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.
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Note: Updates to this data product are discontinued. Dozens of definitions are currently used by Federal and State agencies, researchers, and policymakers. The ERS Rural Definitions data product allows users to make comparisons among nine representative rural definitions.
Methods of designating the urban periphery range from the use of municipal boundaries to definitions based on counties. Definitions based on municipal boundaries may classify as rural much of what would typically be considered suburban. Definitions that delineate the urban periphery based on counties may include extensive segments of a county that many would consider rural.
We have selected a representative set of nine alternative rural definitions and compare social and economic indicators from the 2000 decennial census across the nine definitions. We chose socioeconomic indicators (population, education, poverty, etc.) that are commonly used to highlight differences between urban and rural areas.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 State-Level Maps For complete information, please visit https://data.gov.
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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
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.
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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. 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
Rural Urban Classification
The 2021 RUC is a statistical classification to provide a consistent and standardised method for classifying geographies as rural or urban. This is based on address density, physical settlement form, population size, and Relative Access to Major towns and cities (populations of over 75,000 people). The classification is produced by the Office for National Statistics (ONS) with advice from the Department for Environment, Food and Rural Affairs (Defra), the Welsh Government and colleagues from the Government Geography Profession (GGP).
This is 2021 rural-urban classification (RUC) of 2024 Local Authority Districts in England and Wales. This means that the 2021 RUC methodology has been applied to the 2024 LAD boundaries. LAD classifications are divided into four categories based on their populations:
1. Majority Rural: had at least 50% of their population residing in Rural OAs
2. Intermediate Rural: 35-50% rural population
3. Intermediate Urban: 20-35% rural population
4. Urban: 20% or less of the population lived in rural OAs.
Each 2024 LAD category is split into one of two Relative Access categories, using the same data as the 2021 Output Area RUC. If more than 50% of a LAD population lives in ‘Nearer a major town or city’ OAs, it is deemed ‘nearer a major town or city’; otherwise, it is classified as ‘further from a major town or city’.
Where data is unavailable for Super Output Area geographies, it may be appropriate for users to undertake analysis at the LAD level. At this level, the categorisation works slightly differently in that most areas will include a mix of both rural and urban areas - so the LA RUC categorisation is a reflection of this. A statistical geography may contain substantial portions of open countryside but still be given an ‘Urban’ classification if the majority of the population within the area live in settlements that are urban in nature. Users should take this into consideration to ensure correct interpretations of any analysis of RUC LAD categories.
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.
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The Scottish Government (SG) Urban Rural Classification provides a consistent way of defining urban and rural areas across Scotland. The classification aids policy development and the understanding of issues facing urban, rural and remote communities. It is based upon two main criteria: (i) population as defined by National Records of Scotland (NRS), and (ii) accessibility based on drive time analysis to differentiate between accessible and remote areas in Scotland. The classification can be analysed in a two, three, six or eight fold form. The two-fold classification simply distinguishes between urban and rural areas through two categories, urban and rural, while the three-fold classification splits the rural category between accessible and remote. Most commonly used is the 6-fold classification which distinguishes between urban, rural, and remote areas through six categories. The 8-fold classification further distinguishes between remote and very remote regions. The Classification is normally updated on a biennial basis, with the current dataset reflective of the year 2020. Data for previous versions are available for download in ESRI Shapefile format.
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Dozens of definitions are currently used by Federal and State agencies, researchers, and policymakers. The ERS Rural Definitions data product allows users to make comparisons among nine representative rural definitions.
Methods of designating the urban periphery range from the use of municipal boundaries to definitions based on counties. Definitions based on municipal boundaries may classify as rural much of what would typically be considered suburban. Definitions that delineate the urban periphery based on counties may include extensive segments of a county that many would consider rural.
We have selected a representative set of nine alternative rural definitions and compare social and economic indicators from the 2000 decennial census across the nine definitions. We chose socioeconomic indicators (population, education, poverty, etc.) that are commonly used to highlight differences between urban and rural areas.
