Boston Neighborhood Boundaries represent a combination of zoning neighborhood boundaries, zip code boundaries and 2010 census tract boundaries. These boundaries are used in the broad sense for visualization purposes, research analysis and planning studies. However these boundaries are not official neighborhood boundaries for the City of Boston. The BPDA is not responsible for any districts or boundaries within the City of Boston except for the districts we use for planning purposes.

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.

The population density picture of Boston is generally a story of two Bostons: the high density central and northern neighborhoods, and the low density southern neighborhoods.The highest density areas of Boston are particularly concentrated in Brighton, Allston, and the Fenway area, areas of the city with large numbers of college students and young adults. There is also high population density in areas such as the Back Bay, the South End, Charlestown, the North End, and South Boston. These are all relatively small areas geographically, but have housing stock conducive to population density (e.g. multi-family dwelling units, row housing, large apartment buildings). The southern neighborhoods, specifically Hyde Park and West Roxbury, have significant numbers of people living in them, but lots sizes tend to be much larger. These areas of the city also tend to have more single family dwelling units. In that, there are fewer people per square mile than places north in the city. Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, areas of highest density exceed 30,000 persons per square kilometer. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.How to make this map for your city

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.

Boston Main Street districts are a network of 20 Main Street Organizations that use a comprehensive revitalization approach to create, build, and sustain healthy commercial districts.

Authoritative police districts dataset for the City of Boston.

Neighborhood boundaries are created based on zip code, zoning district boundaries and census tract boundaries. This GIS data layer was produced by the BRA Office of Digital Cartography and GIS. These boundaries should not be considered official neighborhood boundaries for the City of Boston. The locations of features and boundaries shown on this map are approximate and are intended for planning and visualization purposes only. This is not intended for survey, engineering, or legal purposes.

Between 1935 and 1940 the federal government’s Home Owners’ Loan Corporation (HOLC) classified the neighborhoods of 239 cities according to their perceived investment risk. This practice has since been referred to as “redlining,” as the neighborhoods classified as being the highest risk for investment were often colored red on the resultant maps. The Mapping Inequality project, a collaboration of faculty at the University of Richmond’s Digital Scholarship Lab, the University of Maryland’s Digital Curation Innovation Center, Virginia Tech, and Johns Hopkins University has digitized and georectified all 239 HOLC maps and made them publicly available, including the HOLC map of Boston from 1938. The Boston Area Research Initiative has coordinated (i.e., spatial joined) the districts from the 1938 HOLC map of Boston with census tracts from the 2010 U.S. Census. This dataset contains the original shapefile and the spatially joined tract-level data.

City of Boston Public Works Department (PWD) districts as of August 2015.

Boston Fire Department (BFD) district boundaries per general order of the fire department. New districts went into effect on 8/3/2011. This data was last updated on 9/22/2015 by BFD personnel. Boundaries are coincident with the Street Address Management (SAM) conflated street centerline data. Purpose was for use in new CAD system provided by Intergraph. Boundaries of districts created using newest version of city boundary provided by 2010 Census data.

This dataverse repository contains two datasets: 1. A one square meter resolution map of biomass for the City of Boston. Units are Mg biomass per hectare (Mg/ha). 2. A one square meter resolution map of canopy cover for the City of Boston. Units are binary: 0 = no canopy, 1 = canopy Both datasets are derived from LiDAR and high resolution remote sensing imagery. Details of the methodology are provided in the following publications: Raciti, SM, Hutyra, LR, Newell, JD, 2014. Mapping carbon storage in urban trees withmulti-source remote sensing data: Relationships between biomass, land use, and demographics in Boston neighborhoods,Science of the Total Environment, 500-501, 72-83. http://dx.doi.org/10.1016/j.scitotenv.2014.08.070 Raciti, SM, Hutyra, LR, Newell, JD, 2015. Corrigendum to “Mapping carbon storage in urban trees with multi-source remote sensing data: Relationships between biomass, land use, and demographics in Boston neighborhoods”, Science of the Total Environment, 538, 1039-1041. http://dx.doi.org/10.1016/j.scitotenv.2015.07.154

This layer represents Zoning District boundaries indicating geographic areas subject to specific zoning guidelines. Developed and maintained by the Planning Department GIS in accordance with the Boston Zoning Code.

