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.

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/ Data Dictionary: DD_Urbanization Perceptions Small Area Index.

TO VIEW AND DOWNLOAD THE ACTUAL DATA, CLICK ON ONE OF THE LAYERS BELOWPolygon layer containing American Community Survey (ACS) 5-Year Estimate data for the most recent vintage. 5 year estimates are a rolling average of data from the past five years. The current vintage is for 2019-2023. Data is filtered for Cuyahoga County, OH, and additional calculations are performed to determine the city each census tract lies within. Therefore, this dataset is filterable for the city of Cleveland and its surrounding suburbs. To learn more about each of these datasets, click on one of datasets under "Layers". This dataset powers the City Census Viewer.This dataset is ported from the ArcGIS Living Atlas.Data GlossaryClick here, then click on "Fields" to view documentation. Use the "Layers" drop down to view documentation for different tables.Update FrequencyThis dataset is updated annually in December when the new ACS vintage is released.ContactsSamuel Martinez, Urban Analytics and Innovationsmartinez2@clevelandohio.gov

With extensive coverage nationally and across various languages, our B2C Language Demographic Data provides valuable insights for sales, marketing, and research purposes. Whether you're seeking to expand your client base, enhance lead generation efforts, or conduct market analysis, our dataset empowers you to make informed decisions and drive business growth.

Our B2C Language Demographic Data covers a wide range of languages including but not limited to Chinese, Arabic, Hindi, French, German, Vietnamese and more. By leveraging our dataset, you can identify potential prospects, explore new market opportunities, and stay ahead of the competition. Whether you're a startup looking to establish your presence, a seasoned enterprise aiming to expand your market share or a researcher, our B2C Language Demographic Data offers valuable insights.

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The City of Port Adelaide Enfield Community Profile provides demographic and economic analysis for the Council area and its suburbs based on results from the 2016, 2011, 2006, 2001, 1996 and 1991 Censuses of Population and Housing. The profile is updated with population estimates when the Australian Bureau of Statistics (ABS) releases new figures. This is an interactive query tool where results can be downloaded in various formats. Three reporting types are available from this resource: 1. Social atlas that delivers the data displayed on a map showing each SA1 area (approx 200 households), 2. Community Profile which delivers data at a District level which contain 2 to 3 suburbs, and 3. Economic Profile which reports statistics of an economic indicators. The general community profile/social atlas themes available for reporting on are: -Age -Education -Ethnicity -Disability -Employment/Income -Household types -Indigenous profile -Migration -Journey to work -Disadvantage -Population Estimates -Building approvals. It also possible to navigate to the Community Profiles of some other Councils as well.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria. The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The projections are based upon actual values obtained in 2015, and estimates obtained for 2016. A full list of all projections, including historical projections, can be found at http://apps.treasury.act.gov.au/demography/projections/act.

These population projections are not intended to present predictions of the demographic future to any degree of reliability or precision. The population projections contained here are the projected population resulting from certain assumptions about future trends in fertility, mortality and migration trends.

Future population trends are influenced by a variety of social, economic and political factors, with significant fluctuation in short-term population growth rates as well as in the underlying social, economic and political influencers. Numerous behavioural assumptions are required to be made for each age cohort and sex. Many of these assumptions will be swamped by the random impacts on the future movements of individuals through births, deaths, and relocation. Neither the authors nor the ACT Government give warranty in relation to these projections, and no liability is accepted by the authors or the Government or any other person who assisted in the preparation of the publication, for errors and omissions, loss or damage suffered as a result of any person acting in reliance thereon.

Currently, COVID-19 vaccinations are being conducted all over the world. However, the vaccination process may take some time to complete; it needs citizens’ willingness to participate as quickly as possible. Hanoi is one of the most populous cities in Vietnam, with a population of approximately eight million people, so it is generally believed to be a potential disease epicenter. Our study aims to advance the understanding of Hanoian inhabitants’ perceptions of and their willingness to participate in COVID-19 vaccinations. A random sampling technique and an online survey were conducted in Hanoi in March 2021. A total of 520 adults representing 520 households in different districts joined this investigation. The content of this study was divided into four sectors: (1) residents’ perceptions of the COVID-19 pandemic; (2) their understanding of the COVID-19 vaccine; (3) their willingness to opt for the COVID-19 vaccine; and (4) respondents’ demographic information.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and …Show full descriptionThe 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2017 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2017. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.All information contained in this file is in the public _domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and …Show full descriptionThe 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.

The 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and …Show full descriptionThe 2014 Town and Community Profiles bring together information on more than 1000 Victorian communities from a wide variety of sources, both internal and external to the Department of Health and Department of Human Services. The Profiles include information on population, geography, services and facilities, and social, cultural and demographic characteristics of each suburb, town and rural catchment in Victoria.