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.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Webpage with links to Excel files For complete information, please visit https://data.gov.

The 2013 Rural-Urban Continuum Codes form a classification scheme that distinguishes metropolitan counties by the population size of their metro area, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area. The official Office of Management and Budget (OMB) metro and nonmetro categories have been subdivided into three metro and six nonmetro categories. Each county in the U.S. is assigned one of the 9 codes. This scheme allows researchers to break county data into finer residential groups, beyond metro and nonmetro, particularly for the analysis of trends in nonmetro areas that are related to population density and metro influence. The Rural-Urban Continuum Codes were originally developed in 1974. They have been updated each decennial since (1983, 1993, 2003, 2013), and slightly revised in 1988. Note that the 2013 Rural-Urban Continuum Codes are not directly comparable with the codes prior to 2000 because of the new methodology used in developing the 2000 metropolitan areas. See the Documentation for details and a map of the codes. An update of the Rural-Urban Continuum Codes is planned for mid-2023.

2010 Rural-Urban Commuting Area Codes (revised 7/3/2019) , joined to SD, SPA, and CSA as of Dec. 2023.Data from https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes/. Downloaded 1/9/2024.Primary RUCA Codes, 20101 Metropolitan area core: primary flow within an urbanized area (UA)2 Metropolitan area high commuting: primary flow 30% or more to a UA3 Metropolitan area low commuting: primary flow 10% to 30% to a UA4 Micropolitan area core: primary flow within an Urban Cluster of 10,000 to 49,999 (large UC)5 Micropolitan high commuting: primary flow 30% or more to a large UC6 Micropolitan low commuting: primary flow 10% to 30% to a large UC7 Small town core: primary flow within an Urban Cluster of 2,500 to 9,999 (small UC)8 Small town high commuting: primary flow 30% or more to a small UC9 Small town low commuting: primary flow 10% to 30% to a small UC10 Rural areas: primary flow to a tract outside a UA or UC99 Not coded: Census tract has zero population and no rural-urban identifier informationSecondary RUCA Codes, 20101 Metropolitan area core: primary flow within an urbanized area (UA)1No additional code1.1Secondary flow 30% to 50% to a larger UA2 Metropolitan area high commuting: primary flow 30% or more to a UA2No additional code2.1Secondary flow 30% to 50% to a larger UA3 Metropolitan area low commuting: primary flow 10% to 30% to a UA3No additional code4 Micropolitan area core: primary flow within an Urban Cluster of 10,000 to 49,999 (large UC)4No additional code4.1Secondary flow 30% to 50% to a UA5 Micropolitan high commuting: primary flow 30% or more to a large UC5No additional code5.1Secondary flow 30% to 50% to a UA6 Micropolitan low commuting: primary flow 10% to 30% to a large UC6No additional code7 Small town core: primary flow within an Urban Cluster of 2,500 to 9,999 (small UC)7No additional code7.1Secondary flow 30% to 50% to a UA7.2Secondary flow 30% to 50% to a large UC8 Small town high commuting: primary flow 30% or more to a small UC8No additional code8.1Secondary flow 30% to 50% to a UA8.2Secondary flow 30% to 50% to a large UC9 Small town low commuting: primary flow 10% to 30% to a small UC9No additional code10 Rural areas: primary flow to a tract outside a UA or UC10No additional code10.1Secondary flow 30% to 50% to a UA10.2Secondary flow 30% to 50% to a large UC10.3Secondary flow 30% to 50% to a small UC99 Not coded: Census tract has zero population and no rural-urban identifier informationData Sources:Population data for census tracts, by urban-rural components, 2010:U.S. Census Bureau, Census of Population and Housing, 2010. Summary File 1, FTP download: https://www.census.gov/census2000/sumfile1.htmlAssignment of census tracts to specific urban areas or to rural status was completed using ESRI's ArcMap software and Census Bureau shape files:U.S. Census Bureau. Tiger/Line Shapefiles, Census Tracts and Urban Areas, 2010: https://www.census.gov/programs-surveys/geography.htmlCensus tract commuting flows, 2006-2010:U.S. Census Bureau, American Community Survey 2006-2010 Five-year estimates. Special Tabulation: Census Transportation Planning Products, Part 3, Worker Home-to-Work Flow Tables. https://www.fhwa.dot.gov/planning/census_issues/ctpp/data_products/2006-2010_table_list/sheet04.cfmTract-to-tract commuting flow files were constructed from ACS data as part of a special tabulation for the Department of Transportation—the Census Transportation Planning Package. To derive estimates for small geographic units such as census tracts, information collected annually from over 3.5 million housing units was combined across 5 years (2006-2010). As with all survey data, ACS estimates are not exact because they are based on a sample. In general, the smaller the estimate, the larger the degree of uncertainty associated with it.