FHFA's Duty to Serve regulation defines "rural area" as: (i) A census tract outside of an MSA as designated by the Office of Management and Budget (OMB); or (ii) A census tract in an MSA as designated by OMB that is: (A) Outside of the MSA’s Urbanized Areas as designated by the U.S. Department of Agriculture’s (USDA) Rural-Urban Commuting Area (RUCA) Code #1, and outside of tracts with a housing density of over 64 housing units per square mile for USDA’s RUCA Code #2; or (B) A colonia census tract that does not satisfy paragraphs (i) or (ii)(A) of this definition. This data contains both the specific geographies which meet the Rural Areas definition and also the areas defined as “high-needs rural regions”.
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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:
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).
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
The Rural Definition was introduced in 2004 as a joint project between the Commission for Rural Communities (CRC - formerly the Countryside Agency), the Department for Environment, Food and Rural Affairs (Defra), the Office for National Statistics (ONS), the Office of the Deputy Prime Minister (ODPM) and the Welsh Assembly. It was delivered by the Rural Evidence Research Centre at Birkbeck College (RERC).A) This new 'spectrum', or graded system, replaces the earlier Oxford/CA binary ward classification and adopts a settlement-based approach.B) It is available for England and Wales at:Census Output Area (COA or OA)Census Super Output Area (CSOA or SOA)Ward[OAs consist of ~125 households and have a population of ~300. SOAs are built of OAs, typically 5, and so contain ~625 households or a mean population of ~1500. OAs therefore vary greatly in size and shape between urban and rural regions, for example a single tower block may consist of more than one OA, whereas a large area of remote moorland may be covered by a single OA.] More information on OAs and SOAs.C) Output areas are classified by morphology and context:MorphologyUrban (over 10,000)Rural townVillageDispersed (hamlets and isolated dwellings)And contextSparseLess sparseThis gives 8 Urban/Rural Classification (1 urban and 6 rural):Urban (Sparse)Urban (Less Sparse)Town (Less Sparse)Town (Sparse)Village (Less Sparse)Village (Sparse)Dispersed (Less Sparse)Dispersed (Sparse)In April 2009 significant changes in the structure of local government came into force. These changes, especially the creation of 9 new unitary authorities, have necessitated an update to the Local Authority Classification. The Government Statistical Service Regional and Geography Group (GSSRG) commissioned a working group to look at this issue, and the outcome of this working group is a revised LA Classification. Detailed information about the changes can be found here, with guidance on how to use the Definition and Classification here.
The regional definition of the rural vs urban character of the municipalities was recorded in 2016.A municipality is considered rural if it has less than 10000 inhabitants and is located outside the metropolis of Greater Paris.
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Time series data for the statistic Rural population and country Greenland. Indicator Definition:Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.The indicator "Rural population" stands at 6.74 Thousand as of 12/31/2024, the lowest value at least since 12/31/1961, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -1.78 percent compared to the value the year prior.The 1 year change in percent is -1.78.The 3 year change in percent is -4.83.The 5 year change in percent is -7.47.The 10 year change in percent is -15.66.The Serie's long term average value is 10.69 Thousand. It's latest available value, on 12/31/2024, is 36.96 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2024, to it's latest available value, on 12/31/2024, is +0.0%.The Serie's change in percent from it's maximum value, on 12/31/1961, to it's latest available value, on 12/31/2024, is -50.27%.
