The dataset represents approximate Zip code boundaries in Westchester County. Data was downloaded from the U.S. Census Bureau 2020. The cartographic boundary files are simplified representations of selected geographic areas from the Census Bureau’s MAF/TIGER geographic database. These boundary files are specifically designed for small-scale thematic mapping. Some of the boundaries near CT were edited to match the state line. This is NOT official Postal Service data. The data was updated in August 2025.

Publication Date: April 2025. The Westchester County Parcels layer contains 2023- 2024 parcel data only for the County which gave NYS ITS Geospatial Services permission to share this data with the public. No attempt was made to edge-match parcels along adjacent counties. County attribute values were populated using 2024 Assessment Roll tabular data Geospatial Services obtained from the NYS Department of Tax and Finance’s Office of Real Property Tax Services (ORPTS).Tabular assessment data was joined to the county provided parcel geometry using the SWIS & SBL or SWIS & PRINT KEY unique identifier for each parcel. Detailed information about assessment attributes can be found in the ORPTS Assessor’s Manuals available here: https://www.tax.ny.gov/research/property/assess/manuals/assersmanual.htm. This map service is available to the public. The State of New York, acting through the New York State Office of Information Technology Services, makes no representations or warranties, express or implied, with respect to the use of or reliance on the Data provided. The User accepts the Data provided “as is” with no guarantees that it is error free, complete, accurate, current or fit for any particular purpose and assumes all risks associated with its use. The State disclaims any responsibility or legal liability to Users for damages of any kind, relating to the providing of the Data or the use of it. Users should be aware that temporal changes may have occurred since this Data was created.

This layer identifies corporate boundaries for all 45 municipal jurisdictions in Westchester County. Coverage originally obtained from New York State Office for Real Property Services (ORPS), and has been substantially modified to better align with current municipal tax parcel boundaries (WCparcels) based on a compilation of 2012 municipal tax parcel datasets. As all of Westchester's town's and cities compile their tax parcel databases independent of one another, there are situations were the tax parcels do not line up at the municipal borders, often resulting in gaps or overlaps of tax parcels at the border areas. This update sought to re-align boundaries to best follow the municipal boundaries as defined by the tax parcels, and often involved making the best possible spatial compromise where there were gaps or overlaps in tax map jurisdictions. It also reflects the 2011 municipal boundary change that resluted from the annexation of a tax parcel from the Town of Mount Pleasant to the Town of New Castle.

This data layer represents a compilation of local zoning districts and is based on zoning information compiled and digitized from each of Westchester's 43 municipalities between 2011 and 2024. It is important to note that it is not an officially adopted map of local zoning, but rather a depiction - or "snapshot" - of local zoning at the time of compilation. As such, this data layer is intended to be used for general reference purposes only. Since local zoning is constantly subject to change, inquiries regarding current status of local zoning districts, zoning designations of specific parcels, and exact use and bulk requirements should be verified at the local level by contacting the local planning or municipal clerk’s office. Selected updates were completed for this data layer in 2015 and 2016 for the municipalities of Rye City, Town of North Castle, Village of Mamaroneck and Port Chester. Updates for the City of Mount Vernon were completed in April 2021. In 2022/2023 Westchester County conducted an outreach project to obtain updated data. The following municipalities were updated during this time: Ardsley, Dobbs Ferry, Greenburgh, Lewisboro, Mount Pleasant, North Salem, New Castle, Village of Ossining, and Peekskill. Updates for Briarcliff Manor and Buchanan were made in 2024. Buchanan has one overlay district which is an exception because no other polygons should be overlapping.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces

Summary: This repository contains spatial data files representing the density of vegetation cover within a 200 meter radius of points on a grid across the land area of New York City (NYC), New York, USA based on 2017 six-inch resolution land cover data, as well as SQL code used to carry out the analysis. The 200 meter radius was selected based on a study led by researchers at the NYC Department of Health and Mental Hygiene, which found that for a given point in the city, cooling benefits of vegetation only begin to accrue once the vegetation cover within a 200 meter radius is at least 32% (Johnson et al. 2020). The grid spacing of 100 feet in north/south and east/west directions was intended to provide granular enough detail to offer useful insights at a local scale (e.g., within a neighborhood) while keeping the amount of data needed to be processed for this manageable. The contained files were developed by the NY Cities Program of The Nature Conservancy and the NYC Environmental Justice Alliance through the Just Nature NYC Partnership. Additional context and interpretation of this work is available in a blog post.