Frontier and Remote Area (FAR) codes provide a statistically-based, nationally-consistent, and adjustable definition of territory in the U.S. characterized by low population density and high geographic remoteness.

To assist in providing policy-relevant information about conditions in sparsely settled, remote areas of the U.S. to public officials, researchers, and the general public, ERS has developed ZIP-code-level frontier and remote (FAR) area codes. The aim is not to provide a single definition. Instead, it is to meet the demand for a delineation that is both geographically detailed and adjustable within reasonable ranges, in order to be usefully applied in diverse research and policy contexts. This initial set, based on urban-rural data from the 2000 decennial census, provides four separate FAR definition levels, ranging from one that is relatively inclusive (18 million FAR residents) to one that is more restrictive (4.8 million FAR residents).This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: State and ZIP code level tables For complete information, please visit https://data.gov.

This dataset was created for the Appalachia Ohio GIS Collaborative Hub by taking the 2020 Census TIGER/Line Tract boundaries and ZIP Code boundaries, filtered for Ohio, and joining them to the 2020 USDA Rural Urban Commuting Area (RUCA) Codes tables downloaded from the USDA. RUCA codes are a classification scheme allowing for flexible, census tract and ZIP code delineation of rural and urban areas throughout the United States and its territories. There are two layers in this dataset, census tracts and ZIP codes. By default they are symbolized by the Primary RUCA code. Both layers include Primary and Secondary RUCA codes. The census tract layer additionally includes the Urban Area Cluster associated with a tract, the Urban Core Type, primary and secondary commuting destinations, population, and population density. More detail about attributes can be found in the description for each layer.2020 Rural-Urban Commuting Area (RUCA) CodesThe USDA, Economic Research Service’s (ERS) Rural-Urban Commuting Area (RUCA) codes are a classification scheme allowing for flexible, census tract delineation of rural and urban areas throughout the United States and its territories. RUCA codes were designed to address a major limitation associated with county-based classifications; they are often too large to accurately delineate boundaries between rural and urban areas. The more geographically-detailed information provided by RUCA codes can be used to improve rural research and policy—such as addressing concerns that remote, rural communities in large metropolitan counties are not eligible for some rural assistance programs.The RUCA codes consist of two levels. The primary RUCA codes establish urban cores and the census tracts that are the most economically integrated with those cores through commuting. The secondary RUCA codes indicate whether a census tract has a strong secondary connection (through commuting) to an even larger urban core. This two-level structure provides flexibility in combining levels to meet varying definitional needs and preferences. The RUCA codes were created using census tract data and were subsequently adapted to ZIP codes.The tables used for the joins were the USDA 2020 Rural-Urban Commuting Area Codes, census tracts table and the 2020 Rural-Urban Commuting Area Codes, ZIP codes table. Both were marked as last updated 7/31/2025, and are available for download from https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes. Tables used for join were downloaded 9/25/2025.

