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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.
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The urban–rural continuum classifies the global population, allocating rural populations around differently-sized cities. The classification is based on four dimensions: population distribution, population density, urban center location, and travel time to urban centers, all of which can be mapped globally and consistently and then aggregated as administrative unit statistics.Using spatial data, we matched all rural locations to their urban center of reference based on the time needed to reach these urban centers. A hierarchy of urban centers by population size (largest to smallest) is used to determine which center is the point of “reference” for a given rural location: proximity to a larger center “dominates” over a smaller one in the same travel time category. This was done for 7 urban categories and then aggregated, for presentation purposes, into “large cities” (over 1 million people), “intermediate cities” (250,000 –1 million), and “small cities and towns” (20,000–250,000).Finally, to reflect the diversity of population density across the urban–rural continuum, we distinguished between high-density rural areas with over 1,500 inhabitants per km2 and lower density areas. Unlike traditional functional area approaches, our approach does not define urban catchment areas by using thresholds, such as proportion of people commuting; instead, these emerge endogenously from our urban hierarchy and by calculating the shortest travel time.Urban-Rural Catchment Areas (URCA).tif is a raster dataset of the 30 urban–rural continuum categories for the urban–rural continuum showing the catchment areas around cities and towns of different sizes. Each rural pixel is assigned to one defined travel time category: less than one hour, one to two hours, and two to three hours travel time to one of seven urban agglomeration sizes. The agglomerations range from large cities with i) populations greater than 5 million and ii) between 1 to 5 million; intermediate cities with iii) 500,000 to 1 million and iv) 250,000 to 500,000 inhabitants; small cities with populations v) between 100,000 and 250,000 and vi) between 50,000 and 100,000; and vii) towns of between 20,000 and 50,000 people. The remaining pixels that are more than 3 hours away from any urban agglomeration of at least 20,000 people are considered as either hinterland or dispersed towns being that they are not gravitating around any urban agglomeration. The raster also allows for visualizing a simplified continuum created by grouping the seven urban agglomerations into 4 categories.Urban-Rural Catchment Areas (URCA).tif is in GeoTIFF format, band interleaved with LZW compression, suitable for use in Geographic Information Systems and statistical packages. The data type is byte, with pixel values ranging from 1 to 30. The no data value is 128. It has a spatial resolution of 30 arc seconds, which is approximately 1km at the equator. The spatial reference system (projection) is EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long). The geographic extent is 83.6N - 60S / 180E - 180W. The same tif file is also available as an ESRI ArcMap MapPackage Urban-Rural Catchment Areas.mpkFurther details are in the ReadMe_data_description.docx
The global urban population overtook the rural population in numbers in 2007. As of 2023, 4.61 billion people live in urban areas, compared to 3.45 million in rural areas. This development underlines that rapid urbanization the world has seen in recent decades.
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.
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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 urban rural (UR) boundaries as at 1 January 2025 as defined by Stats NZ. 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:
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:
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).
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
2007 marked the first year where more of the world's population lived in an urban setting than a rural setting. In 1960, roughly a third of the world lived in an urban setting; it is expected that this figure will reach two thirds by 2050. Urbanization is a fairly new phenomenon; for the vast majority of human history, fewer than five percent of the world lived in urban areas, due to the dependency on subsistence agriculture. Advancements in agricultural practices and technology then coincided with the beginning of the industrial revolution in Europe in the late 19th century, which resulted in waves of urbanization to meet the demands of emerging manufacturing industries. This trend was replicated across the rest of the world as it industrialized over the following two centuries, and the most significant increase coincided with the industrialization of the most populous countries in Asia. In more developed economies, urbanization remains high even as economies de-industrialize, due to a variety of factors such as housing availability, labor demands in service industries, and social trends.
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.
This map's colors indicate which population is larger in each area: urban (green) or rural (yellow). The map's layers contain total population counts by sex, age, and race groups for Nation, State Legislative Districts Upper, State Legislative Districts Lower, Congressional District in the United States and Puerto Rico.The U.S. Census designates each census block as part of an urban area or as rural. Larger geographies in this map such as block group, tract, county and state can therefore have a mix of urban and rural population. This map illustrates the 100% urban areas in dark green, and 100% rural areas in dark yellow. Areas with mixed urban/rural population have softer shades of green or yellow, to give a visual indication of where change may be happening. From the Census:"The Census Bureau’s urban-rural classification is a delineation of geographic areas, identifying both individual urban areas and the rural area of the nation. The Census Bureau’s urban areas represent densely developed territory, and encompass residential, commercial, and other non-residential urban land uses. The Census Bureau delineates urban areas after each decennial census by applying specified criteria to decennial census and other data. Rural encompasses all population, housing, and territory not included within an urban area.For the 2020 Census, an urban area will comprise a densely settled core of census blocks that meet minimum housing unit density and/or population density requirements. This includes adjacent territory containing non-residential urban land uses. To qualify as an urban area, the territory identified according to criteria must encompass at least 2,000 housing units or have a population of at least 5,000." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters). The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Land and Geographic Unit Area Grids measure land areas in square kilometers and the mean Unit size (population-weighted) in square kilometers. The land area grid permits the summation of areas (net of permanent ice and water) at the same resolution as the population density, count, and urban-rural grids. The mean Unit size grids provide a quantitative surface that indicates the size of the input Unit(s) from which population count and density grids are derived. Additional global grids are created from the 30 arc-second grid at 1/4, 1/2, and 1 degree resolutions. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
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 Census Bureau’s urban-rural classification is fundamentally a delineation of geographical areas, identifying both individual urban areas and the rural areas of the nation. The Census Bureau’s urban areas represent densely developed territory, and encompass residential, commercial, and other non-residential urban land uses. To qualify as an urban area, the territory identified according to criteria must have at least 5,000 people or 2,000 housing units. The 2020 Census changed how urban areas are determined from the 2010 criteria. The population requirement was increased to 5,000 people from 2,500 in 2010. This value is now determined by housing unit density instead of population density. Urban areas can now also be defined by the number of housing units present. Finally, the 2020 Census does not distinguish different types of urban areas. Areas are simply urban or rural.This layer was originally downloaded from the US Census Bureau website and clipped to the Stark County boundary. For more information on urban and rural classification and criteria, visit Redefining Urban Areas following the 2020 Census.
