This web service depicts nearly 17,000 neighborhood boundaries in over 650 U.S. cities. Zillow created the neighborhood boundaries and is sharing them with the public under a Creative Commons license. Users of the data must credit Zillow as the data source. Additional information regarding this dataset can be found at https://www.zillow.com/howto/api/neighborhood-boundaries.htm. Note that neighborhood boundaries are not formal geographic boundaries for legal or jurisdictional purposes and should not be interpreted as such.

Neighborhoods are frequently cited as impactful for social, economic, political, and health outcomes. Measuring neighborhoods, however, is challenging, as the definition of a neighborhood may change dramatically across places. Researchers lack widespread but locally-sourced data on neighborhoods, and instead often adopt widely available but arbitrary Census geographies as neighborhood proxies. Others invest in the collection of more precise definitions, but these types of data are hard to collect at scale. We address this tension between scale and precision by collecting, cleaning, and providing to researchers a new dataset of city-defined neighborhoods. Our data includes 206 of the largest cities in the United States, covering more than 77 million people. We combine these data with block-level Census demographic data and provide them along with open-source software to aid researchers in their use.

The Census Bureau does not recognize or release data for Boston neighborhoods. However, Census block groups can be aggregated to approximate Boston neighborhood boundaries to allow for reporting and visualization of Census data at the neighborhood level. Census block groups are created by the U.S. Census Bureau as statistical geographic subdivisions of a census tract defined for the tabulation and presentation of data from the decennial census and the American Community Survey. The 2020 Census block group boundary files for Boston can be found here. These block group-approximated neighborhood boundaries are used for work with Census data. Work that does not rely on Census data generally uses the Boston neighborhood boundaries found here.

A. SUMMARY The Department of Public Health and the Mayor’s Office of Housing and Community Development, with support from the Planning Department, created these 41 neighborhoods by grouping 2010 Census tracts, using common real estate and residents’ definitions for the purpose of providing consistency in the analysis and reporting of socio-economic, demographic, and environmental data, and data on City-funded programs and services. These neighborhoods are not codified in Planning Code nor Administrative Code, although this map is referenced in Planning Code Section 415 as the “American Community Survey Neighborhood Profile Boundaries Map. Note: These are NOT statistical boundaries as they are not controlled for population size. This is also NOT an official map of neighborhood boundaries in SF but an aggregation of Census tracts and should be used in conjunction with other spatial boundaries for decision making. B. HOW THE DATASET IS CREATED This dataset is produced by assigning Census tracts to neighborhoods based on existing neighborhood definitions used by Planning and MOHCD. A qualitative assessment is made to identify the appropriate neighborhood for a given tract based on understanding of population distribution and significant landmarks. Once all tracts have been assigned a neighborhood, the tracts are dissolved to produce this dataset, Analysis Neighborhoods. C. UPDATE PROCESS This dataset is static. Changes to the analysis neighborhood boundaries will be evaluated as needed by the Analysis Neighborhood working group led by DataSF and the Planning department and includes staff from various other city departments. Contact us for any questions. D. HOW TO USE THIS DATASET Downloading this dataset and opening it in Excel may cause some of the data values to be lost or not display properly (particularly the Analysis Neighborhood column). For a simple list of Analysis Neighborhoods without geographic coordinates, click here: https://data.sfgov.org/resource/xfcw-9evu.csv?$select=nhood E. RELATED DATASETS 2020 Census tracts assigned a neighborhood 2010 Census tracts assigned a neighborhood

The Census Bureau does not recognize or release data for Boston neighborhoods. However, Census tracts can be aggregated to approximate Boston neighborhood boundaries to allow for reporting and visualization of Census data at the neighborhood level. Census tracts are created by the U.S. Census Bureau as statistical geographic subdivisions of a county defined for the tabulation and presentation of data from the decennial census and the American Community Survey. The 2020 Census tract boundary files for Boston can be found here. These tract-approximated neighborhood boundaries are used for work with Census data. Work that does not rely on Census data generally uses the Boston neighborhood boundaries found here.

