Definitions of “urban” and “rural” are abundant in government, academic literature, and data-driven journalism. Equally abundant are debates about what is urban or rural and which factors should be used to define these terms. Absent from most of this discussion is evidence about how people perceive or describe their neighborhood. Moreover, as several housing and demographic researchers have noted, the lack of an official or unofficial definition of suburban obscures the stylized fact that a majority of Americans live in a suburban setting. In 2017, the U.S. Department of Housing and Urban Development added a simple question to the 2017 American Housing Survey (AHS) asking respondents to describe their neighborhood as urban, suburban, or rural. This service provides a tract-level dataset illustrating the outcome of analysis techniques applied to neighborhood classification reported by the American Housing Survey (AHS) as either urban, suburban, or rural.

To create this data, analysts first applied machine learning techniques to the AHS neighborhood description question to build a model that predicts how out-of-sample households would describe their neighborhood (urban, suburban, or rural), given regional and neighborhood characteristics. Analysts then applied the model to the American Community Survey (ACS) aggregate tract-level regional and neighborhood measures, thereby creating a predicted likelihood the average household in a census tract would describe their neighborhood as urban, suburban, and rural. This last step is commonly referred to as small area estimation. The approach is an example of the use of existing federal data to create innovative new data products of substantial interest to researchers and policy makers alike.

If aggregating tract-level probabilities to larger areas, users are strongly encouraged to use occupied household counts as weights.

We recommend users read Section 7 of the working paper before using the raw probabilities. Likewise, we recognize that some users may:

prefer to use an uncontrolled classification, or

prefer to create more than three categories.

To accommodate these uses, our final tract-level output dataset includes the "raw" probability an average household would describe their neighborhood as urban, suburban, and rural. These probability values can be used to create an uncontrolled classification or additional categories.

The final classification is controlled to AHS national estimates (26.9% urban; 52.1% suburban, 21.0% rural).

  For more information about the 2017 AHS Neighborhood Description Study click on the following visit: https://www.hud.gov/program_offices/comm_planning/communitydevelopment/programs/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. 

Data Dictionary: DD_Urbanization Perceptions Small Area Index.

This dataset contains two measures designed to be used in tandem to characterize United States census tracts, originally developed for use in stratified analyses of the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network. The first measure is a 2010 tract-level community type categorization based on a modification of Rural-Urban Commuting Area (RUCA) Codes that incorporates census-designated urban areas and tract land area, with five categories: higher density urban, lower density urban, suburban/small town, rural, and undesignated (McAlexander, et al., 2022). The second measure is a neighborhood social and economic environment (NSEE) score, a community-type stratified z-score sum of 6 US census-derived variables, with sums scaled between 0 and 100, computed for the year 2000 and 2010. A tract with a higher NSEE z-score sum indicates more socioeconomic disadvantage compared to a tract with a lower z-score sum. Analysts should not compare NSEE scores across LEAD community types, as values have been computed and scaled within community type.

The Canadian Active Living Environments (Can-ALE) database is a geographic-based set of measures that represents the active living friendliness of Canadian communities. The primary envisioned use for Can-ALE is research and analysis of the relationship between the way communities are built and the physical activity levels of Canadians. Each of the measures was selected from fourteen potential measures identified by a literature review. Several considerations were weighed in deriving the Canada-wide set of measures, including: (1) the suitability of each measure across different Canadian regions and built areas (e.g., urban, suburban, rural areas); (2) the incorporation of high-quality, open and free-to-use data sources; and (3) the strength of the association between the derived measures with walking rates and active transportation (i.e., walking, cycling, and public transit use). Public transit use is included in the definition of active transportation, as public transit is shown to generate physical activity via walking to and from transit stops.The Can-ALE data were developed by Dr. Nancy Ross, Thomas Herrmann and William Gleckner, with funding from the Public Health Agency of Canada. Can-ALE measures have been developed for 2006 and 2016 census dissemination areas. Users are discouraged from performing longitudinal analyses using data from both the 2006 and 2016 datasets, as the derivation methodologies and census geographies changed between the reference years. ArcGIS was used by CANUE staff to associate the single link DMTI Spatial postal codes to the Statistics Canada dissemination areas boundary files, and then join the Access to Employment data to the postal codes, using dissemination area unique identifiers. There may be many postal codes within a single dissemination area - these will have the same index values and may not be suitable for summation, etc. Please refer to the Supporting Documentation.

