The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building.This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by County Date of Coverage: 2016-2020
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Thumbnail image by Tony Moody.This dataset includes all housing developments approved by the City of Boise’s (“city”) Planning Division since 2020 that are known by the city to have received or are expected to receive support or incentives from a government entity. Each row represents one development. Data may be unavailable for some projects and details are subject to change until construction is complete. Addresses are excluded for projects with fewer than five homes for privacy reasons.
The dataset includes details on the number of “homes” in a development. We use the word "home" to refer to any single unit of housing regardless of size, type, or whether it is rented or owned. For example, a building with 40 apartments counts as 40 homes, and a single detached house counts as one home.
The dataset includes details about the phase of each project. The process for build a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.
The dataset also includes data on the affordability level of each development. To receive a government incentive, a developer is typically required to rent or sell a specified number of homes to households that have an income below limits set by the government and their housing cost must not exceed 30% of their income. The federal government determines income limits based on a standard called “area median income.” The city considers housing affordable if is targeted to households earning at or below 80% of the area median income. For a three-person household in Boise, that equates to an annual income of $60,650 and monthly rent or mortgage of $1,516. See Boise Income Guidelines for more details.Project Address(es) – Includes all addresses that are included as part of the development project.Address – The primary address for the development.Parcel Number(s) – The identification code for all parcels of land included in the development.Acreage – The number of acres for the parcel(s) included in the project.Planning Permit Number – The identification code for all permits the development has received from the Planning Division for the City of Boise. The number and types of permits required vary based on the location and type of development.Date Entitled – The date a development was approved by the City’s Planning Division.Building Permit Number – The identification code for all permits the development has received from the city’s Building Division.Date Building Permit Issued – Building permits are required to begin construction on a development.Date Final Certificate of Occupancy Issued – A certificate of occupancy is the final approval by the city for a development, once construction is complete. Not all developments require a certificate of occupancy.Studio – The number of homes in the development that are classified as a studio. A studio is typically defined as a home in which there is no separate bedroom. A single room serves as both a bedroom and a living room.1-Bedroom – The number of homes in a development that have exactly one bedroom.2-Bedroom – The number of homes in a development that have exactly two bedrooms.3-Bedroom – The number of homes in a development that have exactly three bedrooms.4+ Bedroom – The number of homes in a development that have four or more bedrooms.# of Total Project Units – The total number of homes in the development.# of units toward goals – The number of homes in a development that contribute to either the city’s goal to produce housing affordable at or under 60% of area median income, or the city’s goal to create permanent supportive housing for households experiencing homelessness.Rent at or under 60% AMI - The number of homes in a development that are required to be rented at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 61-80% AMI – The number of homes in a development that are required to be rented at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 81-120% AMI - The number of homes in a development that are required to be rented at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Own at or under 60% AMI - The number of homes in a development that are required to be sold at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Own 61-80% AMI – The number of homes in a development that are required to be sold at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Own 81-120% AMI - The number of homes in a development that are required to be sold at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Housing Land Trust – “Yes” if a development receives or is expected to receive this incentive. The Housing Land Trust is a model in which the city owns land that it leases to a developer to build affordable housing.City Investment – “Yes” if the city invests funding or contributes land to an affordable development.Zoning Incentive - The city's zoning code provides incentives for developers to create affordable housing. Incentives may include the ability to build an extra floor or be subject to reduced parking requirements. “Yes” if a development receives or is expected to receive one of these incentives.Project Management - The city provides a developer and their design team a single point of contact who works across city departments to simplify the permitting process, and assists the applicants in understanding the city’s requirements to avoid possible delays. “Yes” if a development receives or is expected to receive this incentive.Low-Income Housing Tax Credit (LIHTC) - A federal tax credit available to some new affordable housing developments. The Idaho Housing and Finance Association is a quasi-governmental agency that administers these federal tax credits. “Yes” if a development receives or is expected to receive this incentive.CCDC Investment - The Capital City Development Corp (CCDC) is a public agency that financially supports some affordable housing development in Urban Renewal Districts. “Yes” if a development receives or is expected to receive this incentive. If “Yes” the field identifies the Urban Renewal District associated with the development.City Goal – The city has set goals to produce housing affordable to households at or below 60% of area median income, and to create permanent supportive housing for households experiencing homelessness. This field identifies whether a development contributes to one of those goals.Project Phase - The process for build a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.
Tempe’s Housing Choice Voucher program provides federally subsidized housing to eligible low-income families. The program is designed to provide housing that is affordable, decent, safe and sanitary. All dwelling units are inspected prior to a tenant moving into the unit and then inspected annually. Tenants and landlords may request inspections for maintenance issues that impact health and safety.This data represents the resolution rate for all Housing Quality Standard issues related to life, health or safety within 24 hours.This page provides data for the Housing Quality Standards performance measure. The performance measure dashboard is available at 1.19 Housing Quality StandardsAdditional InformationSource: Manually maintained data, Housing Pro and ExcelContact: Irma Hollamby CainContact E-Mail: irma_hollambycain@tempe.govData Source Type: Preparation Method: A tracking log in maintained for units that fail the initial inspection. The required fix timeframe of 24 hour or 30 days is documented and then the unit is manually tracked for re-inspection.Publish Frequency: QuarterlyPublish Method: ManualData Dictionary
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Analysis of ‘1.19 Housing Quality Standards (summary)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/be9e3383-3b4c-40ca-8d16-269fb8e37af0 on 11 February 2022.