Summary File 1 (SF1) Urban/Rural Update contains summary statistics on population and housing subjects derived from the responses to the 2010 Census questionnaire. Population items include sex, age, race, Hispanic or Latino origin, household relationship, household type, household size, family type, family size, and group quarters. Housing items include occupancy status, vacancy status, and tenure (whether a housing unit is owner-occupied or renter-occupied). The summary statistics are presented in 333 tables, which are tabulated for multiple levels of observation (called "summary levels" in the Census Bureau's nomenclature), including, but not limited to, regions, divisions, states, metropolitan/micropolitan statistical areas, counties, county subdivisions, places, congressional districts, American Indian Areas, Alaska Native Areas, Hawaiian Home Lands, ZIP Code tabulation areas, census tracts, block groups, and blocks. There are 177 population tables and 58 housing tables shown down to the block level; 84 population tables and 4 housing tables shown down to the census tract level; and 10 population tables shown down to the county level. Some of the summary areas are iterated for "geographic components" or portions of geographic areas, e.g., the principal city of a metropolitan statistical area (MSA) or the urban and rural portions of a MSA. With one variable per table cell and additional variables with geographic information, the collection comprises 2,597 data files, 49 per state, the District of Columbia, Puerto Rico, and the National File. The Census Bureau released SF1 in three stages: initial release, National Update, and Urban/Rural Update. The National Update added summary levels for the United States, regions, divisions, and geographic areas that cross state lines such as Combined Statistical Areas. This update adds urban and rural population and housing unit counts, summary levels for urban areas and the urban/rural components of census tracts and block groups, geographic components involving urbanized areas and urban clusters, and two new tables (household type by relationship for the population 65 years and over and a new tabulation of the total population by race). The initial release and National Update is available as ICPSR 33461. ICPSR supplies this data collection in 54 ZIP archives. There is a separate archive for each state, the District of Columbia, Puerto Rico, and the National File. The last archive contains a Microsoft Access database shell and additional documentation files besides the codebook.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 27045 (Rural Hall, NC). Interactive charts load automatically as you scroll for improved performance.

The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. Getting started guide To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. The geographic coordinates, which represent the standard geostatistical areas linked to each postal codeOM on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Registers and Geography Division released the first version of the PCCF, which linked postal codesOM to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codesOM are directly geocoded to 2016 Census geography while others are linked via various conversion processes. A quality indicator for the confidence of this linkage is available in the PCCF.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 15075 (Rural Ridge, PA). Interactive charts load automatically as you scroll for improved performance.

Map for question/section 1: "Who lives there?"Containing Rural areas as defined by US Census 2013 urban/rural defined areas, http://nmcdc.maps.arcgis.com/home/item.html?id=fbd1e91ec0a54c58b6fcca8a5138c1fc. Filtered to include: 'RURAL' in 2 category designation, Population of LESS THAN 5001 persons, AND % Low access low-income at 20 miles to AT LEAST 5%. Map displaying by Esri 2019 Age Dependency Ratios.

Census tracts with 4, 5, 6 and 10 tier classifications. We'll be adding 2020 data when its available from the USDA or the Census.From Asnake Hailu,The schemes shared in the RUCAGuide.pdf are DOH modified layers, prepared merely for epidemiological purposes [I.e., to delineate geography for a comprehensive epidemiologic assessment, describing rural-urban differences in demographics, health outcomes, risk factors, access to services, and the like.] Those are not as such rural/urban designation tools for census block areas, nor for any of the other geography categories. The files with the DOH modified layers are available at https://doh.wa.gov/public-health-healthcare-providers/rural-health/data-maps-and-other-resources under the sub-county level: Zip Code and Census Tract sub-heading.Please note: those files are essentially a decade old. We were anticipating to update our core products that are on our website, if and when the Federal Office of Rural Health and Policy (FORHP) produces a newer version of RUCA codes based on census 2020. The FORHP customarily contracts with a university for that task. We are three years away from 2020, except there is no update posted on the webpage I am familiar to get the original RUCA delineations. Here is a path where I go to check for the newer version: https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes/