The US Environmental Protection Agency's (EPA) Center for Public Health and Environmental Assessment (CPHEA) Public Health & Environmental Systems Division (PHESD) is currently engaged in research aimed at developing a measure that estimates overall environmental quality at the census tract level for the United States. This work is being conducted as an effort to learn more about how various environmental factors simultaneously contribute to health disparities in low-income and minority populations, and to better estimate the total environmental and social context to which humans are exposed. This work contains the finalized Environmental Quality Index (EQI), as a single index combining variables from each of the associated domains for the 2006-2010 census tract level EQI: air, water, land, built environment, and sociodemographic environment as well as EQI for census tract stratified by Rural Urban Continuum Code (RUCA) as determined by a reclassification based off urbancity and commuting flow initially proposed in Urban-Rural Residence and the Occurrence of Cleft Lip and Cleft Palate in Texas, 1999-2003 published in Annals of Epidemiology (Messer, et al, 2010, https://pubmed.ncbi.nlm.nih.gov/20006274/); RUCA initially was 10 classifications made by USDA Economic Research Service composed of: RUCA 1 Metropolitan Core Area, RUCA 2 Metropolitan High Commuting Area, RUCA 3 Metropolitan Low Commuting Area, RUCA 4 Micropolitan Area Core, RUCA 5, Micropolitan High Commuting, RUCA 6 Micropolitan Low Commuting Area, RUCA 7 Small Town Core, RUCA 8 Small Town High Commuting Area, RUCA 9 Small Town Low Commuting, RUCA 10 Rural Areas (https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes/). RUCA 1 remained it's own class, RUCA 2 remained it's own class, RUCA 3, 4, 5, 6 were combined and conveyed as RUCA 3, RUCA 7, 8, 9 were combined and now conveyed as RUCA 4 and RUCA 10 became RUCA 5 in the new classification. Within the new classification RUCA 1 is Urban Core, RUCA 2 is Suburban Area, RUCA 3 is Micropolitan Area, RUCA 4 is Small Town Area and RUCA 5 is Rural Area (Messer, et al, 2010). This dataset contains the finalized variables chosen to represent the overall environment within in a single Principal Component Analysis (PCA); data sources are: EPA's CMAQ: The Community Multiscale Air Quality Modeling System (http://www.https://www.epa.gov/cmaq/), the National-Scale Air Toxics Assessment (http://www.epa.gov/nata/), the U.S. Geological Survey Estimates of Water Use in the U.S. for 2010 (https://water.usgs.gov/watuse/data/2010/), the U.S. Drought Monitor Data (http://droughtmonitor.unl.edu/), “Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States” data for pesticide use (https://www.usgs.gov/data/estimated-annual-agricultural-pesticide-use-counties-conterminous-united-states-2013-17-ver-20), CropScape (https://nassgeodata.gmu.edu/CropScape), EPA Facility Registry Service (https://www.epa.gov/frs/geospatial-data-download-service), Dun and Bradstreet North American Industry Classification System (NAICS) codes(http://www.dnb.com); National Land Cover Database (NCDL) (https://www.mrlc.gov/), United States Census (http://www2.census.gov) and ESRI Crime Report (https://doc.arcgis.com/en/esri-demographics/data/crime-indexes.htm).

The County Council has identified each area of the County as urban, suburban, or rural for road code Urban Road: a road segment in or abutting a Metro Station Policy Area, Town Center Policy Area, or other urban area expressly identified in a Council resolution.Rural Road: a road segment located in a rural policy area as defined in the County Growth Policy; Suburban Road: a road segment located elsewhere in the County.For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

The County Council has identified each area of the County as urban, suburban, or rural for road code purposes:Urban Road: a road segment in or abutting a Metro Station Policy Area, Town Center Policy Area, or other urban area expressly identified in a Council resolution.Rural Road: a road segment located in a rural policy area as defined in the County Growth Policy; Suburban Road: a road segment located elsewhere in the CountyUpdates:5/16/2019: Added the urban road code boundary along Veirs Mill Rd form Havard Street to Bushy Drive per the Veirs Mill Corridor Master Plan approved by County Coucil on 4/23/2019.1/24/2018: Expanded the White Flint urban road code boundary per the adopted recomendations of the White Flint 2 Master Plan adopted by Council on 12/05/2018.8/17/2017 : Added the Lyttonsville and Woodside Purple Line Station Urban Road Code areas per the Greater Lyttonsville Sector Plan approved by County Council on 2/7/17. 8/27/2018: Added the Burtonsville, Cabin Branch, and Chevy Chase Lake Urban Road Code areas. Expanded the Kensington, Piney Branch (Flower/Arliss), Great Seneca Science Corridor, Langley Crossroads and Germantown Urban Road Code areas. Both additions and expansions were part of the Technical Update to the Master Plan of Highways and Transitways adopted by County Council on July 24, 2018.