--- Dataset description provided by original source is as follows ---
Tempe’s Housing Choice Voucher program provides federally subsidized housing to eligible low-income families. The program is designed to provide housing that is affordable, decent, safe and sanitary. All dwelling units are inspected prior to a tenant moving into the unit and then inspected annually. Tenants and landlords may request inspections for maintenance issues that impact health and safety.
This data represents the resolution rate for all Housing Quality Standard issues related to life, health or safety within 24 hours.
This page provides data for the Housing Quality Standards performance measure.
The performance measure dashboard is available at 1.19 Housing Quality Standards
Additional Information
Source: Manually maintained data, Housing Pro and Excel
Contact: Levon Lamy
Contact E-Mail: Levon_Lamy@tempe.gov
Data Source Type:
Preparation Method: A tracking log in maintained for units that fail the initial inspection. The required fix timeframe of 24 hour or 30 days is documented and then the unit is manually tracked for re-inspection.
Publish Frequency: Quarterly
Publish Method: Manual
--- Original source retains full ownership of the source dataset ---
Measures the ability of housing voucher holders to find housing in the private rental market. The Housing Choice Voucher (HCV) program is the federal government?s largest low-income housing assistance program where people can seek housing in the private market. The maximum housing assistance is generally the lesser of the payment standard minus 30% of the family's monthly adjusted income or the gross rent for the unit minus 30% of monthly adjusted income. Source: Picture of Subsidized Housing, HUD Years Available: 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2022, 2023
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The data hub publishes a broad set of measures across pertinent topics such as public health, government spending, personal finances, and employment to assess the longer-term economic impact of the pandemic and the efficacy of recovery efforts. It includes indicators on health (COVID-19 cases, deaths), economy (unemployment claims, retail sales, air travel passengers, etc), standard of living (household spending, personal income, food scarcity, housing insecurity, etc), and government (federal government spending, federal reserve assets, state tax revenue, federal deficit).
https://borealisdata.ca/api/datasets/:persistentId/versions/3.1/customlicense?persistentId=doi:10.5683/SP3/LCXVCRhttps://borealisdata.ca/api/datasets/:persistentId/versions/3.1/customlicense?persistentId=doi:10.5683/SP3/LCXVCR
Note: Data on gender diverse households (formerly "2SLGBTQ+" households) has been added as of March 28th, 2025. For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset contains 18 tables which draw upon data from the 2021 Canadian Census of Population. The tables are a custom order and contain data pertaining to core housing need and characteristics of households and dwellings. This custom order was placed in collaboration with Housing, Infrastructure and Communities Canada to fill data gaps in their Housing Needs Assessment Template. 17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The 18th table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole *- Data on gender diverse households is only available for geographies (provinces, territories, CDs, CSDs) with a population count greater than 50,000. Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts greater than 10 are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Counts less than 10 are rounded to a base of 10, meaning they will be rounded to either 10 or Zero. Universe: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Tenure Including Presence of Mortgage and Subsidized Housing; Household size (7) 1. Total - Private households by tenure including presence of mortgage payments and subsidized housing 2. Owner 3. With mortgage 4. Without mortgage 5. Renter 6. Subsidized housing 7. Not subsidized housing Housing indicators in Core Housing Universe (12) 1. Total - Private Households by core housing need status 2. Households examined for core housing need 3. Households in core...