City Council Districts were approved by the City Council, signed by the Mayor and took effect January 1, 2014. Districts were updated September 2016 based on the updates made to wards and precincts by the City of Boston Election department.

Social vulnerability is defined as the disproportionate susceptibility of some social groups to the impacts of hazards, including death, injury, loss, or disruption of livelihood. In this dataset from Climate Ready Boston, groups identified as being more vulnerable are older adults, children, people of color, people with limited English proficiency, people with low or no incomes, people with disabilities, and people with medical illnesses. Source:The analysis and definitions used in Climate Ready Boston (2016) are based on "A framework to understand the relationship between social factors that reduce resilience in cities: Application to the City of Boston." Published 2015 in the International Journal of Disaster Risk Reduction by Atyia Martin, Northeastern University.Population Definitions:Older Adults:Older adults (those over age 65) have physical vulnerabilities in a climate event; they suffer from higher rates of medical illness than the rest of the population and can have some functional limitations in an evacuation scenario, as well as when preparing for and recovering from a disaster. Furthermore, older adults are physically more vulnerable to the impacts of extreme heat. Beyond the physical risk, older adults are more likely to be socially isolated. Without an appropriate support network, an initially small risk could be exacerbated if an older adult is not able to get help.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for population over 65 years of age.Attribute label: OlderAdultChildren: Families with children require additional resources in a climate event. When school is cancelled, parents need alternative childcare options, which can mean missing work. Children are especially vulnerable to extreme heat and stress following a natural disaster.Data source: 2010 American Community Survey 5-year Estimates (ACS) data by census tract for population under 5 years of age.Attribute label: TotChildPeople of Color: People of color make up a majority (53 percent) of Boston’s population. People of color are more likely to fall into multiple vulnerable groups aswell. People of color statistically have lower levels of income and higher levels of poverty than the population at large. People of color, many of whom also have limited English proficiency, may not have ready access in their primary language to information about the dangers of extreme heat or about cooling center resources. This risk to extreme heat can be compounded by the fact that people of color often live in more densely populated urban areas that are at higher risk for heat exposure due to the urban heat island effect.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract: Black, Native American, Asian, Island, Other, Multi, Non-white Hispanics.Attribute label: POC2Limited English Proficiency: Without adequate English skills, residents can miss crucial information on how to preparefor hazards. Cultural practices for information sharing, for example, may focus on word-of-mouth communication. In a flood event, residents can also face challenges communicating with emergency response personnel. If residents are more sociallyisolated, they may be less likely to hear about upcoming events. Finally, immigrants, especially ones who are undocumented, may be reluctant to use government services out of fear of deportation or general distrust of the government or emergency personnel.Data Source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract, defined as speaks English only or speaks English “very well”.Attribute label: LEPLow to no Income: A lack of financial resources impacts a household’s ability to prepare for a disaster event and to support friends and neighborhoods. For example, residents without televisions, computers, or data-driven mobile phones may face challenges getting news about hazards or recovery resources. Renters may have trouble finding and paying deposits for replacement housing if their residence is impacted by flooding. Homeowners may be less able to afford insurance that will cover flood damage. Having low or no income can create difficulty evacuating in a disaster event because of a higher reliance on public transportation. If unable to evacuate, residents may be more at risk without supplies to stay in their homes for an extended period of time. Low- and no-income residents can also be more vulnerable to hot weather if running air conditioning or fans puts utility costs out of reach.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for low-to- no income populations. The data represents a calculated field that combines people who were 100% below the poverty level and those who were 100–149% of the poverty level.Attribute label: Low_to_NoPeople with Disabilities: People with disabilities are among the most vulnerable in an emergency; they sustain disproportionate rates of illness, injury, and death in disaster events.46 People with disabilities can find it difficult to adequately prepare for a disaster event, including moving to a safer place. They are more likely to be left behind or abandoned during evacuations. Rescue and relief resources—like emergency transportation or shelters, for example— may not be universally accessible. Research has revealed a historic pattern of discrimination against people with disabilities in times of resource scarcity, like after a major storm and flood.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for total civilian non-institutionalized population, including: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty. Attribute label: TotDisMedical Illness: Symptoms of existing medical illnesses are often exacerbated by hot temperatures. For example, heat can trigger asthma attacks or increase already high blood pressure due to the stress of high temperatures put on the body. Climate events can interrupt access to normal sources of healthcare and even life-sustaining medication. Special planning is required for people experiencing medical illness. For example, people dependent on dialysis will have different evacuation and care needs than other Boston residents in a climate event.Data source: Medical illness is a proxy measure which is based on EASI data accessed through Simply Map. Health data at the local level in Massachusetts is not available beyond zip codes. EASI modeled the health statistics for the U.S. population based upon age, sex, and race probabilities using U.S. Census Bureau data. The probabilities are modeled against the census and current year and five year forecasts. Medical illness is the sum of asthma in children, asthma in adults, heart disease, emphysema, bronchitis, cancer, diabetes, kidney disease, and liver disease. A limitation is that these numbers may be over-counted as the result of people potentially having more than one medical illness. Therefore, the analysis may have greater numbers of people with medical illness within census tracts than actually present. Overall, the analysis was based on the relationship between social factors.Attribute label: MedIllnesOther attribute definitions:GEOID10: Geographic identifier: State Code (25), Country Code (025), 2010 Census TractAREA_SQFT: Tract area (in square feet)AREA_ACRES: Tract area (in acres)POP100_RE: Tract population countHU100_RE: Tract housing unit countName: Boston Neighborhood