All question modules in the standard Eurobarometer context and largely replicate questions asked in the context of Eurobarometer 80.1 [ZA5876]. Category scheme for country specific protocol variables P6 (SIZE OF COMMUNITY) has changed considerably, except for Germany. Categories for all other countries have been harmonized among each other to three values (Rural area - Towns and suburbs / small urban area - Cities / large urban areas). Category scheme for country specific protocol variables P7 (REGION) have changed for some countries, in particular introducing NUTS categories for Ireland, Estonia and Croatia. Data for protocol variables p1 (date of interview), p2 (time of interview), p3 (duration of interview), p4 (n of persons present during interview), p5 (respondent cooperation), p8 (postal code), p9 (sample point number) and p10 (interviewer number) have not been made available.

Refer to the current geographies boundaries table for a list of all current geographies and recent updates.

This dataset is the definitive version of the annually released statistical area 3 (SA3) 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 873 SA3s, excluding 4 non-digitised SA3s.

The SA3 geography aims to meet three purposes:

1. approximate suburbs in major, large, and medium urban areas,

2. in predominantly rural areas, provide geographical areas that are larger in area and population size than SA2s but smaller than territorial authorities,

3. minimise data suppression.

SA3s in major, large, and medium urban areas were created by combining SA2s to approximate suburbs as delineated in the Fire and Emergency NZ (FENZ) Localities dataset. Some of the resulting SA3s have very large populations.

Outside of major, large, and medium urban areas, SA3s generally have populations of 5,000–10,000. These SA3s may represent either a single small urban area, a combination of small urban areas and their surrounding rural SA2s, or a combination of rural SA2s.

Zero or nominal population SA3s

To minimise the amount of unsuppressed data that can be provided in multivariate statistical tables, SA2s with fewer than 1,000 residents are combined with other SA2s wherever possible to reach the 1,000 SA3 population target. However, there are still a number of SA3s with zero or nominal populations.

Small population SA2s designed to maintain alignment between territorial authority and regional council geographies are merged with other SA2s to reach the 5,000–10,000 SA3 population target. These merges mean that some SA3s do not align with regional council boundaries but are aligned to territorial authority.

Small population island SA2s are included in their adjacent land-based SA3.

Island SA2s outside territorial authority or region are the same in the SA3 geography.

Inland water SA2s are aggregated and named by territorial authority, as in the urban rural classification.

Inlet SA2s are aggregated and named by territorial authority or regional council where the water area is outside the territorial authority.

Oceanic SA2s translate directly to SA3s as they are already aggregated to regional council.

The 16 non-digitised SA2s are aggregated to the following 4 non-digitised SA3s (SA3 code; SA3 name):

70001; Oceanic outside region, 70002; Oceanic oil rigs, 70003; Islands outside region, 70004; Ross Dependency outside region.

SA3 numbering and naming

Each SA3 is a single geographic entity with a name and a numeric code. The name refers to a suburb, recognised place name, or portion of a territorial authority. In some instances where place names are the same or very similar, the SA3s are differentiated by their territorial authority, for example, Hillcrest (Hamilton City) and Hillcrest (Rotorua District).

SA3 codes have five digits. North Island SA3 codes start with a 5, South Island SA3 codes start with a 6 and non-digitised SA3 codes start with a 7. They are numbered approximately north to south within their respective territorial authorities. When first created in 2025, the last digit of each code was 0. When SA3 boundaries change in future, only the last digit of the code will change to ensure the north-south pattern is maintained.

​

Clipped Version

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

​

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.

​

Macrons

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

​

Digital data

Digital boundary data became freely available on 1 July 2007.