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Here we used remote sensing data from multiple sources (time-series of Landsat and Sentinel images) to map the impervious surface area (ISA) at five-year intervals from 1990 to 2015, and then converted the results into a standardized dataset of the built-up area for 433 Chinese cities with 300,000 inhabitants or more, which were listed in the United Nations (UN) World Urbanization Prospects (WUP) database (including Mainland China, Hong Kong, Macao and Taiwan). We employed a range of spectral indices to generate the 1990–2015 ISA maps in urban areas based on remotely sensed data acquired from multiple sources. In this process, various types of auxiliary data were used to create the desired products for urban areas through manual segmentation of peri-urban and rural areas together with reference to several freely available products of urban extent derived from ISA data using automated urban–rural segmentation methods. After that, following the well-established rules adopted by the UN, we carried out the conversion to the standardized built-up area products from the 1990–2015 ISA maps in urban areas, which conformed to the definition of urban agglomeration area (UAA). Finally, we implemented data postprocessing to guarantee the spatial accuracy and temporal consistency of the final product.The standardized urban built-up area dataset (SUBAD–China) introduced here is the first product using the same definition of UAA adopted by the WUP database for 433 county and higher-level cities in China. The comparisons made with contemporary data produced by the National Bureau of Statistics of China, the World Bank and UN-habitat indicate that our results have a high spatial accuracy and good temporal consistency and thus can be used to characterize the process of urban expansion in China.The SUBAD–China contains 2,598 vector files in shapefile format containing data for all China's cities listed in the WUP database that have different urban sizes and income levels with populations over 300,000. Attached with it, we also provided the distribution of validation points for the 1990–2010 ISA products of these 433 Chinese cities in shapefile format and the confusion matrices between classified data and reference data during different time periods as a Microsoft Excel Open XML Spreadsheet (XLSX) file.Furthermore, The standardized built-up area products for such cities will be consistently updated and refined to ensure the quality of their spatiotemporal coverage and accuracy. The production of this dataset together with the usage of population counts derived from the WUP database will close some of the data gaps in the calculation of SDG11.3.1 and benefit other downstream applications relevant to a combined analysis of the spatial and socio-economic domains in urban areas.
Census tracts are designated as urban, rural center, or rural through SB 1000 analysis. These designations are being used for the REV 2.0 and Community Charging in Urban Areas GFOs. Rural centers are contiguous urban census tracts with a population of less than 50,0000. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Rural communities are census tracts where less than 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Urban communities are contiguous urban census tracts with a population of 50,000 or greater. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria.Data Dictionary:OBJECTID: Unique IDSTATEFP: State FIPS CodeCOUNTYFP: County FIPS CodeTRACTCE: Census Tract IDGEOID: Geographic IdentifierName: Census Tract ID Name (short)NAMELSAD: Census Tract ID Name (long)ALAND: Land Area (square meters)AWATER: Water Area (square meters)DAC: Whether or not a census tract is a disadvantaged community as defined by SB 535 and designated by CalEPA using CalEnviroScreen 4.0 (May 2022 update)Income_Group: Whether or not a census tract is low-, middle-, or high-income as defined by AB 1550 and designated by CARB and the CEC (June 2023 update)Urban_Rural_RuralCenter: Whether or not a census tract is urban, rural, or rural center as defined and designated by the CEC through the SB 1000 Assessment (2024 update)PerCap_100k_L2DCFC: Number of public Level 2 and DC fast chargers per 100,000 people in a census tractDAC_andor_LIC: Whether or not a census tract is a disadvantaged or low-income community as defined by SB 535 and AB 1550 and designated by CalEPA and CARBUCC_eligible: Whether or not the census tract is an eligible area for the Community Charging in Urban Areas GFO. For a site to be eligible, it must be in a census tract that is either a disadvantaged or low-income community, and urban, and has below the state average for per capita public Level 2 and DC fast chargers as defined by the CEC.REV2_eligible: Whether or not the census tract is an eligible area for the Rural Electric Vehicle Charging 2.0 GFO. For a site to be eligible, it must be in a rural or rural center census tract as defined by the CEC.Shape_Area: Census tract shape area (square meters)Shape_Length: Census tract shape length (square meters)
This service provides a tract-level dataset illustrating the outcome of machine learning techniques applied to neighborhood classification reported by the American Housing Survey (AHS) as either urban, suburban, or rural. 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.