In 2023, there were approximately ***** million people living in rural areas in the United States, while about ****** million people were living in urban areas. Within the provided time period, the number of people living in urban U.S. areas has increased significantly since totaling only ****** million in 1960.
CLICK ON THE ABOVE IMAGE TO LAUNCH THE MAP - Healthcare access issues vary greatly between urban and rural areas of New Mexico. Launch the map to explore alternate ways to classify geographies as urban or rural. These classifications are often used for food access as well as healthcare access.BIBLIOGRAPHY WITH LINKS:US Census Bureau, Urban Area - Urban Cluster FAQ - https://www2.census.gov/geo/pdfs/reference/ua/2010ua_faqs.pdfAre the problems with Rural areas actually just a result of definitions that change?: "When a rural county grows, it transmutes into an urban one." - The real (surprisingly comforting) reason rural America is doomed to decline, https://www.washingtonpost.com/business/2019/05/24/real-surprisingly-comforting-reason-rural-america-is-doomed-decline/ (See also the complete study - http://programme.exordo.com/2018annualmeeting/delegates/presentation/130/ )Rural Definitions for Health Policy, Harvey Licht, a presentation for the University of New Mexico Center for Health Policy: : http://nmcdc.maps.arcgis.com/home/item.html?id=7076f283b8de4bb69bf3153bc42e0402Rural Definitions for Health Policy, update of 2019, Harvey Licht, a presentation to the NMDOH Quarterly Epidemiology Meeting, November, 2019 - http://www.arcgis.com/home/item.html?id=a60a73f4e5614eb3ab01e2f96227ce4bNew Mexico Rural-Urban Counties Comparison Tables - October 2017, Harvey Licht, A preliminary compilation for the National Conference of State Legislators Rural Health Plan Taskforce : https://nmcdc.maps.arcgis.com/home/item.html?id=d3ca56e99f8b45c58522b2f9e061999eNew Mexico Rural Health Plan - Report of the Rural Health Planning Workgroup convened by the NM Department of Health 2018-2019 - http://nmcdc.maps.arcgis.com/home/item.html?id=d4b9b66a5ca34ec9bbe90efd9562586aFrontier and Remote Areas Zip Code Map - http://nmcdc.maps.arcgis.com/home/webmap/viewer.html?webmap=56b4005256244499a58f863c17bbac8aHOUSING ISSUES, RURAL & URBAN, 2017 - http://nmcdc.maps.arcgis.com/home/webmap/viewer.html?webmap=3e3aeabc04ac4672994e25a1ec94df83FURTHER READING:What is Rural? Rural Health Information Hub: https://www.ruralhealthinfo.org/topics/what-is-ruralDefining Rural. Research and Training Center on Disability in Rural Communities: http://rtc.ruralinstitute.umt.edu/resources/defining-rural/What is Rural? USDA: https://www.ers.usda.gov/topics/rural-economy-population/rural-classifications/what-is-rural/National Center for Health Statistics Urban–Rural Classification Scheme: https://www.cdc.gov/nchs/data_access/urban_rural.htm.Health-Related Behaviors by Urban-Rural County Classification — United States, 2013, CDC: https://www.cdc.gov/mmwr/volumes/66/ss/ss6605a1.htm?s_cid=ss6605a1_wExtending Work on Rural Health Disparities, The Journal of Rural Health: http://onlinelibrary.wiley.com/doi/10.1111/jrh.12241/fullMinority Populations Driving Community Growth in the Rural West, Headwaters Economics: https://headwaterseconomics.org/economic-development/trends-performance/minority-populations-driving-county-growth/ Methodology - https://headwaterseconomics.org/wp-content/uploads/Minorities_Methods.pdfThe Role of Medicaid in Rural America, Kaiser Family Foundation: http://www.kff.org/medicaid/issue-brief/the-role-of-medicaid-in-rural-america/The Future of the Frontier: Water, Energy & Climate Change in America’s Most Remote Communities: http://frontierus.org/wp-content/uploads/2017/09/FUTURE-OF-THE-FRONTIER_Final-Version_Spring-2017.pdfRural and Urban Differences in Passenger-Vehicle–Occupant Deaths and Seat Belt Use Among Adults — United States, 2014, CDC: https://www.cdc.gov/mmwr/volumes/66/ss/ss6617a1.htm
https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/
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.