NYC Neighborhoods polygons and correlated data with their respective Postal Codes, Assembly Districts, Community Districts, Congressional Districts, Council Districts and State Senate Districts created by Ontodia. There are hundreds of neighborhoods in New York City's five boroughs, each with unique characteristics and histories. Many historical neighborhood names are derived from the names of the previously independent villages, towns, and cities that were incorporated into into the City of New York in the consolidation of 1898. Other neighborhood names have been introduced by real estate developers and urban planners, sometimes contentiously. Boundaries of neighborhoods are notoriously fuzzy, although many boundaries are widely agreed upon. Complicating the definition of neighborhood further, boundaries may overlap, some neighborhoods may function as a micro-neighborhood within another neighborhood, or a larger district which can be made up of multiple neighborhoods. Names and boundaries of neighborhoods shift over time; they are determined by the collective conscious of the people who live, work, and play in these places. There is never an official version of neighborhoods, but the concept is deeply meaningful to many people. In many cases a New Yorker is just as proud to claim identity with a particular neighborhood, and visitors plan their trips around visits to specific neighborhoods. To display data about neighborhoods on NYCpedia we created our own neighborhood boundaries, 264 in all. In order to display a continuous map with no overlap some boundaries have been stretched or shrunk, and neighborhoods have been omitted in this version. We intend to expand our work developing neighborhood polygon files (all released with open source license) and also to collect and organize as many meaningful alternative versions of neighborhood boundaries as possible. If you are a map geek or software developer who builds apps about New York City you can find the shapefile and geoJSON of the NYCpedia neighborhoods on Data Wrangler. Drop us a line if you see any errors, or if you have suggestions for how to improve our conception of NYC geography.

This dataset contains polygons that represent the boundaries of statistical neighborhoods as defined by the DC Department of Health (DC Health). DC Health delineates statistical neighborhoods to facilitate small-area analyses and visualization of health, economic, social, and other indicators to display and uncover disparate outcomes among populations across the city. The neighborhoods are also used to determine eligibility for some health services programs and support research by various entities within and outside of government. DC Health Planning Neighborhood boundaries follow census tract 2010 lines defined by the US Census Bureau. Each neighborhood is a group of between one and seven different, contiguous census tracts. This allows for easier comparison to Census data and calculation of rates per population (including estimates from the American Community Survey and Annual Population Estimates). These do not reflect precise neighborhood locations and do not necessarily include all commonly-used neighborhood designations. There is no formal set of standards that describes which neighborhoods are included in this dataset. Note that the District of Columbia does not have official neighborhood boundaries. Origin of boundaries: each neighborhood is a group of between one and seven different, contiguous census tracts. They were originally determined in 2015 as part of an analytical research project with technical assistance from the Centers for Disease Control and Prevention (CDC) and the Council for State and Territorial Epidemiologists (CSTE) to define small area estimates of life expectancy. Census tracts were grouped roughly following the Office of Planning Neighborhood Cluster boundaries, where possible, and were made just large enough to achieve standard errors of less than 2 for each neighborhood's calculation of life expectancy. The resulting neighborhoods were used in the DC Health Equity Report (2018) with updated names. HPNs were modified slightly in 2019, incorporating one census tract that was consistently suppressed due to low numbers into a neighboring HPN (Lincoln Park incorporated into Capitol Hill). Demographic information were analyzed to identify the bordering group with the most similarities to the single census tract. A second change split a neighborhood (GWU/National Mall) into two to facilitate separate analysis.

Cincinnati SNA Boundary (2020)

The Cincinnati SNA (Statistical Neighborhood Approximations) Boundary layer shows Cincinnati neighborhoods modified to closely "fit" the US Census 2020 Data & 2016-2020 American Community Survey five-year estimates. These boundaries are useful in that they can be correlated to US Census population data. The boundaries are redrawn every ten years following the Census.

