This data layer is an element of the Oregon GIS Framework. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. 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 and beyond, 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: The data release is complete as of August 14th, 2023. 1. (Added April 4th) Canada and Census Divisions = Early April 2023 2. (Added May 1st) Ontario, British Columbia, and Alberta Census Subdivisions (CSDs) = Late April 2023 3a. (Added June 8th) Manitoba and Saskatchewan CSDs 3b. (Added June 12th) Quebec CSDs = June 12th 2023 4. (Added June 30th) Newfoundland and Labrador, Prince Edward Island, New Brunswick, and Nova Scotia CSDs = Early July 2023 5. (Added August 14th) Yukon, Northwest Territories, and Nunavut CSDs = Early August 2023. 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 Census of Canada. The tables are a custom order and contains data pertaining to core housing need and characteristics of households. 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 last 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. Included alongside the data tables is a guide to HART's housing need assessment methodology. This guide is intended to support independent use of HART's custom data both to allow for transparent verification of our analysis, as well as supporting efforts to utilize the data for analysis beyond what HART did. There are many data fields in the data order that we did not use that may be of value for others. 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 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 of 10 or less are rounded to a base of 10, meaning they will be rounded to either 10 or zero. Universe: Full 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...

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...

The census is Canada's largest and most comprehensive data source conducted by Statistics Canada every five years. The Census of Population collects demographic and linguistic information on every man, woman and child living in Canada.The data shown here is provided by Statistics Canada from the 2011 Census as a custom profile data order for the City of Vancouver, using the City's 22 local planning areas. The data may be reproduced provided they are credited to Statistics Canada, Census 2011, custom order for City of Vancouver Local Areas.Data accessThis dataset has not yet been converted to a format compatible with our new platform. The following links provide access to the files from our legacy site: Census local area profiles 2011 (CSV) Census local area profiles 2011 (XLS) Dataset schema (Attributes)Please see the Census local area profiles 2011 attributes page. NoteThe 22 Local Areas is defined by the Census blocks and is equal to the City'​s 22 local planning areas and includes the Musqueam 2 reserve.Vancouver CSD (Census Subdivision) is defined by the City of Vancouver municipal boundary which excludes the Musqueam 2 reserve but includes Stanley Park. Vancouver CMA (Census Metropolitan Area) is defined by the Metro Vancouver boundary which includes the following Census Subdivisions: Vancouver, Surrey, Burnaby, Richmond, Coquitlam, District of Langley, Delta, District of North Vancouver, Maple Ridge, New Westminster, Port Coquitlam, City of North Vancouver, West Vancouver, Port Moody, City of Langley, White Rock, Pitt Meadows, Greater Vancouver A, Bowen Island, Capilano 5, Anmore, Musqueam 2, Burrard Inlet 3, Lions Bay, Tsawwassen, Belcarra, Mission 1, Matsqui 4, Katzie 1, Semiahmoo, Seymour Creek 2, McMillian Island 6, Coquitlam 1, Musqueam 4, Coquitlam 2, Katzie 2, Whonnock 1, Barnston Island 3, and Langley 5. In 2011 Statistics Canada replaced the "long form" census with a voluntary National Household Survey. The result of the survey will not be directly comparable with previous census data. In 2006 there were changes made to the definition of households. A number of Single Room Occupancy and Seniors facilities were considered to be dwellings in 2001, and collective dwellings in 2006. The City believes a similar change occurred on some properties between 2006 and 2011. This would explain why the numbers of "Apartments under 5 stories" has fallen in some locations.Note that for the first time in 2011, three language questions (knowledge of official languages, home language and mother tongue) were included on the census questionnaire that was administered to 100% of the population.Language data and analysis published for all censuses since 1996 have been based almost exclusively on responses from the long-form census questionnaire administered to 20% of the population. However, Statistics Canada has observed changes in patterns of response to both the mother tongue and home language questions that appear to have arisen from changes in the placement and context of the language questions on the 2011 Census questionnaire relative to previous censuses. As a result, Canadians appear to have been less inclined than in previous censuses to report languages other than English or French as their only mother tongue, and also more inclined to report multiple languages as their mother tongue and as the language used most often at home. Data currencyThe data for Census 2011 was collected in May 2011. Data accuracyStatistics Canada is committed to protect the privacy of all Canadians and the confidentiality of the data they provide to us. As part of this commitment, some population counts of geographic areas are adjusted in order to ensure confidentiality. Counts of the total population are rounded to a base of 5 for any dissemination block having a population of less than 15. Population counts for all standard geographic areas above the dissemination block level are derived by summing the adjusted dissemination block counts. The adjustment of dissemination block counts is controlled to ensure that the population counts for dissemination areas will always be within 5 of the actual values. The adjustment has no impact on the population counts of census divisions and large census subdivisions. Websites for further information Statistics Canada 2011 Census Dictionary Local area boundary dataset