References: Johnson, S., Z. Ross, I. Kheirbek, and K. Ito. 2020. Characterization of intra-urban spatial variation in observed summer ambient temperature from the New York City Community Air Survey. Urban Climate 31:100583. https://doi.org/10.1016/j.uclim.2020.100583

Files in this Repository: Spatial Data (all data are in the New York State Plane Coordinate System - Long Island Zone, North American Datum 1983, EPSG 2263): Points with unique identifiers (fid) and data on proportion tree canopy cover (prop_canopy), proportion grass/shrub cover (prop_grassshrub), and proportion total vegetation cover (prop_veg) within a 200 meter radius (same data made available in two commonly used formats, Esri File GeoDatabase and GeoPackage): nyc_propveg2017_200mbuffer_100ftgrid_nowater.gdb.zip nyc_propveg2017_200mbuffer_100ftgrid_nowater.gpkg Raster Data with the proportion total vegetation within a 200 meter radius of the center of each cell (pixel centers align with the spatial point data) nyc_propveg2017_200mbuffer_100ftgrid_nowater.tif Computer Code: Code for generating the point data in PostgreSQL/PostGIS, assuming the data sources listed below are already in a PostGIS database. nyc_point_buffer_vegetation_overlay.sql

Data Sources and Methods: We used two openly available datasets from the City of New York for this analysis: Borough Boundaries (Clipped to Shoreline) for NYC, from the NYC Department of City Planning, available at https://www.nyc.gov/site/planning/data-maps/open-data/districts-download-metadata.page Six-inch resolution land cover data for New York City as of 2017, available at https://data.cityofnewyork.us/Environment/Land-Cover-Raster-Data-2017-6in-Resolution/he6d-2qns All data were used in the New York State Plane Coordinate System, Long Island Zone (EPSG 2263). Land cover data were used in a polygonized form for these analyses. The general steps for developing the data available in this repository were as follows: Create a grid of points across the city, based on the full extent of the Borough Boundaries dataset, with points 100 feet from one another in east/west and north/south directions Delete any points that do not overlap the areas in the Borough Boundaries dataset. Create circles centered at each point, with a radius of 200 meters (656.168 feet) in line with the aforementioned paper (Johnson et al. 2020). Overlay the circles with the land cover data, and calculate the proportion of the land cover that was grass/shrub and tree canopy land cover types. Note, because the land cover data consistently ended at the boundaries of NYC, for points within 200 meters of Nassau and Westchester Counties, the area with land cover data was smaller than the area of the circles. Relate the results from the overlay analysis back to the associated points. Create a raster data layer from the point data, with 100 foot by 100 foot resolution, where the center of each pixel is at the location of the respective points. Areas between the Borough Boundary polygons (open water of NY Harbor) are coded as "no data." All steps except for the creation of the raster dataset were conducted in PostgreSQL/PostGIS, as documented in nyc_point_buffer_vegetation_overlay.sql. The conversion of the results to a raster dataset was done in QGIS (version 3.28), ultimately using the gdal_rasterize function.