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🇺🇸 미국 English Tempe’s Housing Choice Voucher program provides federally subsidized housing to eligible low-income families. The program is designed to provide housing that is affordable decent, safe and sanitary. All dwelling units are inspected prior to a tenant moving into the unit and then inspected annually. Tenants and landlords may request inspections for maintenance issues that impact health and safety.This data represents the resolution rate for all Housing Quality Standard issues related to life, health or safety within 24 hours.This page provides data for the Housing Quality Standards performance measure. The performance measure dashboard is available at 1.19 Housing Quality StandardsAdditional InformationSource: Manually maintained data, Housing Pro and ExcelContact: Irma Hollamby CainContact E-Mail: irma_hollambycain@tempe.govData Source Type: Preparation Method: A tracking log in maintained for units that fail the initial inspection. The required fix timeframe of 24 hour or 30 days is documented and then the unit is manually tracked for re-inspection.Publish Frequency: QuarterlyPublish Method: ManualData Dictionary
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The aim of the project was to identify and compile the best available historical time series for Germany, and to complement or update them at reasonable expense. Time series were only to be included, if data for the entire period from 1834 to 2012 was at least theoretically available. An integral aspect of the concept of our project is the combination of data with critical commentaries of the time series by established expert scientists. The following themes are covered (authors in parentheses): 1. Environment, Climate, and Nature (Paul Erker) 2. Population, Households, Families (Georg Fertig/Franz Rothenbacher) 3. Migration (Jochen Oltmer) 4. Education and Science (Volker Müller-Benedict) 5. Health Service (Reinhard Spree) 6. Social Policy (Marcel Boldorf) 7. Public Finance and Taxation (Mark Spoerer) 8. Political Participation (Marc Debus) 9. Crime and Justice (Dietrich Oberwittler) 10. Work, Income, and Standard of Living (Toni Pierenkemper) 11. Culture, Tourism, and Sports (Heike Wolter/Bernd Wedemeyer-Kolwe) 12. Religion (Thomas Großbölting/Markus Goldbeck) 13. National Accounts (Rainer Metz) 14. Prices (Rainer Metz) 15. Money and Credit (Richard Tilly) 16. Transport and Communication (Christopher Kopper) 17. Agriculture (Michael Kopsidis) 18. Business, Industry, and Craft (Alfred Reckendrees) 19. Building and Housing (Günther Schulz) 20. Trade (Markus Lampe/ Nikolaus Wolf) 21. Balance of Payments (Nikolaus Wolf) 22. International Comparisons (Herman de Jong/Joerg Baten) Basically, the structure of a dataset is guided by the tables in the print publication by the Federal Agency. The print publication allows for four to eight tables for each of the 22 chapters, which means the data record is correspondingly made up of 120 tables in total. The inner structure of the dataset is a consequence of a German idiosyncrasy: the numerous territorial changes. To account for this idiosyncrasy, we decided on a four-fold data structure. Four territorial units with their respective data, are therefore differentiated in each table in separate columns: A German Confederation/Custom Union/German Reich (1834-1945).B German Federal Republic (1949-1989).C German Democratic Republic (1949-1989).D Germany since the reunification (since 1990). Years in parentheses should be considered a guideline only. It is possible that series for the territory of the old Federal Republic or the new federal states are continued after 1990, or that all-German data from before 1990 were available or were reconstructed.All time series are identified by a distinct ID consisting of an “x” and a four-digit number (for numbers under 1000 with leading zeros). The time series that exclusively contain GDR data were identified with a “c” prefix instead of the “x”.For the four territorial units, the time series are arranged in four blocks side by side within the XLSX files. That means: first all time series for the territory and the period of the Custom Union and German Reich, the next columns contain side by side all time series for the territory of the German Federal Republic / the old federal states, then – if available – those for the territory of the German Democratic Republic / the new federal states, and finally for the reunified Germany. There is at most one row for each year. Dates can be missing if no data for the respective year are available in either of the table’s time series, but no date will appear twice. The four territorial units and the resultant time periods cause a “stepwise” appearance of the data tables.
If you find anything missing, unclear, incomprehensible, improvable, etc., please contact me (kontakt@deutschland-in-daten.de). Further reading:Rahlf, Thomas, The German Time Series Dataset 1834-2012, in: Journal of Economics and Statistics 236/1 (2016), pp. 129-143. [DOI: 10.1515/jbnst-2015-1005] Open Access: Rahlf, Thomas, Voraussetzungen für eine Historische Statistik von Deutschland (19./20. Jh.), in: Vierteljahrschrift für Sozial- und Wirtschaftsgeschichte 101/3 (2014), S. 322-352. [PDF] Rahlf, Thomas (Hrsg.), Dokumentation zum Zeitreihendatensatz für Deutschland, 1834-2012, Version 01 (= Historical Social Research Transition 26v01), Köln 2015. http://dx.doi.org/10.12759/hsr.trans.26.v01.2015Rahlf, Thomas (Hrsg.), Deutschland in Daten. Zeitreihen zur Historischen Statistik, Bonn: Bundeszentrale für Politische Bildung, 2015. [EconStor]
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Tempe’s Housing Choice Voucher program provides federally subsidized housing to eligible low-income families. The program is designed to provide housing that is affordable decent, safe and sanitary. All dwelling units are inspected prior to a tenant moving into the unit and then inspected annually. Tenants and landlords may request inspections for maintenance issues that impact health and safety.This data represents the resolution rate for all Housing Quality Standard issues related to life, health or safety within 24 hours.This page provides data for the Housing Quality Standards performance measure. The performance measure dashboard is available at 1.19 Housing Quality StandardsAdditional InformationSource: Manually maintained data, Housing Pro and ExcelContact: Irma Hollamby CainContact E-Mail: irma_hollambycain@tempe.govData Source Type: Preparation Method: A tracking log in maintained for units that fail the initial inspection. The required fix timeframe of 24 hour or 30 days is documented and then the unit is manually tracked for re-inspection.Publish Frequency: QuarterlyPublish Method: ManualData Dictionary
The U.S. Department of Housing and Urban Development's (HUD) Housing Choice Voucher Program (HCVP) is the federal government's major program for assisting very low-income families, the elderly, and the disabled with decent, safe, sanitary and affordable housing in the private market. Since housing assistance is provided on behalf of the family or individual, participants are able to find their own housing, including single-family homes, townhouses and apartments. The participant is free to choose any housing that meets the requirements of the program and is not limited to units located in subsidized housing projects. Housing choice vouchers (HCV) are administered locally by public housing agencies (PHAs). The PHAs receive federal funds from HUD to administer the voucher program. A family that is issued a housing voucher is responsible for finding a suitable housing unit where the owner agrees to rent under the program. This unit may include the family's present residence. Rental units must meet minimum standards of health and safety, as determined by the PHA. A housing subsidy is paid to the landlord directly by the PHA on behalf of the participating family. The family then pays the difference between the actual rent charged by the landlord and the amount subsidized by the program. Under certain circumstances, if authorized by the PHA, a family may use its voucher to purchase a modest home.HCV locations are identified in public records by the owner and not the tenant so access to this information is restricted to help safeguard the location of HCV units. Due to the sensitive nature of the HCV locations, these are aggregated to the U.S. Census Bureau?s census tract geography.