​

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

CENSUS_TRACTS_TIGER2011_IN.SHP is a polygon shapefile that contains 2011 census block boundaries for the state of Indiana. Census blocks are not legal boundaries, but are considered stable geographic units used for the presentation of decennial census data. The following is excerpted from an Adobe Acrobat PDF document named "TGRSHP2011_TECHDOC.PDF (U.S. Census Bureau): "Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and by non-visible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Generally, census blocks are small in area; for example, a block in a city. Census blocks in suburban and rural areas may be large, irregular, and bounded by a variety of features, such as roads, streams, and/or transmission line rights-of-way. In remote areas census blocks may encompass hundreds of square miles. Census blocks cover all territory in the United States, Puerto Rico, and the Island areas. A block may consist of one or more faces. "Blocks never cross county or census tract boundaries (See Figures 3 and 4). They do not cross the boundaries of any entity for which the Census Bureau tabulates data, including American Indian, Alaska Native, and Native Hawaiian areas, congressional districts, county subdivisions, places, state legislative districts, urbanized areas, urban clusters, school districts, voting districts, or ZIP Code Tabulation Areas (ZCTAs) or some special administrative areas such as military installations, and national parks and monuments. "Census 2010 blocks are numbered uniquely within the 2010 boundaries of each state/county/census tract with a 4-digit census block number. The first digit of the tabulation block number identifies the block group."

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 statistical area 3 (SA3) boundaries as at 1 January 2025 as defined by Stats NZ. This version contains 929 SA3s, including 4 non-digitised SA3s.

The SA3 geography aims to meet three purposes:

1. approximate suburbs in major, large, and medium urban areas,
2. in predominantly rural areas, provide geographical areas that are larger in area and population size than SA2s but smaller than territorial authorities,
3. minimise data suppression.

SA3s in major, large, and medium urban areas were created by combining SA2s to approximate suburbs as delineated in the Fire and Emergency NZ (FENZ) Localities dataset. Some of the resulting SA3s have very large populations.

Outside of major, large, and medium urban areas, SA3s generally have populations of 5,000–10,000. These SA3s may represent either a single small urban area, a combination of small urban areas and their surrounding rural SA2s, or a combination of rural SA2s.

Zero or nominal population SA3s

To minimise the amount of unsuppressed data that can be provided in multivariate statistical tables, SA2s with fewer than 1,000 residents are combined with other SA2s wherever possible to reach the 1,000 SA3 population target. However, there are still a number of SA3s with zero or nominal populations.

Small population SA2s designed to maintain alignment between territorial authority and regional council geographies are merged with other SA2s to reach the 5,000–10,000 SA3 population target. These merges mean that some SA3s do not align with regional council boundaries but are aligned to territorial authority.

Small population island SA2s are included in their adjacent land-based SA3.

Island SA2s outside territorial authority or region are the same in the SA3 geography.

Inland water SA2s are aggregated and named by territorial authority, as in the urban rural classification.

Inlet SA2s are aggregated and named by territorial authority or regional council where the water area is outside the territorial authority.

Oceanic SA2s translate directly to SA3s as they are already aggregated to regional council.

The 16 non-digitised SA2s are aggregated to the following 4 non-digitised SA3s (SA3 code; SA3 name):

70001; Oceanic outside region, 70002; Oceanic oil rigs, 70003; Islands outside region, 70004; Ross Dependency outside region.

SA3 numbering and naming

Each SA3 is a single geographic entity with a name and a numeric code. The name refers to a suburb, recognised place name, or portion of a territorial authority. In some instances where place names are the same or very similar, the SA3s are differentiated by their territorial authority, for example, Hillcrest (Hamilton City) and Hillcrest (Rotorua District).

SA3 codes have five digits. North Island SA3 codes start with a 5, South Island SA3 codes start with a 6 and non-digitised SA3 codes start with a 7. They are numbered approximately north to south within their respective territorial authorities. When first created in 2025, the last digit of each code was 0. When SA3 boundaries change in future, only the last digit of the code will change to ensure the north-south pattern is maintained.

​

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.

​

Macrons

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

​

Digital data

Digital boundary data became freely available on 1 July 2007

​

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

Statistical Area 2 2023 update

SA2 2023 is the first major update of the geography since it was first created in 2018. The update is to ensure SA2s are relevant and meet criteria before each five-yearly population and dwelling census. SA2 2023 contains 135 new SA2s. Updates were made to reflect real world change of population and dwelling growth mainly in urban areas, and to make some improvements to their delineation of communities of interest.

​

Description

This dataset is the definitive version of the annually released statistical area 2 (SA2) boundaries as at 1 January 2023 as defined by Stats NZ. This version contains 2,395 SA2s (2,379 digitised and 16 with empty or null geometries (non-digitised)).