Boston Transportation Department (BTD) districts.

Areas that are within 10 minutes of an exit are emphasized on this map, to give an indication of how accessible neighborhoods are by highway. The colors represent 1, 3, 5 and 10 minute increments from the exits, based on posted exit speeds and local road speeds in ideal conditions. The areas were calculated using ready to use services hosted in ArcGIS which feature a road network from HERE. A simple geoprocessing tool sent 40,000+ exit locations to the service, which returned the 160,000+ polygons. ---------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.

This map compares the number of households living above the poverty line to the number of households living below. In the U.S. overall, there are 6.2 households living above the poverty line for every 1 household living below. Green areas on the map have a higher than normal number of households living above compared to below poverty. Orange areas on the map have a higher than normal number of households living below the poverty line compared to those above in that same area.In this map you see the ratio of households living above the poverty line to households living below the poverty line. For the U.S. overall, there are 6.2 households living above the poverty line for every household living below. This map is shaded to clearly show which areas have about the same ratio as the U.S. overall, and which areas have far more families living above poverty or far more families living below poverty than "normal.""The poverty rate is one of several socioeconomic indicators used by policy makers to evaluate economic conditions. It measures the percentage of people whose income fell below the poverty threshold. Federal and state governments use such estimates to allocate funds to local communities. Local communities use these estimates to identify the number of individuals or families eligible for various programs." Source: U.S. Census BureauThe map shows the ratio for states, counties, tracts and block groups, using data from the U.S. Census Bureau's American Community Survey (ACS) for 2013 for the previous 12 months. -------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.

The boundaries of locally designated historic districts in Boston that require design review for exterior alterations to buildings.

The Coastal Flood Resilience Zoning Overlay District goes beyond the areas identified in FEMA flood maps, applying to areas of the City that could be inundated during a major coastal storm event, known as a 1 percent chance flood event with 40-inches of sea level rise. The zoning overlay promotes resilient planning and design, provides consistent standards for the review of projects, and maximizes the benefits of investments in coastal resilience.