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A Home for Everyone is the City of Boise’s (city) initiative to address needs in the community by supporting the development and preservation of housing affordable to residents on Boise budgets. A Home for Everyone has three core goals: produce new homes affordable at 60% of area median income, create permanent supportive housing for households experiencing homelessness, and preserve home affordable at 80% of area median income. This dataset includes information about all homes that count toward the city’s Home for Everyone goals.
While the “produce affordable housing” and “create permanent supportive housing” goals are focused on supporting the development of new housing, the preservation goal is focused on maintaining existing housing affordable. As a result, many of the data fields related to new development are not relevant to preservation projects. For example, zoning incentives are only applicable to new construction projects.
Data may be unavailable for some projects and details are subject to change until construction is complete. Addresses are excluded for projects with fewer than five homes for privacy reasons.
The dataset includes details on the number of “homes”. We use the word "home" to refer to any single unit of housing regardless of size, type, or whether it is rented or owned. For example, a building with 40 apartments counts as 40 homes, and a single detached house counts as one home.
The dataset includes details about the phase of each project when a project involves constructing new housing. The process for building a new development is as follows: First, one must receive approval from the city’s Planning Division, which is also known as being “entitled.” Next, one must apply for and receive a permit from the city’s Building Division before beginning construction. Finally, once construction is complete and all city inspections have been passed, the building can be occupied.
To contribute to a city goal, homes must meet affordability requirements based on a standard called area median income. The city considers housing affordable if is targeted to households earning at or below 80% of the area median income. For a three-person household in Boise, that equates to an annual income of $60,650 and monthly housing cost of $1,516. Deeply affordable housing sets the income limit at 60% of area median income, or even 30% of area median income. See Boise Income Guidelines for more details.Project Name – The name of each project. If a row is related to the Home Improvement Loan program, that row aggregates data for all homes that received a loan in that quarter or year. Primary Address – The primary address for the development. Some developments encompass multiple addresses.Project Address(es) – Includes all addresses that are included as part of the development project.Parcel Number(s) – The identification code for all parcels of land included in the development.Acreage – The number of acres for the parcel(s) included in the project.Planning Permit Number – The identification code for all permits the development has received from the Planning Division for the City of Boise. The number and types of permits required vary based on the location and type of development.Date Entitled – The date a development was approved by the City’s Planning Division.Building Permit Number – The identification code for all permits the development has received from the city’s Building Division.Date Building Permit Issued – Building permits are required to begin construction on a development.Date Final Certificate of Occupancy Issued – A certificate of occupancy is the final approval by the city for a development, once construction is complete. Not all developments require a certificate of occupancy.Studio – The number of homes in the development that are classified as a studio. A studio is typically defined as a home in which there is no separate bedroom. A single room serves as both a bedroom and a living room.1-Bedroom – The number of homes in a development that have exactly one bedroom.2-Bedroom – The number of homes in a development that have exactly two bedrooms.3-Bedroom – The number of homes in a development that have exactly three bedrooms.4+ Bedroom – The number of homes in a development that have four or more bedrooms.# of Total Project Units – The total number of homes in the development.# of units toward goals – The number of homes in a development that contribute to either the city’s goal to produce housing affordable at or under 60% of area median income, or the city’s goal to create permanent supportive housing for households experiencing homelessness. Rent at or under 60% AMI - The number of homes in a development that are required to be rented at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 61-80% AMI – The number of homes in a development that are required to be rented at between 61% and 80% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.Rent 81-120% AMI - The number of homes in a development that are required to be rented at between 81% and 120% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details.Own at or under 60% AMI - The number of homes in a development that are required to be sold at or below 60% of area median income. See the description of the dataset above for an explanation of area median income or see Boise Income Guidelines for more details. Boise defines a home as “affordable” if it is rented or sold at or below 80% of area median income.