In the 2023 classification there are:
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.
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.
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:
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.
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).
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.
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
Rural lands are those areas outside of urban growth areas (UGAs). As the Growth Management Act (GMA) requires a “Rural Element” that includes lands “not designated for urban growth, agriculture, forest, or mineral resources” (RCW 36.70A.070(5)). The GMA requires the county to include a rural element in its comprehensive plan. The county’s rural element consists of the rural land use policies in this subsection of the Land Use chapter as well as other rural-related policies addressing utilities, transportation, housing, open space, parks and recreation, economic development, and natural resources, each discussed in separate sections of the county’s comprehensive plan.
In 2024, about 943.5 million people lived in urban regions in China and 464.8 million in rural. That year, the country had a total population of approximately 1.41 billion people. As of 2024, China was the second most populous country in the world. Urbanization in China Urbanization refers to the process by which people move from rural to urban areas and how a society adapts to the population shift. It is usually seen as a driving force in economic growth, accompanied by industrialization, modernization and the spread of education. Urbanization levels tend to be higher in industrial countries, whereas the degree of urbanization in developing countries remains relatively low. According to World Bank, a mere 19.4 percent of the Chinese population had been living in urban areas in 1980. Since then, China’s urban population has skyrocketed. By 2024, about 67 percent of the Chinese population lived in urban areas. Regional urbanization rates In the last decades, urbanization has progressed greatly in every region of China. Even in most of the more remote Chinese provinces, the urbanization rate surpassed 50 percent in recent years. However, the most urbanized areas are still to be found in the coastal eastern and southern regions of China. The population of Shanghai, the largest city in China and the world’s seventh largest city ranged at around 24 million people in 2023. China’s urban areas are characterized by a developing middle class. Per capita disposable income of Chinese urban households has more than doubled between 2010 and 2020. The emerging middle class is expected to become a significant driver for the continuing growth of the Chinese economy.
As of 2024, an estimated ** percent of Europeans living in rural areas accessed the internet, compared to ** percent of the Commonwealth of Independent States (CIS) rural population. The lowest internet usage reach was in rural areas in Africa, at ** percent. Overall, urban areas presented a higher percentage of internet penetration.
The Department of Veterans Affairs provides official estimates and projections of the Veteran population using the Veteran Population Projection Model (VetPop). Based on the latest model VetPop2023 and the most recent national survey estimates from the 2023 American Community Survey 1-Year (ACS) data, the projected number of Veterans living in the 50 states, DC and Puerto Rico for fiscal years, 2023 to 2025, are allocated to Urban and Rural areas. As defined by the Census Bureau, Rural encompasses all population, housing, and territory not included within an Urban area (https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html). This table contains the Veteran estimates by urban/rural, sex, age group, and race. Note: rounding to the nearest 1,000 is always appropriate for VetPop estimates.
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file provides a rural-urban view of 2001 Lower Layer Super Output Areas (LSOA) in England and Wales. The ZIP file contains the Rural Urban Classification in XLSX and CSV format and includes a user guide. The files were originally from the NeSS website. Click on the Download button to download the ZIP file.The classification of rural and urban areas is the outcome of a project co-sponsored by:Office for National Statistics (ONS);Department for Environment, Food and Rural Affairs (Defra);Office of the Deputy Prime Minister (now Communities and Local Government);Countryside Agency (CA); andNational Assembly for Wales (NAW).The classification was developed in 2004 by a consortium co-ordinated by Prof. John Shepherd from Birkbeck College. The technical work was lead by Peter Bibby of University of Sheffield and the project also involved the University of Glamorgan and Geowise. The rural and urban classification of Output Areas, Super Output Areas (this dataset) and Wards has been provided to enable datasets to be analysed according to the classification. This provides a powerful tool for the development and monitoring of rural and urban policies.Please Note: Super Output Areas do not have all the same codes as the OA level Dataset. For SOAs and Wards the classifications for ‘Villages, Hamlets and Isolated Dwellings’ have been combined.Similar procedures to those used to classify Output Areas apply to the classification for the 34,378 Lower Layer Super Output Areas in the dataset. However the morphological classification differs in the number of categories as very few LSOAs can be classified as predominantly dispersed settlements. LSOAs are categorised into just three domains: urban 10k, town and fringe and villages, hamlets and isolated dwellings, using the key below:2005 Rural and Urban morphology indicator1 - denotes predominantly urban >10k2 - denotes predominantly town and fringe3 - denotes other rural (including village, hamlet and isolated dwellings)2005 Rural and Urban context indicator0 - denotes less sparsely populated areas1 - denotes sparsely populated areas
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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
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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.