Abstract

A crosswalk dataset matching US ZIP codes to corresponding census tracts

Documentation

The denominators used to calculate the address ratios are the ZIP code totals. When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file.

**Example: **ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record.

So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code.

https://redivis.com/fileUploads/4ecb405e-f533-4a5b-8286-11e56bb93368%3E" alt="">(Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.)

Census tract definition

A census tract, census area, census district or meshblock is a geographic region defined for the purpose of taking a census. Sometimes these coincide with the limits of cities, towns or other administrative areas and several tracts commonly exist within a county. In unincorporated areas of the United States these are often arbitrary, except for coinciding with political lines.

Further reading

The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.

Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. URL: https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf

Contact information

Questions regarding these crosswalk files can be directed to Alex Din with the subject line HUD-Crosswalks.

Acknowledgement

This dataset is taken from the U.S. Department of Housing and Urban Development (HUD) office: https://www.huduser.gov/portal/datasets/usps_crosswalk.html#codebook

The Core Based Statistical Areas boundaries were defined by OMB based on the 2010 Census, and the dataset was updated on August 09, 2019 from the United States Census Bureau (USCB) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Metropolitan and Micropolitan Statistical Areas are together termed Core Based Statistical Areas (CBSAs) and are defined by the Office of Management and Budget (OMB) and consist of the county or counties or equivalent entities associated with at least one urban core (urbanized area or urban cluster) of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration with the core as measured through commuting ties with the counties containing the core. Categories of CBSAs are: Metropolitan Statistical Areas, based on urbanized areas of 50,000 or more population; and Micropolitan Statistical Areas, based on urban clusters of at least 10,000 population but less than 50,000 population. The CBSA boundaries are those defined by OMB based on the 2010 Census, published in 2013, and updated in 2018. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529014

Housing Assessment Resource Tools (HART) This dataset contains 2 tables and 5 files which draw upon data from the 2021 Census of Canada. The tables are a custom order and contain data pertaining to older adults and housing need. The 2 tables have 6 dimensions in common and 1 dimension that is unique to each table. Table 1's unique dimension is the "Ethnicity / Indigeneity status" dimension which contains data fields related to visible minority and Indigenous identity within the population in private households. Table 2's unique dimension is "Structural type of dwelling and Period of Construction" which contains data fields relating to the structural type and period of construction of the dwelling. Each of the two tables is then split into multiple files based on geography. Table 1 has two files: Table 1.1 includes Canada, Provinces and Territories (14 geographies), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); and Table 1.2 includes Canada and the CMAs of Canada (44). Table 2 has three files: Table 2.1 includes Canada, Provinces and Territories (14), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); Table 2.2 includes Canada and the CMAs of Canada excluding Ontario and Quebec (20 geographies); and Table 2.3 includes Canada and the CMAs of Canada that are in Ontario and Quebec (25 geographies). 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 as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia) as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), as a whole as well as all census divisions (CDs) within the 3 territories - All 43 census metropolitan areas (CMAs) in Canada 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 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. Universe: Full Universe: Population aged 55 years and over in owner and tenant households with household total income greater than zero in non-reserve non-farm private dwellings. Definition of 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: Table 1: Age / Gender (12) 1. Total – Population 55 years and over 2. Men+ 3. Women+ 4. 55 to 64 years 5. Men+ 6. Women+ 7. 65+ years 8. Men+ 9. Women+ 10. 85+ 11. Men+ 12. Women+ Housing indicators (13) 1. Total – Private Households by core housing need status 2. Households below one standard only...