Subjektive Bewertungen von Lebensbedingungen, Wünsche undPrioritäten, sowie Differenz zwischen Wunsch und Wirklichkeit. Themen: Wohnlage; Zuzugsjahr; Zufriedenheit mit dem Wohnort;Umzugshäufigkeit; vorherige Wohnlage, Wohnstatus und Wohnungsgröße;wichtigste Umzugsgründe; derzeitiger Wohnstatus; Anzahl der Haushalte imHaus; Umlagekosten; Art des Erwerbs der Wohnungen bzw. des Hauses;öffentliche Förderung und monatliche Belastung durchHypothekenzahlungen; Nebenkosten; Heizkosten; Instandhaltungskosten;Lastenzuschuss; Wohnberechtigungsschein; Mietkosten; Heizkosten undWarmwasserkosten; Pauschale für Heizkosten oder Warmwasserkosten;Heizkosten; Zahlungsmodus; Modernisierungsumlage; Art derModernisierungsumlagen; Beurteilung der Mietkosten und Wohngeldbezug;Höhe Wohngeld; Wohnungsgröße; Anzahl der Wohnräume; Beurteilung derWohnungsgröße; detaillierte Angaben zur Wohnungsausstattung; Beurteilungder Wohnungsausstattung; Angabe der wünschbaren Ausstattungsmerkmale füreine Standardwohnung; Baujahr des Hauses; Beurteilung des Zustands desHauses; Zufriedenheit mit den Umweltbedingungen, der Wohnumgebung undWohnzufriedenheit (Skalometer); Beschreibung derInfrastruktureinrichtungen im Wohngebiet; soziale Unterschiede in derWohngegend; Nachbarschaftsverhältnis; Zufriedenheit mit derNachbarschaft (Skalometer); Entwicklung der Wohnsituation im Laufe desLebens; wichtigste Entbehrungen und Verluste im Falle eines Wegzugs ausder derzeitigen Wohnumgebung; Haustyp; Wunschhaus und Wunschgegend;Ausländeranteil im Wohngebiet im Vergleich zu anderen Wohngegenden;aktueller Zuzug von Ausländern oder traditionelles Ausländerviertel;Herkunft der Ausländer als Aussiedler oder Flüchtlinge; Verhältnis zuden Ausländern; Beurteilung des Nachbarschaftsverhältnisses zu denAusländern; Präferenz für eine Durchmischung oder separateAusländerviertel; Kontakte zu Ausländern; Einstellungen zuEinstiegshilfen und Eingliederungsmaßnahmen für Ausländer; Umzugspläne;Umzugsgründe; Zielort des Umzugs; Renovierungspläne; Renovierung in derVergangenheit; Einstufung der eigenen Wohnung auf einem Skalometer sowieEinstufung der eigenen Wohnung vor fünf Jahren, der erreichbarenWohnung, der durchschnittlichen Wohnung von Freunden, des Durchschnittsder Bundesbürger und der Wohnung, die dem Befragten zustehe; Beurteilungder eigenen wirtschaftlichen Lage; Lebensziele (Skala); Präferenzen inder Musik, im Fernsehkonsum, und beim Bücherkonsum; Lebensstil undVerhaltensweisen; Präferenzen beim Einrichtungsstil und Kleidungsstil;Freizeitpräferenzen. Demographie: Bundesland; Urbanisierungsgrad und Art des Wohngebiets;Regierungsbezirk; Ortsgröße; Erwerbstätigkeit; Arbeitsplatzsicherheit;Wegezeiten zur Arbeit; räumliche Mobilitätsbereitschaft; Geschlecht;Alter (Geburtsmonat und Geburtsjahr); Schulabschluß; Alter beiSchulabschluß; Berufsbildung; Hochschulabschluss; Erwerbstätigkeit;berufliche Stellung früher und heute; Familienstand; Zusammenleben miteinem Partner; Kinderzahl; Selbsteinschätzung der Schichtzugehörigkeit;Konfession; Kirchenverbundenheit; Wahlverhalten bei der letztenBundestagswahl; Parteipräferenz (Sonntagsfrage); Haushaltsgröße;Haushaltsnettoeinkommen; eigenes Nettoeinkommen; Geburtsjahr der Kinder;Anzahl der Personen im Haushalt mit eigenem Einkommen; Wohnort vor 1989;PKW-Besitz; deutsche Staatsangehörigkeit; Telefonbesitz. Interviewerrating: Interviewtag und Monat; Interviewdauer. Subjective evaluations of living conditions, desires and priorities,as well as difference between desire and reality.Topics:residential area;year of arrival;satisfaction with place of residence;moving frequency;previous residential area, residential status and size of residence;most important reasons to move;current residential status;number of households in building;shared costs;manner of acquisition of residence or building;public support and monthly load from mortgage payments;additional costs;heating costs;maintenance costs;subsidy of expenses;residence authorization;rent costs;heating costs and hot water costs;fixed amount for heating costs or hot water costs;heating costs;manner of payment;shared costs for modernization;type of shared costs for modernization;judgement on rent costs and receipt of housing benefit;amount of housing benefit;size of residence;number of living-rooms;judgement on size of residence;detailed information on residential furnishings;judgement on residential furnishings;information on desirable furnishing characteristics for a standard residence;year of construction of building;judgement on condition of building;satisfaction with environmental conditions, residential surroundings andsatisfaction with housing (scale);description of infrastructure facilities in residential area;social differences in residential area;neighborhood relationship;satisfaction with neighborhood (scale);development of housing situation in the course of life;most important sacrifices and losses in case of leavingcurrent residential surroundings;type of building;desired building and desired area;proportion of foreigners in residential areain comparison to other residential areas;current influx of foreigners or traditional foreigner quarter;origins of foreigners as ethnic Germans from Eastern Europe or refugees;relationship with foreigners;judgement on neighborhood relationships with foreigners;preference for mixing or separate foreigner quarter;contacts with foreigners;attitudes to help getting set up and integration measures for foreigners;moving plans;reasons for moving;destination city of moving;renovation