The Daily and Annual PM2.5, O3, and NO2 Concentrations at ZIP Codes for the Contiguous U.S., 2000-2016, v1.0 data set contains daily and annual concentration predictions for Fine Particulate Matter (PM2.5), Ozone (O3), and Nitrogen Dioxide (NO2) pollutants at ZIP Code-level for the years 2000 to 2016. Ensemble predictions of three machine-learning models were implemented (Random Forest, Gradient Boosting, and Neural Network) to estimate the daily PM2.5, O3, and NO2 at the centroids of 1km x 1km grid cells across the contiguous U.S. for 2000 to 2016. The predictors included air monitoring data, satellite aerosol optical depth, meteorological conditions, chemical transport model simulations, and land-use variables. The ensemble models demonstrated excellent predictive performance with 10-fold cross-validated R-squared values of 0.86 for PM2.5, 0.86 for O3, and 0.79 for NO2. These high-resolution, well-validated predictions allow for estimates of ZIP Code-level pollution concentrations with a high degree of accuracy. For general ZIP Codes with polygon representations, pollution levels were estimated by averaging the predictions of grid cells whose centroids lie inside the polygon of that ZIP Code; for other ZIP Codes such as Post Offices or large volume single customers, they were treated as a single point and predicted their pollution levels by assigning the predictions using the nearest grid cell. The polygon shapes and points with latitudes and longitudes for ZIP Codes were obtained from Esri and the U.S. ZIP Code Database and were updated annually. The data include about 31,000 general ZIP Codes with polygon representations, and about 10,000 ZIP Codes as single points. The aggregated ZIP Code-level, daily predictions are applicable in research such as environmental epidemiology, environmental justice, health equity, and political science, by linking with ZIP Code-level demographic and medical data sets, including national inpatient care records, medical claims data, census data, U.S. Census Bureau American CommUnity Survey (ACS), and Area Deprivation Index (ADI). The data are particularly useful for studies on rural populations who are under-represented due to the lack of air monitoring sites in rural areas. Compared with the 1km grid data, the ZIP Code-level predictions are much smaller in size and are manageable in personal computing environments. This greatly improves the inclusion of scientists in different fields by lowering the key barrier to participation in air pollution research. The Units are ug/m^3 for PM2.5 and ppb for O3 and NO2.

The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. The geographic coordinates, which represent the standard geostatistical areas linked to each postal codeOM on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Registers and Geography Division released the first version of the PCCF, which linked postal codesOM to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codesOM are directly geocoded to 2016 Census geography while others are linked via various conversion processes. A quality indicator for the confidence of this linkage is available in the PCCF.

ZIP Code business counts data for Maptitude mapping software are from Caliper Corporation and contain aggregated ZIP Code Business Patterns (ZBP) data and Rural-Urban Commuting Area (RUCA) data.

This dataset contains measures of the urban/rural characteristics of each census tract in the United States. These include proportions of urban and rural population, population density, rural/urban commuting area (RUCA) codes, and RUCA-based four- and seven- category urbanicity scales. A curated version of this data is available through ICPSR at https://www.icpsr.umich.edu/web/ICPSR/studies/38606/versions/V1

ZIP Code boundaries were developed from street delivery 5-digit ZIP Codes. These polygons identify areas where mail is delivered (from a city block or two to a whole rural town).ZIPCODE: Zip Code number NAME: Community name, per USPS.

Demographics, population, housing, income, education, schools, and geography for ZIP Code 24368 (Rural Retreat, VA). Interactive charts load automatically as you scroll for improved performance.

(StatCan Product) Labour Income Profile for all city totals and rural postal codes in Canada in 2012. Customization details: This information product has been customized to present information on the 2012 Labour Income Profile for all city totals and rural postal codes in Canada.. Variables included: - All persons - Taxfilers - Total income - Labour income - Employment income - Wages/salaries/commissions - Self-employment - Wages, salaries and commissions Only - Self-employment only - Wages, salaries, commissions and self-employment - Employment Insurance (EI)

Refer to the 'Current Geographic Boundaries Table' layer for a list of all current geographies and recent updates.

This dataset is the definitive version of the annually released urban rural (UR) boundaries as at 1 January 2025 as defined by Stats NZ, clipped to the coastline. This clipped version has been created for cartographic purposes and so does not fully represent the official full extent boundaries. This version contains 689 UR areas, including 195 urban areas and 402 rural settlements.

Urban rural (UR) is an output geography that classifies New Zealand into areas that share common urban or rural characteristics and is used to disseminate a broad range of Stats NZ’s social, demographic and economic statistics.

The UR separately identifies urban areas, rural settlements, other rural areas, and water areas. Urban areas and rural settlements are form-based geographies delineated by the inspection of aerial imagery, local government land designations on district plan maps, address registers, property title data, and any other available information. However, because the underlying meshblock pattern is used to define the geographies, boundaries may not align exactly with local government land designations or what can be seen in aerial images. Other rural areas, and bodies of water represent areas not included within an urban area.

Urban areas are built from the statistical area 2 (SA2) geography, while rural and water areas are built from the statistical area 1 (SA1) geography.