Note: The Cincinnati SNA Boundaries are NOT the same as the Cincinnati Community Council Neighborhood Boundaries.

The purpose of this dashboard is to empower community members, organizations, and other stakeholders through shared access to neighborhood-level data. The tool allows the user to view and interact with maps and reports showing data for the following Atlanta-specific geographies:City of AtlantaCity Council DistrictNeighborhood Planning Units (NPUs)Neighborhood Statistical Areas (NSAs)

The tool includes both an interactive map and report interface. The map interface enables the comparison between geographic areas within the city based on a drop-down selection of 300+ indicators across and array of categories. The report portion of the tool enables a closer look at a chosen geographic area (selected using the map) and can be tailored to the user’s specific topic of interest with pre-formatted report types, including but not limited to:

Employment EducationTransportationCrime & SafetyPoverty

Data sources:

·
Atlanta Police Department, COBRA, 2012 & 2016

·
Atlanta Fire Department, Emergency Call Records, 2012 & 2016

·
City of Atlanta Planning Department, New Building Permits, 2013 & 2016

·
U.S. Census Bureau, Decennial Census, 2000

·
U.S. Census Bureau, American Community Survey (ACS), 5-year estimates, 2011-15

·
U.S. Census Bureau, Longitudinal-Employer Household Dynamics (LEHD), 2002 & 2015

City of Seattle neighborhood boundaries with American Community Survey (ACS) 5-year series data of frequently requested topics. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment. Seattle neighborhood geography of Council Districts, Comprehensive Plan Growth Areas are included.The census block groups have been assigned to a neighborhood based on the distribution of the total population from the 2020 decennial census for the component census blocks. If the majority of the population in the block group were inside the boundaries of the neighborhood, the block group was assigned wholly to that neighborhood.Feature layer created for and used in the Neighborhood Profiles application.The attribute data associated with this map is updated annually to contain the most currently released American Community Survey (ACS) 5-year data and contains estimates and margins of error. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. For more information regarding the ACS vintage, table sources and data processing notes, please see the item page for the source map service.

Census Tracts are small, relatively permanent statistical subdivisions of a county or statistically equivalent entity delineated by local participants as part of the U.S. Census Bureau's Participant Statistical Areas Program. The primary purpose of Census Tracts is to provide a stable set of geographic units for the presentation of decennial census data. In 1980 the New Orleans City Planning Commission, for planning and decision-making purposes, divided the city into Census Tract based 'neighborhoods'. Additional neighborhoods were created after the 1990 and 2000 Censuses. Following Hurricane Katrina the Greater New Orleans Community Data Center (GNOCDC) settled on these boundaries to facilitate the use of local data in decision-making. These neighborhoods underwent further change during the 2010 Census due to modifications (consolidation and/or splitting) of Census Tracts, the resulting boundaries were renamed as 'Neighborhood Statistical Areas' to reflect their actual function.

Data from: American Community Survey, 5-year Series

KML file of neighborhood boundaries in Chicago, as developed by the Office of Tourism. These boundaries are approximate and names are not official. To view or use these files, special GIS software, such as Google Earth, is required.

Table from the American Community Survey (ACS) 5-year series on education enrollment and attainment related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B14007/B14002 School Enrollment, B15003 Educational Attainment. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

Neighborhood polygons used by the Cook County Assessor's Office for valuation and reporting. These neighborhoods are specific to the Assessor. They are intended to represent homogenous housing submarkets, NOT Chicago community areas or municipalities.

These neighborhoods were reconstructed from individual parcels using spatial buffering and simplification. The full transformation script can be found on the Assessor's GitHub.

Read about the Assessor's 2023 Open Data Refresh.

