [Dataset]. https://regionalbarometer.oregonmetro.gov/datasets/851c890e1d22418e92a056023e9b8910
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    Dataset updated
    Nov 21, 2019
    Dataset authored and provided by
    Metro
    Area covered
    Description

    This map shows the location of buildings with regulated affordable housing units, with a regulatory agreement tied to the deed to restrict rent for an established income level over a set time frame. The color of a circle represents the type of units, while the size indicates the number of units in the building.

  20. p

    Affordable Housing

    • opendata.pickering.ca
    • opendata.durham.ca
    • +6more
    Updated Nov 30, 2020
    + more versions
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    Regional Municipality of Durham (2020). Affordable Housing [Dataset]. https://opendata.pickering.ca/maps/DurhamRegion::affordable-housing
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    Dataset updated
    Nov 30, 2020
    Dataset authored and provided by
    Regional Municipality of Durham
    License

    https://www.durham.ca/en/regional-government/resources/Documents/OpenDataLicenceAgreement.pdfhttps://www.durham.ca/en/regional-government/resources/Documents/OpenDataLicenceAgreement.pdf

    Area covered
    Description

    Affordable Housing is point data representing social housing locations in Durham Region.

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City of Washington, DC (2025). Affordable Housing [Dataset]. https://catalog.data.gov/dataset/affordable-housing

Affordable Housing

Explore at:
Dataset updated
May 21, 2025
Dataset provided by
City of Washington, DC
Description

Affordable housing production and preservation projects are managed by the Department of Housing and Community Development (DHCD), the Deputy Mayor for Planning and Economic Development (DMPED), the DC Housing Authority, the DC Housing Finance Agency and DC's Inclusionary Zoning program. This dataset comprehensively covers affordable housing projects which started (i.e. reached financial closing and/or started construction) or completed since January of 2015. The data includes affordable housing projects (production and preservation, rental and for-sale) which were subsidized by DMPED, DHCD, DCHFA, or DCHA, and those which were produced as a result of Planned Unit Development (PUD) proffers or Inclusionary Zoning (IZ) requirements.

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