Urban areas

Urban areas are statistically defined areas with no administrative or legal basis. They are characterised by high population density with many built environment features where people and buildings are located close together for residential, cultural, productive, trade and social purposes.

Urban areas are delineated using the following criteria. They:

form a contiguous cluster of one or more SA2s,

contain an estimated resident population of more than 1,000 people and usually have a population density of more than 400 residents or 200 address points per square kilometre,

have a high coverage of built physical structures and artificial landscapes such as:

• residential dwellings and apartments,
• commercial structures, such as factories, office complexes, and shopping centres,
• transport and communication facilities, such as airports, ports and port facilities, railway stations, bus stations and similar transport hubs, and communications infrastructure,
• medical, education, and community facilities,
• tourist attractions and accommodation facilities,
• waste disposal and sewerage facilities,
• cemeteries,
• sports and recreation facilities, such as stadiums, golf courses, racecourses, showgrounds, and fitness centres,
• green spaces, such as community parks, gardens, and reserves,

have strong economic ties where people gather together to work, and for social, cultural, and recreational interaction,

have planned development within the next 5–8 years.

Urban boundaries are independent of local government and other administrative boundaries. However, the Richmond urban area, which is mainly in the Tasman District, is the only urban area that crosses territorial authority boundaries

Rural areas

Rural areas are classified as rural settlements or other rural.

Rural settlements

Rural settlements are statistically defined areas with no administrative or legal basis. A rural settlement is a cluster of residential dwellings about a place that usually contains at least one community or public building.

Rural settlements are delineated using the following criteria. They:

form a contiguous cluster of one or more SA1s,

contain an estimated resident population of 200–1,000, or at least 40 residential dwellings,

represent a reasonably compact area or have a visible centre of population with a population density of at least 200 residents per square kilometre or 100 address points per square kilometre,

contain at least one community or public building, such as a church, school, or shop.

To reach the target SA2 population size of more than 1,000 residents, rural settlements are usually included with other rural SA1s to form an SA2. In some instances, the settlement and the SA2 have the same name, for example, Kirwee rural settlement is part of the Kirwee SA2.

Some rural settlements whose populations are just under 1,000 are a single SA2. Creating separate SA2s for these rural settlements allows for easy reclassification to urban areas if their populations grow beyond 1,000.

Other rural

Other rural areas are the mainland areas and islands located outside urban areas or rural settlements. Other rural areas include land used for agriculture and forestry, conservation areas, and regional and national parks. Other rural areas are defined by territorial authority.

Water

Bodies of water are classified separately, using the land/water demarcation classification described in the Statistical standard for meshblock. These water areas are not named and are defined by territorial authority or regional council.

The water classes include:

inland water – non-contiguous, defined by territorial authority,

inlets (which also includes tidal areas and harbours) – non-contiguous, defined by territorial authority,

oceanic – non-contiguous, defined by regional council.

To minimise suppression of population data, separate meshblocks have been created for marinas. These meshblocks are attached to adjacent land in the UR geography.

Non-digitised

The following 4 non-digitised UR areas have been aggregated from the 16 non-digitised meshblocks/SA2s.

6901; Oceanic outside region, 6902; Oceanic oil rigs, 6903; Islands outside region, 6904; Ross Dependency outside region.

UR numbering and naming

Each urban area and rural settlement is a single geographic entity with a name and a numeric code.

Other rural areas, inland water areas, and inlets are defined by territorial authority; oceanic areas are defined by regional council; and each have a name and a numeric code.

Urban rural codes have four digits. North Island locations start with a 1, South Island codes start with a 2, oceanic codes start with a 6 and non-digitised codes start with 69.

Urban rural indicator (IUR)

The accompanying urban rural indicator (IUR) classifies the urban, rural, and water areas by type. Urban areas are further classified by the size of their estimated resident population:

• major urban area – 100,000 or more residents,
• large urban area – 30,000–99,999 residents,
• medium urban area – 10,000–29,999 residents,
• small urban area – 1,000–9,999 residents.

This was based on 2018 Census data and 2021 population estimates. Their IUR status (urban area size/rural settlement) may change if the 2025 Census population count moves them up or down a category.