Neighborhood boundaries for the City of Providence

The Statistical Neighborhood boundaries were developed in 1970 by the Community Renewal Program (CRP) which was administered by the current Denver Department of Community Planning and Development. Statistical Neighborhoods are typically combinations of census tracts. Geographic place names, such as Windsor and Mar Lee, were assigned to each area and reflect commonly used names of subdivisions and historical parts of the city.

This map symbolizes the relative population counts for the City's 12 Data Divisions, aggregating the tract-level estimates from the the Census Bureau's American Community Survey 2021 five-year samples. Please refer to the map's legend for context to the color shading -- darker hues indicate more population.If you click on each Data Division, you can view other Census demographic information about that Data Division in addition to the population count.About the Census Data:The data comes from the U.S. Census Bureau's American Community Survey's 2017-2021 five-year samples. The American Community Survey (ACS) is an ongoing survey conducted by the federal government that provides vital information annually about America and its population. Information from the survey generates data that help determine how more than $675 billion in federal and state funds are distributed each year.For more information about the Census Bureau's ACS data and process of constructing the survey, visit the ACS's About page.About the City's Data Divisions:As a planning analytic tool, an interdepartmental working group divided Rochester into 12 “data divisions.” These divisions are well-defined and static so they are positioned to be used by the City of Rochester for statistical and planning purposes. Census data is tied to these divisions and serves as the basis for analyses over time. As such, the data divisions are designed to follow census boundaries, while also recognizing natural and human-made boundaries, such as the River, rail lines, and highways. Historical neighborhood boundaries, while informative in the division process, did not drive the boundaries. Data divisions are distinct from the numerous neighborhoods in Rochester. Neighborhood boundaries, like quadrant boundaries, police precincts, and legislative districts often change, which makes statistical analysis challenging when looking at data over time. The data division boundaries, however, are intended to remain unchanged. It is hoped that over time, all City data analysts will adopt the data divisions for the purpose of measuring change over time throughout the city.

This dataset contains polygons that represent the boundaries of statistical neighborhoods as defined by the DC Department of Health (DC Health). DC Health delineates statistical neighborhoods to facilitate small-area analyses and visualization of health, economic, social, and other indicators to display and uncover disparate outcomes among populations across the city. The neighborhoods are also used to determine eligibility for some health services programs and support research by various entities within and outside of government. DC Health Planning Neighborhood boundaries follow census tract 2010 lines defined by the US Census Bureau. Each neighborhood is a group of between one and seven different, contiguous census tracts. This allows for easier comparison to Census data and calculation of rates per population (including estimates from the American Community Survey and Annual Population Estimates). These do not reflect precise neighborhood locations and do not necessarily include all commonly-used neighborhood designations. There is no formal set of standards that describes which neighborhoods are included in this dataset. Note that the District of Columbia does not have official neighborhood boundaries. Origin of boundaries: each neighborhood is a group of between one and seven different, contiguous census tracts. They were originally determined in 2015 as part of an analytical research project with technical assistance from the Centers for Disease Control and Prevention (CDC) and the Council for State and Territorial Epidemiologists (CSTE) to define small area estimates of life expectancy. Census tracts were grouped roughly following the Office of Planning Neighborhood Cluster boundaries, where possible, and were made just large enough to achieve standard errors of less than 2 for each neighborhood's calculation of life expectancy. The resulting neighborhoods were used in the DC Health Equity Report (2018) with updated names. HPNs were modified slightly in 2019, incorporating one census tract that was consistently suppressed due to low numbers into a neighboring HPN (Lincoln Park incorporated into Capitol Hill). Demographic information were analyzed to identify the bordering group with the most similarities to the single census tract. A second change split a neighborhood (GWU/National Mall) into two to facilitate separate analysis.

Table from the American Community Survey (ACS) B01001A-I sex by age by race - data is grouped into three age group categories for each race, under 18, 18-64 and 65 and older. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.Data on total number of people by each race alone and in combination by each census tract has been transposed to support dashboard visualizations.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): B01001Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, 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 level 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 still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.