Neighborhood Map Atlas neighborhoods are derived from the Seattle City Clerk's Office Geographic Indexing Atlas. These are the smallest neighborhood areas and have been supplemented with alternate names from other sources in 2020. They roll up to the district areas. The sub-neighborhood field contains the most common name and the alternate name field is a comma delimited list of all the alternate names.The original atlas is designed for subject indexing of legislation, photographs, and other documents and is an unofficial delineation of neighborhood boundaries used by the City Clerks Office. Sources for this atlas and the neighborhood names used in it include a 1980 neighborhood map produced by the Department of Community Development, Seattle Public Library indexes, a 1984-1986 Neighborhood Profiles feature series in the Seattle Post-Intelligencer, numerous parks, land use and transportation planning studies, and records in the Seattle Municipal Archives. Many of the neighborhood names are traditional names whose meaning has changed over the years, and others derive from subdivision names or elementary school attendance areas.Disclaimer: The Seattle City Clerk's Office Geographic Indexing Atlas is designed for subject indexing of legislation, photographs, and other records in the City Clerk's Office and Seattle Municipal Archives according to geographic area. Neighborhoods are named and delineated in this collection of maps in order to provide consistency in the way geographic names are used in describing records of the Archives and City Clerk, thus allowing precise retrieval of records. The neighborhood names and boundaries are not intended to represent any "official" City of Seattle neighborhood map. The Office of the City Clerk makes no claims as to the completeness, accuracy, or content of any data contained in the Geographic Indexing Atlas; nor does it make any representation of any kind, including, but not limited to, warranty of the accuracy or fitness for a particular use; nor are any such warranties to be implied or inferred with respect to the representations furnished herein. The maps are subject to change for administrative purposes of the Office of the City Clerk. Information contained in the site, if used for any purpose other than as an indexing and search aid for the databases of the Office of the City Clerk, is being used at one's own risk.

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.

In 1934, the Federal Housing Administration created a financial mortgage system that rated mortgage risks for properties based on various criteria but was centered on race and ethnicity. This rating system propagated racial segregation that in many ways persists today.

The FHA Underwriting Handbook incorporated color-coded real estate investment maps that classified neighborhoods based on assumptions about a community, primarily their racial and ethnic composition, and not on the financial ability of the residents to satisfy the obligations of a mortgage loan. These maps, created by the Home Owners Loan Corporation (HOLC) were used to determine where mortgages could or could not be issued.

The neighborhoods were categoriezed into four types:
Type A : Best - newer or areas stil in demand
Type B : Still Desirable - areas expected to remain stable for many years
Type C : Definitely Declining - areas in transition
Type D : Hazardous - older areas considered risky

Neighborhoods shaded red were deemed too hazardous for federally-back loans. These "red-lined" neighborhoods were where most African American residents lived.

Many have argued tha the HOLC maps institutionalized discriminating lending practices which not only perpetuated racial segregation but also led to neighborhood disinvestment. Today, neighborhoods classified as Type C and Type D in 2934 make up the majority of neighborhoods in 2016 that are Areas of Concentrated Poverty where 50% or More are People of Color.

This data set describes Neighborhood Clusters that have been used for community planning and related purposes in the District of Columbia for many years. It does not represent boundaries of District of Columbia neighborhoods. Cluster boundaries were established in the early 2000s based on the professional judgment of the staff of the Office of Planning as reasonably descriptive units of the City for planning purposes. Once created, these boundaries have been maintained unchanged to facilitate comparisons over time, and have been used by many city agencies and outside analysts for this purpose. (The exception is that 7 “additional” areas were added to fill the gaps in the original dataset, which omitted areas without significant neighborhood character such as Rock Creek Park, the National Mall, and the Naval Observatory.) The District of Columbia does not have official neighborhood boundaries. The Office of Planning provides a separate data layer containing Neighborhood Labels that it uses to place neighborhood names on its maps. No formal set of standards describes which neighborhoods are included in that dataset.Whereas neighborhood boundaries can be subjective and fluid over time, these Neighborhood Clusters represent a stable set of boundaries that can be used to describe conditions within the District of Columbia over time.

Map Gallery for overall maps of Neighborhood Associations and Organizations registered with the City of Bloomington Housing and Neighborhood Development Department (HAND) Related Maps Individual Neighborhood Maps Neighborhood Compliance Zone Maps

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 2025 Open Data Refresh.

Note: As of April 16, 2021, this dataset will update daily with a five-day data lag.

A. SUMMARY This dataset includes COVID-19 tests by resident neighborhood and specimen collection date (the day the test was collected). Specifically, this dataset includes tests of San Francisco residents who listed a San Francisco home address at the time of testing. These resident addresses were then geo-located and mapped to neighborhoods. The resident address associated with each test is hand-entered and susceptible to errors, therefore neighborhood data should be interpreted as an approximation, not a precise nor comprehensive total.