​

SA2 is an output geography that provides higher aggregations of population data than can be provided at the statistical area 1 (SA1) level. The SA2 geography aims to reflect communities that interact together socially and economically. In populated areas, SA2s generally contain similar sized populations.

​

The SA2 should:

form a contiguous cluster of one or more SA1s,

excluding exceptions below, allow the release of multivariate statistics with minimal data suppression,

capture a similar type of area, such as a high-density urban area, farmland, wilderness area, and water area,

be socially homogeneous and capture a community of interest. It may have, for example:

​

• a shared road network,
• shared community facilities,
• shared historical or social links, or
• socio-economic similarity,

​

form a nested hierarchy with statistical output geographies and administrative boundaries. It must:

​

• be built from SA1s,
• either define or aggregate to define SA3s, urban areas, territorial authorities, and regional councils.

​

SA2s in city council areas generally have a population of 2,000–4,000 residents while SA2s in district council areas generally have a population of 1,000–3,000 residents.

​

In major urban areas, an SA2 or a group of SA2s often approximates a single suburb. In rural areas, rural settlements are included in their respective SA2 with the surrounding rural area.

​

SA2s in urban areas where there is significant business and industrial activity, for example ports, airports, industrial, commercial, and retail areas, often have fewer than 1,000 residents. These SA2s are useful for analysing business demographics, labour markets, and commuting patterns.

​

In rural areas, some SA2s have fewer than 1,000 residents because they are in conservation areas or contain sparse populations that cover a large area.

​

To minimise suppression of population data, small islands with zero or low populations close to the mainland, and marinas are generally included in their adjacent land-based SA2.

​

Zero or nominal population SA2s

To ensure that the SA2 geography covers all of New Zealand and aligns with New Zealand’s topography and local government boundaries, some SA2s have zero or nominal populations. These include:

​

• SA2s where territorial authority boundaries straddle regional council boundaries. These SA2s each have fewer than 200 residents and are: Arahiwi, Tiroa, Rangataiki, Kaimanawa, Taharua, Te More, Ngamatea, Whangamomona, and Mara.
• SA2s created for single islands or groups of islands that are some distance from the mainland or to separate large unpopulated islands from urban areas
• SA2s that represent inland water, inlets or oceanic areas including: inland lakes larger than 50 square kilometres, harbours larger than 40 square kilometres, major ports, other non-contiguous inlets and harbours defined by territorial authority, and contiguous oceanic areas defined by regional council.
• SA2s for non-digitised oceanic areas, offshore oil rigs, islands, and the Ross Dependency. Each SA2 is represented by a single meshblock. The following 16 SA2s are held in non-digitised form (SA2 code; SA2 name):

400001; New Zealand Economic Zone, 400002; Oceanic Kermadec Islands, 400003; Kermadec Islands, 400004; Oceanic Oil Rig Taranaki, 400005; Oceanic Campbell Island, 400006; Campbell Island, 400007; Oceanic Oil Rig Southland, 400008; Oceanic Auckland Islands, 400009; Auckland Islands, 400010 ; Oceanic Bounty Islands, 400011; Bounty Islands, 400012; Oceanic Snares Islands, 400013; Snares Islands, 400014; Oceanic Antipodes Islands, 400015; Antipodes Islands, 400016; Ross Dependency.

​

SA2 numbering and naming

Each SA2 is a single geographic entity with a name and a numeric code. The name refers to a geographic feature or a recognised place name or suburb. In some instances where place names are the same or very similar, the SA2s are differentiated by their territorial authority name, for example, Gladstone (Carterton District) and Gladstone (Invercargill City).

​

SA2 codes have six digits. North Island SA2 codes start with a 1 or 2, South Island SA2 codes start with a 3 and non-digitised SA2 codes start with a 4. They are numbered approximately north to south within their respective territorial authorities. To ensure the north–south code pattern is maintained, the SA2 codes were given 00 for the last two digits when the geography was created in 2018. When SA2 names or boundaries change only the last two digits of the code will change.

​

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

​

Generalised version

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

​

Macrons

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

​

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

Statistical area 3 (SA3) is a new output geography, introduced in 2023, that allows aggregations of population data between the SA2 geography and territorial authority geography.

​

This dataset is the definitive version of the annually released statistical area 3 (SA3) boundaries as at 1 January 2023 as defined by Stats NZ. This version contains 929 SA3s, including 4 non-digitised SA3s.