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include legally-recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census, the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county subdivisions. The boundaries of most legal MCDs are as of January 1, 2021, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CCDs, delineated in 21 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. 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 Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. 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.Field Definition:STATEFP10 - 2010 Census State FIPS codesCOUNTYFP10 - 2010 Census County FIPS CodesTRACTCE10 - 2010 Census Census TractGEOID10 - "Census tract identifier; a concatenation of 2010 Census state FIPS code, county FIPS code, and census tract code"NAME10 - "2010 Census census tract name, this is the census tract code converted to an integer or integer plus two-digit decimal if the last two characters of the code are not both zeros"NAMELSAD10 - 2010 Census translated legal/statistical area description and the census tract nameMTFCC10 - 2010 Census MAF/TIGER featture class codeFUNCSTAT10 - 2010 Census Functional Statitical CodeALAND10 - 2010 Census Area LandAWATER10 - 2010 Census Area waterINTPTLAT10 - 2010 Census Internal Point (Latitude)INTPTLON10 - 2010 Census Internal Point (Longtitude)POPULATION - Total PopulationHOUSING_UNITS - Total Housing units

Abstract

A crosswalk matching US ZIP codes to corresponding CBSA (core-based statistical area)

Documentation

The denominators used to calculate the address ratios are the ZIP code totals. When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file.

**Example: **ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record.

So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code.

https://redivis.com/fileUploads/4ecb405e-f533-4a5b-8286-11e56bb93368%3E" alt="">(Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.)

CBSA definition

A core-based statistical area (CBSA) is a U.S. geographic area defined by the Office of Management and Budget (OMB) that consists of one or more counties (or equivalents) anchored by an urban center of at least 10,000 people plus adjacent counties that are socioeconomically tied to the urban center by commuting. Areas defined on the basis of these standards applied to Census 2000 data were announced by OMB in June 2003. These standards are used to replace the definitions of metropolitan areas that were defined in 1990. The OMB released new standards based on the 2010 Census on July 15, 2015.

Further reading

The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.

Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. URL: https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf

Contact authors

Questions regarding these crosswalk files can be directed to Alex Din with the subject line HUD-Crosswalks.

Acknowledgement

This dataset is taken from the U.S. Department of Housing and Urban Development (HUD) office: https://www.huduser.gov/portal/datasets/usps_crosswalk.html#codebook

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau to show population change from 2000 to2019. It shows the population change from 2000 to2019 by ARC 20 County. This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission using data from the U.S. Census Bureau.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimated value is expressed as a number, then its MOE will also be a number; if the estimated value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2015-2019). Therefore, these data do not represent anyone specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes, and so forth for all metrics.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% Confidence Interval, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e18

Estimate from 2015-19 ACS

_m19

Margin of Error from 2015-19 ACS

_00_v19

Decennial 2000 in 2019 geography boundary

_00_19

Change, 2000-19

_e10_v19

Estimate from 2006-10 ACS in 2019 geography boundary

_m10_v19

Margin of Error from 2006-10 ACS in 2019 geography boundary

_e10_19

Change, 2010-19

The rural-urban commuting area codes (RUCA) classify U.S. census tracts using measures of urbanization, population density, and daily commuting from the decennial census. The most recent RUCA codes are based on data from the 2000 decennial census. The classification contains two levels. Whole numbers (1-10) delineate metropolitan, micropolitan, small town, and rural commuting areas based on the size and direction of the primary (largest) commuting flows. These 10 codes are further subdivided to permit stricter or looser delimitation of commuting areas, based on secondary (second largest) commuting flows. The approach errs in the direction of more codes, providing flexibility in combining levels to meet varying definitional needs and preferences. The 1990 codes are similarly defined. However, the Census Bureau's methods of defining urban cores and clusters changed between the two censuses. And, census tracts changed in number and shapes. The 2000 rural-urban commuting codes are not directly comparable with the 1990 codes because of these differences. An update of the Rural-Urban Commuting Area Codes is planned for late 2013.