In recent months, about 5% of tests are missing addresses and therefore cannot be included in any neighborhood totals. In earlier months, more tests were missing address data. Because of this high percentage of tests missing resident address data, this neighborhood testing data for March, April, and May should be interpreted with caution (see below)

Percentage of tests missing address information, by month in 2020 Mar - 33.6% Apr - 25.9% May - 11.1% Jun - 7.2% Jul - 5.8% Aug - 5.4% Sep - 5.1% Oct (Oct 1-12) - 5.1%

To protect the privacy of residents, the City does not disclose the number of tests in neighborhoods with resident populations of fewer than 1,000 people. These neighborhoods are omitted from the data (they include Golden Gate Park, John McLaren Park, and Lands End).

Tests for residents that listed a Skilled Nursing Facility as their home address are not included in this neighborhood-level testing data. Skilled Nursing Facilities have required and repeated testing of residents, which would change neighborhood trends and not reflect the broader neighborhood's testing data.

This data was de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected).

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. During this investigation, some test results are found to be for persons living outside of San Francisco and some people in San Francisco may be tested multiple times (which is common). To see the number of new confirmed cases by neighborhood, reference this map: https://data.sfgov.org/stories/s/Map-of-Cumulative-Cases/adm5-wq8i#new-cases-map

B. HOW THE DATASET IS CREATED COVID-19 laboratory test data is based on electronic laboratory test reports. Deduplication, quality assurance measures and other data verification processes maximize accuracy of laboratory test information. All testing data is then geo-coded by resident address. Then data is aggregated by "https://data.sfgov.org/Geographic-Locations-and-Boundaries/Analysis-Neighborhoods/p5b7-5n3h ">analysis neighborhood and specimen collection date.

Data are prepared by close of business Monday through Saturday for public display.

C. UPDATE PROCESS Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET Due to the high degree of variation in the time needed to complete tests by different labs there is a delay in this reporting. On March 24 the Health Officer ordered all labs in the City to report complete COVID-19 testing information to the local and state health departments.

In order to track trends over time, a data user can analyze this data by "specimen_collection_date".

Calculating Percent Positivity: The positivity rate is the percentage of tests that return a positive result for COVID-19 (positive tests divided by the sum of positive and negative tests). Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of percent positive. Percent positivity indicates how widesprea

This dataset was created by the DC Office of Planning and provides a simplified representation of the neighborhoods of the District of Columbia. These boundaries are used by the Office of Planning to determine appropriate locations for placement of neighborhood names on maps. They do not reflect detailed boundary information, do not necessarily include all commonly-used neighborhood designations, do not match planimetric centerlines, and do not necessarily match Neighborhood Cluster boundaries. There is no formal set of standards that describes which neighborhoods are represented or where boundaries are placed. These informal boundaries are not appropriate for display, calculation, or reporting. Their only appropriate use is to guide the placement of text labels for DC's neighborhoods. This is an informal product used for internal mapping purposes only. It should be considered draft, will be subject to change on an irregular basis, and is not intended for publication.

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 map symbolizes the relative percentages of adults living below the poverty level for the City's 12 Data Divisions, aggregating the tract-level estimates from the the Census Bureau's American Community Survey 2018 five-year samples. Please refer to the map's legend for context to the color shading -- darker hues indicate a higher level of adults living below the poverty level.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 2014-2018 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.

The Mayor’s Office utilizes the most recent data to inform decisions about COVID-19 response and policies. The Los Angeles COVID-19 Neighborhood Map visualizes the cases and deaths across 139 neighborhoods in the city. It includes the same data used by the office to spot changes in infection trends in the city, and identify areas where testing resources should be deployed.Data Source:Data are provided on a weekly basis by the LA County Department of Public Health and prepared by the LA Mayor's Office Innovation Team. The data included in this map are on a one-week lag. That means the data shown here are reporting statistics gathered from one week ago. This map will be updated weekly on Mondays. Click on the maps to zoom in, get more details, and see the legends.

This dataset contains the Geographic Information Systems (GIS) data for the City of Little Rock Neighborhood Association boundaries along with meeting information.

The My Neighborhood - Property application allows users to find property information for Baltimore County. This includes parcels and zoning information. Users have the ability to create a customized, printable map as well as a property information report. Users can search for a property and generate a report by entering in an address or 10-digit tax account id

Author: E Gunderson, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8, high schoolResource type: lessonSubject topic(s): gisRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

1. Create a custom map using Google Maps
2. Collect and plot data using Google MapsSummary: Students will learn the basics of Google Maps while using geospatial data to create their neighborhood map with the places they spend time. They will also collect data of their choice from another source (website, book, personal life) and plot the data using Google Maps.