The indicators, by name, with their codes in brackets, are:

urban area – major urban (11), large urban (12), medium urban (13), small urban (14),

rural area – rural settlement (21), rural other (22),

water – inland water (31), inlet (32), oceanic (33).

Clipped Version

This clipped version has been created for cartographic purposes and so does not fully represent the official full extent boundaries.

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High definition version

This high definition (HD) version is the most detailed geometry, suitable for use in GIS for geometric analysis operations and for the computation of areas, centroids and other metrics. The HD version is aligned to the LINZ cadastre.

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Macrons

Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

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Digital data

Digital boundary data became freely available on 1 July 2007.

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Further information

To download geographic classifications in table formats such as CSV please use Ariā

For more information please refer to the Statistical standard for geographic areas 2023.

Contact: geography@stats.govt.nz

Urban rural 2023 update

UR 2023 is the first major update of the geography since it was first created in 2018. The update is to ensure UR geographies are relevant and meet criteria before each five-yearly population and dwelling census. UR 2023 contains 13 new rural settlements and 7 new small urban areas. Updates were made to reflect real world change including new subdivisions and motorways, and to improve delineation of urban areas and rural settlements. The Wānaka urban area, whose population has grown to be more than 10,000 based on population estimates, has been reclassified to a medium urban area in the 2023 urban rural indicator.

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In the 2023 classification there are:

• 7 major urban areas
• 13 large urban areas
• 23 medium urban areas
• 152 small urban areas
• 402 rural settlements.

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This dataset is the definitive version of the annually released urban rural (UR) boundaries as at 1 January 2023 as defined by Stats NZ. This version contains 745 UR areas, including 195 urban areas and 402 rural settlements.

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Urban rural (UR) is an output geography that classifies New Zealand into areas that share common urban or rural characteristics and is used to disseminate a broad range of Stats NZ’s social, demographic and economic statistics.

The UR separately identifies urban areas, rural settlements, other rural areas, and water areas. Urban areas and rural settlements are form-based geographies delineated by the inspection of aerial imagery, local government land designations on district plan maps, address registers, property title data, and any other available information. However, because the underlying meshblock pattern is used to define the geographies, boundaries may not align exactly with local government land designations or what can be seen in aerial images. Other rural areas, and bodies of water represent areas not included within an urban area.

Urban areas are built from the statistical area 2 (SA2) geography, while rural and water areas are built from the statistical area 1 (SA1) geography.

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Non-digitised

The following 4 non-digitised UR areas have been aggregated from the 16 non-digitised meshblocks/SA2s.

6901; Oceanic outside region, 6902; Oceanic oil rigs, 6903; Islands outside region, 6904; Ross Dependency outside region.

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UR numbering and naming

Each urban area and rural settlement is a single geographic entity with a name and a numeric code.

Other rural areas, inland water areas, and inlets are defined by territorial authority; oceanic areas are defined by regional council; and each have a name and a numeric code.

Urban rural codes have four digits. North Island locations start with a 1, South Island codes start with a 2, oceanic codes start with a 6 and non-digitised codes start with 69.

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Urban rural indicator (IUR)

The accompanying urban rural indicator (IUR) classifies the urban, rural, and water areas by type. Urban areas are further classified by the size of their estimated resident population:

• major urban area – 100,000 or more residents,
• large urban area – 30,000–99,999 residents,
• medium urban area – 10,000–29,999 residents,
• small urban area – 1,000–9,999 residents.

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This was based on 2018 Census data and 2021 population estimates. Their IUR status (urban area size/rural settlement) may change if the 2023 Census population count moves them up or down a category.

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The indicators, by name, with their codes in brackets, are:

urban area – major urban (11), large urban (12), medium urban (13), small urban (14),

rural area – rural settlement (21), rural other (22),

water – inland water (31), inlet (32), oceanic (33).

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The urban rural indicator complements the urban rural geography and is an attribute in this dataset. Further information on the urban rural indicator is available on the Stats NZ classification and coding tool ARIA.

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For more information please refer to the Statistical standard for geographic areas 2023.

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Generalised version

This generalised version has been simplified for rapid drawing and is designed for thematic or web mapping purposes.

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Macrons

Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

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Digital data

Digital boundary data became freely available on 1 July 2007.

To download geographic classifications in table formats such as CSV please use Ariā