The Census Bureau released revised delineations for urban areas on December 29, 2022. The new criteria (contained in this Federal Register Notice) is based primarily on housing unit density measured at the census block level. The minimum qualifying threshold for inclusion as an urban area is an area that contains at least 2,000 housing units or has a population of at least 5,000 persons. It also eliminates the classification of areas as “urban clusters/urbanized areas”. This represents a change from 2010, where urban areas were defined as areas consisting of 50,000 people or more and urban clusters consisted of at least 2,500 people but less than 50,000 people with at least 1,500 people living outside of group quarters. Due to the new population thresholds for urban areas, 36 urban clusters in California are no longer considered urban areas, leaving California with 193 urban areas after the new criteria was implemented.

The State of California experienced an increase of 1,885,884 in the total urban population, or 5.3%. However, the total urban area population as a percentage of the California total population went down from 95% to 94.2%. For more information about the mapped data, download the Excel spreadsheet here.

Please note that some of the 2020 urban areas have different names or additional place names as a result of the inclusion of housing unit counts as secondary naming criteria.

Please note there are four urban areas that cross state boundaries in Arizona and Nevada. For 2010, only the parts within California are displayed on the map; however, the population and housing estimates represent the entirety of the urban areas. For 2020, the population and housing unit estimates pertains to the areas within California only.

Data for this web application was derived from the 2010 and 2020 Censuses (2010 and 2020 Census Blocks, 2020 Urban Areas, and Counties) and the 2016-2020 American Community Survey (2010 -Urban Areas) and can be found at data.census.gov.

For more information about the urban area delineations, visit the Census Bureau's Urban and Rural webpage and FAQ.

To view more data from the State of California Department of Finance, visit the Demographic Research Unit Data Hub.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. In New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont), the Office of Management and Budget (OMB) has defined an alternative county subdivision (generally cities and towns) based definition of Core Based Statistical Areas (CBSAs) known as New England City and Town Areas (NECTAs). NECTAs are defined using the same criteria as Metropolitan Statistical Areas and Micropolitan Statistical Areas and are identified as either metropolitan or micropolitan, based, respectively, on the presence of either an urban area of 50,000 or more population or an urban cluster of at least 10,000 and less than 50,000 population. A NECTA containing a single core urban area with a population of at least 2.5 million may be subdivided to form smaller groupings of cities and towns referred to as NECTA Divisions. The NECTA boundaries are those defined by OMB based on the 2010 Census, published in 2013, and updated in 2018.

This is a series-level metadata record. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national filewith no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independentdata set, or they can be combined to cover the entire nation. In New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont), the Office of Management and Budget (OMB) has defined an alternative county subdivision (generally cities and towns) based definition of Core Based Statistical Areas (CBSAs) known as New England City and Town Areas (NECTAs). NECTAs are defined using the same criteria as Metropolitan Statistical Areas and Micropolitan Statistical Areas and are identified as either metropolitan or micropolitan, based, respectively, on the presence of either an urban area of 50,000 or more population or an urban cluster of at least 10,000 and less than 50,000 population. A NECTA containing a single core urban area with a population of at least 2.5 million may be subdivided to form smaller groupings of cities and towns referred to as NECTA Divisions. The NECTA boundaries are those defined by OMB based on the 2010 Census, published in 2013, and updated in 2017.

The 2020 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. In New England (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont), the Office of Management and Budget (OMB) has defined an alternative county subdivision (generally cities and towns) based definition of Core Based Statistical Areas (CBSAs) known as New England City and Town Areas (NECTAs). NECTAs are defined using the same criteria as Metropolitan Statistical Areas and Micropolitan Statistical Areas and are identified as either metropolitan or micropolitan, based, respectively, on the presence of either an urban area of 50,000 or more population or an urban cluster of at least 10,000 and less than 50,000 population. A NECTA containing a single core urban area with a population of at least 2.5 million may be subdivided to form smaller groupings of cities and towns referred to as NECTA Divisions. The generalized boundaries in this file are based on those defined by OMB based on the 2010 Census, published in 2013, and updated in 2018.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include legally-recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census, the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county subdivisions. The boundaries of most legal MCDs are as of January 1, 2015, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CCDs, delineated in 20 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.