plans;renovation in the past;classification of one's residence on a scale as well asclassification of one's residence five years ago, an attainable residence,the average residence of friends, the average of the West German andthe residence the respondent is entitled to;judgement on personal economic situation;goals in life (scale);preferences in music, watching television, and reading books;life style and behaviors;preferences in furnishing style and clothing style;leisure preferences.Demography:state;degree of urbanization and type of residential area;administrative district;city size;employment;job security;commuting time to work;spatial mobility readiness;sex;age (month and year of birth);school degree;age at school degree;occupational training;college degree;employment;occupational position earlier and today;marital status;living together with a partner;number of children;self-assessment of social class;religious denomination;church closeness;behavior at the polls in the last Federal Parliament election;party preference (Sunday question);size of household;net household income;personal net income;year of birth of children;number of persons in household with their own income;place of residence before 1989;car possession;German citizenship;possession of a telephone.Interviewer rating:day of interview and month;length of interview.
https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de457140https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de457140
Abstract (en): This collection presents in computer-readable form the data items used to produce the corresponding printed volume of the COUNTY AND CITY DATA BOOK, 1988. Included is a broad range of statistical information, made available by federal agencies and national associations, for counties, cities, and places. Information also is provided for the 50 states, the District of Columbia, and for the United States as a whole. The dataset is comprised of seven files: a county file, a city file, and a place file, with footnote files and data dictionaries for both the county and the city files. The county data file contains information on areas such as age, agriculture, banking, construction, crime, education, federal expenditures, personal income, population, and vital statistics. The city data file includes variables such as city government, climate, crime, housing, labor force and employment, manufactures, retail trade, and service industries. Included in the place data file are items on population and money income. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.. The universe varies from item to item within the files, e.g., all persons, all housing units, all local governments, etc. 2009-05-26 SAS, SPSS, and Stata setups have been added to this data collection.2006-03-30 File CB9251.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. Users are advised that the codebook that the Census Bureau has issued for use with this dataset is a preliminary one and does not include codes and definitions for states, counties, and cities. The codes and definitions may be listed off the tape or users may refer to other sources such as the printed version of the COUNTY AND CITY DATA BOOK, 1988. For each case in the Counties Data file, there are two 1,239-character records.
The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building. This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by State Date of Coverage: 2016-2020
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If you’re a senior with low income, you may qualify for monthly Guaranteed Annual Income System payments.
The data is organized by private income levels. GAINS payments are provided on top of the Old Age Security (OAS) pension and the Guaranteed Income Supplement (GIS) payments you may receive from the federal government.
Learn more about the Ontario Guaranteed Annual Income System
This data is related to The Retirement Income System in Canada
A broad and generalized selection of 2011-2015 US Census Bureau 2015 5-year American Community Survey race, ethnicity and citizenship data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of the household income, median household income by race and by age group, Social Security income, the GINI Index, per capita income, median family income, and median household earnings by age, and by education level, in New Mexico. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. NOTE: A '-666666666' entry indicates that 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 main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population’s welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.
The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.
National coverage
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Sample survey data [ssd]
The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained.
Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.
EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey.
Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.
A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.
HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA.
Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.
Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.
The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.
Computer Assisted Personal Interview [capi]
Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.
Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.
Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.
CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet
IntroductionThis metadata is broken up into different sections that provide both a high-level summary of the Housing Element and more detailed information about the data itself with links to other resources. The following is an excerpt from the Executive Summary from the Housing Element 2021 – 2029 document:The County of Los Angeles is required to ensure the availability of residential sites, at adequate densities and appropriate development standards, in the unincorporated Los Angeles County to accommodate its share of the regional housing need--also known as the Regional Housing Needs Allocation (RHNA). Unincorporated Los Angeles County has been assigned a RHNA of 90,052 units for the 2021-2029 Housing Element planning period, which is subdivided by level of affordability as follows:Extremely Low / Very Low (<50% AMI) - 25,648Lower (50 - 80% AMI) - 13,691Moderate (80 - 120% AMI) - 14,180Above Moderate (>120% AMI) - 36,533Total - 90,052NOTES - Pursuant to State law, the projected need of extremely low income households can be estimated at 50% of the very low income RHNA. Therefore, the County’s projected extremely low income can be estimated at 12,824 units. However, for the purpose of identifying adequate sites for RHNA, no separate accounting of sites for extremely low income households is required. AMI = Area Median IncomeDescriptionThe Sites Inventory (Appendix A) is comprised of vacant and underutilized sites within unincorporated Los Angeles County that are zoned at appropriate densities and development standards to facilitate housing development. The Sites Inventory was developed specifically for the County of Los Angeles, and has built-in features that filter sites based on specific criteria, including access to transit, protection from environmental hazards, and other criteria unique to unincorporated Los Angeles County. Other strategies used within the Sites Inventory analysis to accommodate the County’s assigned RHNA of 90,052 units include projected growth of ADUs, specific plan capacity, selected entitled projects, and capacity or planned development on County-owned sites within cities. This accounts for approximately 38 percent of the RHNA. The remaining 62 percent of the RHNA is accommodated by sites to be rezoned to accommodate higher density housing development (Appendix B).Caveats:This data is a snapshot in time, generally from the year 2021. It contains information about parcels, zoning and land use policy that may be outdated. The Department of Regional Planning will be keeping an internal tally of sites that get developed or rezoned to meet our RHNA goals, and we may, in the future, develop some public facing web applications or dashboards to show the progress. There may even be periodic updates to this GIS dataset as well, throughout this 8-year planning cycle.Update History:5/31/22– Los Angeles County Board of Supervisors adopted the Housing Element on 5/17/22, and it received final certification from the State of California Department of Housing and Community Development (HCD) on 5/27/22. Data layer published on 5/31/22.Links to other resources:Department of Regional Planning Housing Page - Contains Housing Element and it's AppendicesHousing Element Update - Rezoning Program Story Map (English, and Spanish)Southern California Association of Governments (SCAG) - Regional Housing Needs AssessmentCalifornia Department of Housing and Community Development Housing Element pageField Descriptions:OBJECTID - Internal GIS IDAIN - Assessor Identification Number*ASI Status - Sites Inventory Status (Nonvacant or Vacant)SitusAddress- Site Address (Street and Number) from Assessor Data*SitusCity - Site Address (City) from Assessor Data*SitusZIP - Site Address (ZIP) from Assessor Data*LV_IV_Ratio - Land Value to Improvement Value Ratio from Assessor Data*YearBuiltMax- Maximum Year Built from Assessor Data*Use Code - Existing Land Use Code (corresponds to Use Type and Use Description) from Assessor Data*Use Type - Existing Land Use Type from Assessor Data*Use Description - Existing Land Use Description from Assessor Data*Publicly Owned - If publicly owned, indicates whether it's Federal, State, County, or Special DistrictUnits Total - Total Existing Units from Assessor Data*Supervisorial District (2021) - LA County Board of Supervisor DistrictSubmarket Area - Inclusionary Housing Submarket AreaPlanning Area - Planning Areas from the LA County Department of Regional Planning General Plan 2035Community Name - Unincorporated Community NamePlan Name - Land Use Plan Name from the LA County Department of Regional Planning (General Plan and Area / Community Plans)Zoning - 1 - Zoning from Dept. of Regional Planning - Primary Zone (in cases where there are more than one zone category present)*Zoning - 1 (% area) - Zoning from Dept. of Regional Planning - Primary Zone (% of parcel covered in cases where there are more than one zone category present)*Zoning - 2 - Zoning from Dept. of Regional Planning - Secondary Zone (in cases where there are more than one zone category present)*Zoning - 2 (% area)- Zoning from Dept. of Regional Planning - Secondary Zone (% of parcel covered in cases where there are more than one zone category present)*Zoning - 3 - Zoning from Dept. of Regional Planning - Tertiary Zone (in cases where there are more than one zone category present)*Zoning - 3 (% area) - Zoning from Dept. of Regional Planning - Tertiary Zone (% of parcel covered in cases where there are more than one zone category present)*LUP - 1 - Land Use Policy from Dept. of Regional Planning - Primary Land Use Policy (in cases where there are more than one Land Use Policy category present)*LUP - 1 (% area) - Land Use Policy from Dept. of Regional Planning - Primary Land Use Policy (% of parcel covered in cases where there are more than one Land Use