The map shows the quality of life in all neighbourhoods, districts and municipalities. The better the 'quality of life situation' (green locations on the map), the better the neighborhood meets what people need to live or work there. Quality of life has to do with many different things: the type of houses, the people (young-old, poor-rich, ethnicity, education), crime, parks and facilities in the area... In this map, a hundred of these types of data have been collected and a calculation model converted into one digit. The map shows the data per municipality, district, neighborhood and per square of 100 x 100 m. The further you zoom in on the map, the more details you see.

Villages help elders stay at home in their neighborhoods. A Village is neighborhood-based nonprofit membership organization supported by volunteers. A Village makes it easier for older neighbors to keep living safely, comfortably and actively in their own homes and connected with their neighbors.Members continue to live in their homes. The can get together for parties, picnics, happy hours, and visits to local theaters, music, and art venues. Volunteers offer free services that can range from rides to and from medical appointments, prescription pickups, yard clean-ups, and simple handyman repairs, assistance with grocery shopping, changing light bulbs in ceiling fixtures, and reading to the visually impaired. Villages also help their members find useful community resources and reliable professionals and licensed vendors. Villages do not provide medical services, but can connect seniors with these services. They typically offer some services not traditionally offered by the DC Lead Agencies.The Department of Aging and Community Living has a senior service directory of agencies providing a variety of services. Call (202) 724-5622.

Map Gallery of individual Neighborhood Associations and Organizations registered with the City of Bloomington Housing and Neighborhood Development Department (HAND)

Related Maps
Neighborhood Maps
Neighborhood Compliance Zone Maps

Northwest Neighborhoods
Arlington Valley
Crescent Bend
Crestmont Residential Community
Fritz Terrace
Maple Heights
Near West Side
North Kinser Point
Northwood Estates
Pigeon Hill
Sixth and Ritter
Trail View
Waterman

Northeast Neighborhoods
Blue Ridge
Eastern Heights
Garden Hill
Grandview Hills
Green Acres
High Point
Matlock Heights
Old Northeast
Park Ridge East
Park Ridge
South Griffy

Southeast Neighborhoods
Arden Place
Ashwood
Barclay Gardens
Bentley Court
Bittner Woods
Bryan Park
Eastside
Elm Heights
Gentry Estates
Hearthstone
Hoosier Acres
Hyde Park Village
Longwood-Devon
Moss Creek Village
Peppergrass
Pinestone
Saint James Woods
Sherwood Oaks
Somax
Spicewood
Sunny Slopes
Sycamore Knolls
Timber Ridge
Walnut Creek
The Woodlands-Windingbrook

Southwest Neighborhoods
Autumnview
Broadview
Evergreen Village
Highland Village
McDoel Gardens
Prospect Hill
Rockport Hills
Sunflower Gardens
Southern Pines
West Pointe

"Neighborhood Financial Health (NFH) Digital Mapping and Data Tool provides neighborhood financial health indicator data for every neighborhood in New York City. DCWP's Office of Financial Empowerment (OFE) also developed NFH Indexes to present patterns in the data within and across neighborhoods. NFH Index scores describe relative differences between neighborhoods across the same indicators; they do not evaluate neighborhoods against fixed standards. OFE intends for the NFH Indexes to provide an easy reference tool for comparing neighborhoods, and to establish patterns in the relationship of NFH indicators to economic and demographic factors, such as race and income. Understanding these connections is potentially useful for uncovering systems that perpetuate the racial wealth gap, an issue with direct implications for OFE’s mission to expand asset building opportunities for New Yorkers with low and moderate incomes. This data tool was borne out of the Collaborative for Neighborhood Financial Health, a community-led initiative designed to better understand how neighborhoods influence the financial health of their residents.

Analysis of ‘Planning Neighborhood Groups Map’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/43f70602-710e-44e3-a7cd-91a8df265003 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Neighborhood notification boundaries created by the Department of City Planning. These boundaries are designed solely for the Planning Department's neighborhood notifications where neighborhood groups are notified about certain types of developments in their area. An Excel spreadsheet of Neighborhood Groups contact details can be downloaded from this page: http://sf-planning.org/index.aspx?page=1654 There are alternative neighborhood boundaries available (which include a larger number of neighborhoods) here (Mayors Office): https://data.sfgov.org/d/pty2-tcw4 and here (Realtors): https://data.sfgov.org/d/5gzd-g9ns

--- Original source retains full ownership of the source dataset ---

In order to comply with the government's information disclosure policy and facilitate the use of geographical information in business operations, GIS layers have been established for the boundaries of the 12 administrative districts and 456 neighborhoods in this city for reference and use by various government agencies or relevant units. The coordinate system used for this data is TWD97.