The Home Owners' Loan Corporation (HOLC) was created in the New Deal Era and trained many home appraisers in the 1930s. The HOLC created a neighborhood ranking system infamously known today as redlining. Local real estate developers and appraisers in over 200 cities assigned grades to residential neighborhoods. These maps and neighborhood ratings set the rules for decades of real estate practices. The grades ranged from A to D. A was traditionally colored in green, B was traditionally colored in blue, C was traditionally colored in yellow, and D was traditionally colored in red. A (Best): Always upper- or upper-middle-class White neighborhoods that HOLC defined as posing minimal risk for banks and other mortgage lenders, as they were "ethnically homogeneous" and had room to be further developed.B (Still Desirable): Generally nearly or completely White, U.S. -born neighborhoods that HOLC defined as "still desirable" and sound investments for mortgage lenders.C (Declining): Areas where the residents were often working-class and/or first or second generation immigrants from Europe. These areas often lacked utilities and were characterized by older building stock.D (Hazardous): Areas here often received this grade because they were "infiltrated" with "undesirable populations" such as Jewish, Asian, Mexican, and Black families. These areas were more likely to be close to industrial areas and to have older housing.Banks received federal backing to lend money for mortgages based on these grades. Many banks simply refused to lend to areas with the lowest grade, making it impossible for people in many areas to become homeowners. While this type of neighborhood classification is no longer legal thanks to the Fair Housing Act of 1968 (which was passed in large part due to the activism and work of the NAACP and other groups), the effects of disinvestment due to redlining are still observable today. For example, the health and wealth of neighborhoods in Chicago today can be traced back to redlining (Chicago Tribune). In addition to formerly redlined neighborhoods having fewer resources such as quality schools, access to fresh foods, and health care facilities, new research from the Science Museum of Virginia finds a link between urban heat islands and redlining (Hoffman, et al., 2020). This layer comes out of that work, specifically from University of Richmond's Digital Scholarship Lab. More information on sources and digitization process can be found on the Data and Download and About pages. NOTE: This map has been updated as of 1/16/24 to use a newer version of the data layer which contains more cities than it previously did. As mentioned above, over 200 cities were redlined and therefore this is not a complete dataset of every city that experienced redlining by the HOLC in the 1930s. Map opens in Sacramento, CA. Use bookmarks or the search bar to get to other cities.Cities included in this mapAlabama: Birmingham, Mobile, MontgomeryArizona: PhoenixArkansas: Arkadelphia, Batesville, Camden, Conway, El Dorado, Fort Smith, Little Rock, Russellville, TexarkanaCalifornia: Fresno, Los Angeles, Oakland, Sacramento, San Diego, San Francisco, San Jose, StocktonColorado: Boulder, Colorado Springs, Denver, Fort Collins, Fort Morgan, Grand Junction, Greeley, Longmont, PuebloConnecticut: Bridgeport and Fairfield; Hartford; New Britain; New Haven; Stamford, Darien, and New Canaan; WaterburyFlorida: Crestview, Daytona Beach, DeFuniak Springs, DeLand, Jacksonville, Miami, New Smyrna, Orlando, Pensacola, St. Petersburg, TampaGeorgia: Atlanta, Augusta, Columbus, Macon, SavannahIowa: Boone, Cedar Rapids, Council Bluffs, Davenport, Des Moines, Dubuque, Sioux City, WaterlooIllinois: Aurora, Chicago, Decatur, East St. Louis, Joliet, Peoria, Rockford, SpringfieldIndiana: Evansville, Fort Wayne, Indianapolis, Lake County Gary, Muncie, South Bend, Terre HauteKansas: Atchison, Greater Kansas City, Junction City, Topeka, WichitaKentucky: Covington, Lexington, LouisvilleLouisiana: New Orleans, ShreveportMaine: Augusta, Boothbay, Portland, Sanford, WatervilleMaryland: BaltimoreMassachusetts: Arlington, Belmont, Boston, Braintree, Brockton, Brookline, Cambridge, Chelsea, Dedham, Everett, Fall River, Fitchburg, Haverhill, Holyoke