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Time series data for the statistic Rural population and country Burundi. Indicator Definition:Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.The indicator "Rural population" stands at 11.92 Million as of 12/31/2024, the highest value at least since 12/31/1961, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 2.16 percent compared to the value the year prior.The 1 year change in percent is 2.16.The 3 year change in percent is 6.96.The 5 year change in percent is 12.25.The 10 year change in percent is 25.09.The Serie's long term average value is 6.00 Million. It's latest available value, on 12/31/2024, is 98.79 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1960, to it's latest available value, on 12/31/2024, is +340.30%.The Serie's change in percent from it's maximum value, on 12/31/2024, to it's latest available value, on 12/31/2024, is 0.0%.
BackgroundStudies from high income countries (HIC) have generally shown higher osteoporotic fracture rates in urban areas than rural areas. Low bone mineral density (BMD) increases susceptibility to fractures. This review aimed to assess whether urbanicity is consistently associated with lower BMD globally.MethodOvid MEDLINE, EMBASE, and Global Health (-April 2013) were searched for articles investigating differences in bone mineral content (BMC) or BMD between urban and rural areas. Ratio of means (RoM) of BMD were used to estimate effect sizes in meta-analysis, with an exception for one study that only presented BMC data.ResultsFifteen articles from eleven distinct populations were included in the review; seven populations from four high income countries and four from three low and middle income countries (LMIC). Meta-analysis showed conflicting evidence for urban-rural difference in BMD; studies from high income countries generally showed higher BMD in rural areas while the results were more mixed in studies from low and middle income countries (HIC RoM = 0.05; 95% CI: 0.03 to 0.06; LMIC RoM = -0.04: 95% CI: -0.1 to 0.01).ConclusionsUrban-rural differences of bone mineral density may be context-specific. BMD may be higher in urban areas in some lower income countries. More studies with robust designs and analytical techniques are needed to understand mechanisms underlying the effects of urbanization on bone mass accrual and loss.
The project aimed to thoroughly examine the rural geographies of gentrification in France, the UK, and the USA through a comparative study of its theory, forms, and dynamics. It sought to determine whether rural gentrification could be used as a concept to explain changes in rural areas in these countries. he project began by using the concept of "sociologies of translation" to understand how the term "rural gentrification" was used in academic, policy, and popular discourses in the past and present in these countries. To identify the presence and use of social assets within rural gentrification, an asset-based theory was developed. National datasets were mapped using empirical indicators and comparable measures of rural, urban, and peri-urban spaces to analyse the geographies of gentrification in these countries and develop a typology of rural gentrification. The archive consists of the UK element of the International Rural Gentrification (iRGENT) project The dataset contains material from a questionnaire survey conducted in 9 villages, located in 6 local authority Districts in EnglandThis project will deliver the first in-depth examination of the cross-national rural geographies of both the concept and phenomenon of gentrification, through an integrated comparative study of the theory, forms and dynamics of gentrification across rural France, UK and USA. The project aims to investigate the salience of rural gentrification as a concept that is capable of explaining rural change in France, the UK and the USA. As a starting point, the project draws upon the concept of 'sociologies of translation' to understand past and current differential meanings and uses of the term rural gentrification within academic, policy and popular discourses in France, UK and USA. An asset-based theorisation of rural gentrification will be developed to create empirical indicators of the presence and use of social assets within rural gentrification. Using these empirical indicators and comparable measures of rural, urban and peri-urban spaces, census and other national datasets will be mapped to analyse the geographies of gentrification in rural France, UK and USA, and to develop a typology of rural gentrification. Using this typology, detailed comparative studies of rural gentrification spanning a contrasting range of rural regions and rural settlement areas within France, UK and USA will be undertaken using comparable interviews, surveys, and focus groups. The deposited dates relates to a 'mixed method' personally administered questionnaire. Due to consent issues, the deposited data relates to the quantitative elements of survey, and excludes data where consent was not given for data archiving.
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.