​

The SA3 geography aims to meet three purposes:

1. approximate suburbs in major, large, and medium urban areas,

2. in predominantly rural areas, provide geographical areas that are larger in area and population size than SA2s but smaller than territorial authorities,

3. minimise data suppression.

​

SA3s in major, large, and medium urban areas were created by combining SA2s to approximate suburbs as delineated in the Fire and Emergency NZ (FENZ) Localities dataset. Some of the resulting SA3s have very large populations.

​

Outside of major, large, and medium urban areas, SA3s generally have populations of 5,000–10,000. These SA3s may represent either a single small urban area, a combination of small urban areas and their surrounding rural SA2s, or a combination of rural SA2s.

​

Zero or nominal population SA3s

To minimise the amount of unsuppressed data that can be provided in multivariate statistical tables, SA2s with fewer than 1,000 residents are combined with other SA2s wherever possible to reach the 1,000 SA3 population target. However, there are still a number of SA3s with zero or nominal populations.

​

Small population SA2s designed to maintain alignment between territorial authority and regional council geographies are merged with other SA2s to reach the 5,000–10,000 SA3 population target. These merges mean that some SA3s do not align with regional council boundaries but are aligned to territorial authority.

​

Small population island SA2s are included in their adjacent land-based SA3.

​

Island SA2s outside territorial authority or region are the same in the SA3 geography.

​

Inland water SA2s are aggregated and named by territorial authority, as in the urban rural classification.

​

Inlet SA2s are aggregated and named by territorial authority or regional council where the water area is outside the territorial authority.

​

Oceanic SA2s translate directly to SA3s as they are already aggregated to regional council.

​

The 16 non-digitised SA2s are aggregated to the following 4 non-digitised SA3s (SA3 code; SA3 name):

70001; Oceanic outside region, 70002; Oceanic oil rigs, 70003; Islands outside region, 70004; Ross Dependency outside region.

​

SA3 numbering and naming

Each SA3 is a single geographic entity with a name and a numeric code. The name refers to a suburb,recognised place name, or portion of a territorial authority. In some instances where place names are the same or very similar, the SA3s are differentiated by their territorial authority, for example, Hillcrest (Hamilton City) and Hillcrest (Rotorua District).

​

SA3 codes have five digits. North Island SA3 codes start with a 5, South Island SA3 codes start with a 6 and non-digitised SA3 codes start with a 7. They are numbered approximately north to south within their respective territorial authorities. When first created in 2023, the last digit of each code was 0. When SA3 boundaries change in future, only the last digit of the code will change to ensure the north-south pattern is maintained.

​

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

​

Generalised version

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

​

Macrons

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

​

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

A Certificate of Necessity (“CON”) is required to operate a ground ambulance and transport patients in Arizona. The Arizona Department of Health Services (“ADHS”) regulates the operating and response times of ambulance services to meet the needs of the public and ensure adequate service, pursuant to Arizona Revised Statute (“A.R.S.”) § 36-2232. Under A.R.S. § 36-2232(A)(3), response times shall follow uniform standard definitions for urban, suburban, rural, and wilderness geographic areas within a CON. Under Arizona Administrative Code (“A.A.C.”) R9-25-901, “Scene locality” is defined as an urban, suburban, rural, or wilderness area. Scene locality is sometimes also referred to as “urbanicity”. The current scene locality / urbanicity maps were developed based on the 2020 Census urban areas and block groups, to geographically represent areas within a CON defined under A.A.C. R9-25-901 as the following:“Urban area” means a geographic region delineated as an urbanized area by the United States Department of Commerce, Bureau of the Census. “Suburban area” means a geographic region within a 10-mile radius of an urban area that has a population density equal to or greater than 1,000 residents per square mile.“Rural area” means a geographic region with a population of less than 40,000 residents that is not a suburban area. “Wilderness area” means a geographic region that has a population density of less than one resident per square mile.Additional Information:The 2010 definition for urbanized areas is applied, as the 2020 Census doesn't delineate urban into two categories.Updates occur as needed based on the most recent decennial census, adhering to Administrative Statute and Code.Regulatory authority and definitions for scene localities can be found in the Statute and Rule Book, under A.R.S. § 36-2232 and A.A.C. R9-25-901.For more information about the Certificates of Necessity program, please visit the ADHS Ground Ambulance Program website or call (602) 364-3150.Last Updated: Update Frequency: As Needed; requires Administrative Code change