Policy category present)*LUP - 2 - Land Use Policy from Dept. of Regional Planning - Secondary Land Use Policy (in cases where there are more than one Land Use Policy category present)*LUP - 2 (% area) - Land Use Policy from Dept. of Regional Planning - Secondary Land Use Policy (% of parcel covered in cases where there are more than one Land Use Policy category present)*LUP - 3 - Land Use Policy from Dept. of Regional Planning - Tertiary Land Use Policy (in cases where there are more than one Land Use Policy category present)*LUP - 3 (% area) - Land Use Policy from Dept. of Regional Planning - Tertiary Land Use Policy (% of parcel covered in cases where there are more than one Land Use Policy category present)*SP - 1 - Specific Plan from Dept. of Regional Planning - Primary Specific Plan (in cases where there are more than one Specific Plan category present)*SP - 1 (desc) - Specific Plan from Dept. of Regional Planning - Primary Specific Plan Category Description (in cases where there are more than one Specific Plan category present)*SP - 1 (% area) - Specific Plan from Dept. of Regional Planning - Primary Specific Plan (% of parcel covered in cases where there are more than one Specific Plan category present)*SP - 2 - Specific Plan from Dept. of Regional Planning - Secondary Specific Plan (in cases where there are more than one Specific Plan category present)*SP - 2 (desc) - Specific Plan from Dept. of Regional Planning - Secondary Specific Plan Category Description (in cases where there are more than one Specific Plan category present)*SP - 2 (% area) - Specific Plan from Dept. of Regional Planning - Secondary Specific Plan (% of parcel covered in cases where there are more than one Specific Plan category present)*SP - 3 - Specific Plan from Dept. of Regional Planning - Tertiary Specific Plan (in cases where there are more than one Specific Plan category present)*SP - 3 (desc) - Specific Plan from Dept. of Regional Planning - Tertiary Specific Plan Category Description (in cases where there are more than one Specific Plan category present)*SP - 3 (% area) - Specific Plan from Dept. of Regional Planning - Tertiary Specific Plan (% of parcel covered in cases where there are more than one Specific Plan category present)*Acres - Acreage of parcelLUP Units - Total - Total Land Use Policy Units (note - takes into account different densities and % area covered if there are multiple categories)Current LUP (Min Density - net or gross)- Minimum density for this category (as net or gross) per the Land Use Plan for this areaCurrent LUP (Max Density - net or gross) - Maximum density for this category (as net or gross) per the Land Use Plan for this areaSite Status - Status of the site - mostly shows as 'available', but some are flagged as 'Pending Project'Very Low Income Capacity - Total capacity for the Very Low Income level as defined in the Housing ElementLow Income Capacity - Total capacity for the Low Income level as defined in the Housing ElementModerate Income Capacity - Total capacity for the Moderate Income level as defined in the Housing ElementAbove Moderate Income Capacity - Total capacity for the Above Moderate Income level as defined in the Housing ElementRealistic Capacity - Total Realistic Capacity of parcel (totaling all income levels). Several factors went into this final calculation. See the Housing Element (Links to Other Resources above) in the following locations - "Sites Inventory - Lower Income RHNA" (p. 223), and "Rezoning - Very Low / Low Income RHNA" (p231).Income Categories - Income Categories assigned to the parcel (relates to income capacity units)Lot Consolidation ID - Parcels with a unique identfier for consolidation potential (based on parcel ownership)Lot Consolidation Notes - Specific notes for consolidationConsolidation - Adjacent Parcels - All adjacent parcels that are tied to each lot consolidation IDsUsed in Previous Housing Elements? - These are the Very Low and Low Income level parcels that showed up in previous Housing ElementsShape_Length - Perimeter (feet)Shape_Area - Area (sq feet)*As it existed in 2021
The U.S. Department of Housing and Urban Development (HUD) periodically receives "custom tabulations" of Census data from the U.S. Census Bureau that are largely not available through standard Census products. These datasets, known as "CHAS" (Comprehensive Housing Affordability Strategy) data, demonstrate the extent of housing problems and housing needs, particularly for low income households. The primary purpose of CHAS data is to demonstrate the number of households in need of housing assistance. This is estimated by the number of households that have certain housing problems and have income low enough to qualify for HUD’s programs (primarily 30, 50, and 80 percent of median income). CHAS data provides counts of the numbers of households that fit these HUD-specified characteristics in a variety of geographic areas. In addition to estimating low-income housing needs, CHAS data contributes to a more comprehensive market analysis by documenting issues like lead paint risks, "affordability mismatch," and the interaction of affordability with variables like age of homes, number of bedrooms, and type of building.This dataset is a special tabulation of the 2016-2020 American Community Survey (ACS) and reflects conditions over that time period. The dataset uses custom HUD Area Median Family Income (HAMFI) figures calculated by HUD PDR staff based on 2016-2020 ACS income data. CHAS datasets are used by Federal, State, and Local governments to plan how to spend, and distribute HUD program funds. To learn more about the Comprehensive Housing Affordability Strategy (CHAS), visit: https://www.huduser.gov/portal/datasets/cp.html, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs Data Dictionary: DD_ACS 5-Year CHAS Estimate Data by County Date of Coverage: 2016-2020