Chicopee, Lawrence, Lexington, Lowell, Lynn, Malden, Medford, Melrose, Milton, Needham, New Bedford, Newton, Pittsfield, Quincy, Revere, Salem, Saugus, Somerville, Springfield, Waltham, Watertown, Winchester, Winthrop, WorcesterMichigan: Battle Creek, Bay City, Detroit, Flint, Grand Rapids, Jackson, Kalamazoo, Lansing, Muskegon, Pontiac, Saginaw, ToledoMinnesota: Austin, Duluth, Mankato, Minneapolis, Rochester, Staples, St. Cloud, St. PaulMississippi: JacksonMissouri: Cape Girardeau, Carthage, Greater Kansas City, Joplin, Springfield, St. Joseph, St. LouisNorth Carolina: Asheville, Charlotte, Durham, Elizabeth City, Fayetteville, Goldsboro, Greensboro, Hendersonville, High Point, New Bern, Rocky Mount, Statesville, Winston-SalemNorth Dakota: Fargo, Grand Forks, Minot, WillistonNebraska: Lincoln, OmahaNew Hampshire: ManchesterNew Jersey: Atlantic City, Bergen County, Camden, Essex County, Monmouth, Passaic County, Perth Amboy, Trenton, Union CountyNew York: Albany, Binghamton/Johnson City, Bronx, Brooklyn, Buffalo, Elmira, Jamestown, Lower Westchester County, Manhattan, Niagara Falls, Poughkeepsie, Queens, Rochester, Schenectady, Staten Island, Syracuse, Troy, UticaOhio: Akron, Canton, Cleveland, Columbus, Dayton, Hamilton, Lima, Lorain, Portsmouth, Springfield, Toledo, Warren, YoungstownOklahoma: Ada, Alva, Enid, Miami Ottawa County, Muskogee, Norman, Oklahoma City, South McAlester, TulsaOregon: PortlandPennsylvania: Allentown, Altoona, Bethlehem, Chester, Erie, Harrisburg, Johnstown, Lancaster, McKeesport, New Castle, Philadelphia, Pittsburgh, Wilkes-Barre, YorkRhode Island: Pawtucket & Central Falls, Providence, WoonsocketSouth Carolina: Aiken, Charleston, Columbia, Greater Anderson, Greater Greensville, Orangeburg, Rock Hill, Spartanburg, SumterSouth Dakota: Aberdeen, Huron, Milbank, Mitchell, Rapid City, Sioux Falls, Vermillion, WatertownTennessee: Chattanooga, Elizabethton, Erwin, Greenville, Johnson City, Knoxville, Memphis, NashvilleTexas: Amarillo, Austin, Beaumont, Dallas, El Paso, Forth Worth, Galveston, Houston, Port Arthur, San Antonio, Waco, Wichita FallsUtah: Ogden, Salt Lake CityVirginia: Bristol, Danville, Harrisonburg, Lynchburg, Newport News, Norfolk, Petersburg, Phoebus, Richmond, Roanoke, StauntonVermont: Bennington, Brattleboro, Burlington, Montpelier, Newport City, Poultney, Rutland, Springfield, St. Albans, St. Johnsbury, WindsorWashington: Seattle, Spokane, TacomaWisconsin: Kenosha, Madison, Milwaukee County, Oshkosh, RacineWest Virginia: Charleston, Huntington, WheelingAn example of a map produced by the HOLC of Philadelphia:

MS4 Stormwater Outfalls: This data is a collection of stormwater outfalls (discharge points) within Westchester County, NY. The data was collected by various local sources in 2018.

This layer has been updated in July 2020 to remove all features that were located in MS4 consortium municipalities (17 municipalities are consortium in the year 2020). This layer now contains only outfalls that are nonconsortium.

This layer was created by joining the 2020 decennial Hispanic or Latino, and not Hispanic or Latino by Race data table with the 2020 Census Block geometry. The meta data for Census Blocks is below. This is 2020 Census Block Boundaries. In order for others to use the information in the Census MAF/TIGER database in a geographic information system (GIS) or for other geographic applications, the Census Bureau releases to the public extracts of the database in the form of TIGER/Line Shapefiles. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by nonvisible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2020 Census blocks nest within every other 2020 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up to the appropriate geographic areas. Census blocks cover all territory in the United States, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands). Blocks are the smallest geographic areas for which the Census Bureau publishes data from the decennial census. A block may consist of one or more faces

This coverage shows the Fire agency boundaries in the form of polygons in Westchester County. This coverage identifies fire agency boundry polygons in Westchester County. This information is captured using Microstation. Updated as of February 2011.