This map contains NYC administrative boundaries enriched with various demographics datasets.Learn more about Esri's Enrich Layer / Geoenrichment analysis tool.Learn more about Esri's Demographics, Psychographic, and Socioeconomic datasets.Search for a specific location or site using the search bar. Toggle layer visibility with the layer list. Click on a layer to see more information about the feature.

2020 Census Tracts from the US Census for New York City. These boundary files are derived from the US Census Bureau's TIGER data products and have been geographically modified to fit the New York City base map. All previously released versions of this data are available at BYTES of the BIG APPLE- Archive.

"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.

My ArcGIS StoryMap is centered around The Green Book, an annual travel guide that allowed African Americans to travel safely during the height of the Jim Crow Era in the United States. More specifically, The Green Book listed establishments, such as hotels and restaurants, that would openly accept and welcome black customers into their businesses. As someone who is interested in the intersection between STEM and the humanities, I wanted to utilize The Science of Where to formulate a project that would reveal important historical implications to the public. Therefore, my overarching goal was to map each location in The Green Book in order to draw significant conclusions regarding racial segregation in one of the largest cities in the entire world.Although a more detailed methodology of my work can be found in the project itself, the following is a step by step walkthrough of my overall scientific process:Develop a question in relation to The Green Book to be solved through the completion of the project.Perform background research on The Green Book to gain a more comprehensive understanding of the subject matter.Formulate a hypothesis that answers the proposed question based on the background research.Transcribe names and addresses for each of the hotel listings in The Green Book into a comma separated values file.Transcribe names and addresses for each of the restaurants listings in The Green Book into a comma separated values file.Repeat Steps 4 and 5 for the 1940, 1950, 1960, and 1966 publications of The Green Book. In total, there should be eight unique database files (1940 New York City Hotels, 1940 New York City Restaurants, 1950 New York City Hotels, 1950 New York City Restaurants, 1960 New York City Hotels, 1960 New York City Restaurants, 1966 New York City Hotels, and 1966 New York City Restaurants.)Construct an address locator that references a New York City street base map to plot the information from the databases in Step 6 as points on a map.Manually plot locations that the address locator did not automatically match on the map.Repeat Steps 7 and 8 for all eight database files.Find and match the point locations for each listing in The Green Book with historical photographs.Generate a map tour using the geotagged images for each point from Step 10.Create a point density heat map for the locations in all eight database files.Research and obtain professional and historically accurate racial demographic data for New York City during the same time period as when The Green Book was published.Generate a hot spot map of the black population percentage using the demographic data.Analyze any geospatial trends between the point density heat maps for The Green Book and the black population percentage hot spot maps from the demographic data.Research and obtain professional and historically accurate redlining data for New York City during the same time period as when The Green Book was published.Overlay the points from The Green Book listings from Step 9 on top of the redlining shapefile.Count the number of point features completely located within each redlining zone ranking utilizing the spatial join tool.Plot the data recorded from Step 18 in the form of graphs.Analyze any geospatial trends between the listings for The Green Book and its location relative to the redlining ranking zones.Draw conclusions from the analyses in Steps 15 and 20 to present a justifiable rationale for the results._Student Generated Maps:New York City Pin Location Maphttps://arcg.is/15i4nj1940 New York City Hotels Maphttps://arcg.is/WuXeq1940 New York City Restaurants Maphttps://arcg.is/L4aqq1950 New York City Hotels Maphttps://arcg.is/1CvTGj1950 New York City Restaurants Maphttps://arcg.is/0iSG4r1960 New York City Hotels Maphttps://arcg.is/1DOzeT1960 New York City Restaurants Maphttps://arcg.is/1rWKTj1966 New York City Hotels Maphttps://arcg.is/4PjOK1966 New York City Restaurants Maphttps://arcg.is/1zyDTv11930s Manhattan Black Population Percentage Enumeration District Maphttps://arcg.is/1rKSzz1930s Manhattan Black Population Percentage Hot Spot Map (Same as Previous)https://arcg.is/1rKSzz1940 Hotels Point Density Heat Maphttps://arcg.is/jD1Ki1940 Restaurants Point Density Heat Maphttps://arcg.is/1aKbTS1940 Hotels Redlining Maphttps://arcg.is/8b10y1940 Restaurants Redlining Maphttps://arcg.is/9WrXv1950 Hotels Redlining Maphttps://arcg.is/ruGiP1950 Restaurants Redlining Maphttps://arcg.is/0qzfvC01960 Hotels Redlining Maphttps://arcg.is/1KTHLK01960 Restaurants Redlining Maphttps://arcg.is/0jiu9q1966 Hotels Redlining Maphttps://arcg.is/PXKn41966 Restaurants Redlining Maphttps://arcg.is/uCD05_Bibliography:Image Credits (In Order of Appearance)Header/Thumbnail Image:Student Generated Collage (Created Using Pictures from the Schomburg Center for Research in Black Culture, Manuscripts, Archives and Rare Books Division, The New York Public Library, https://digitalcollections.nypl.org/collections/the-green-book#/?tab=about.)Mob Violence Image:Kelley, Robert W. “A Mob Rocks an out of State Car Passing.” Life Magazine, www.life.com/history/school-integration-clinton-history, The Green Book Example Image:Schomburg Center for Research in Black Culture, Manuscripts, Archives and Rare Books Division, The New York Public Library Digital Collections, https://images.nypl.org/index.php?id=5207583&t=w. 1940s Borough of Manhattan Hotels and Restaurants Photographs:“Manhattan 1940s Tax Photos.” NYC Municipal Archives Collections, The New York City Department of Records & Information Services, https://nycma.lunaimaging.com/luna/servlet/NYCMA~5~5?cic=NYCMA~5~5.Figure 1:Student Generated GraphFigure 2:Student Generated GraphFigure 3:Student Generated GraphGIS DataThe Green Book Database:Student Generated (See Above)The Green Book Listings Maps:Student Generated (See Above)The Green Book Point Density Heat Maps:Student Generated (See Above)The Green Book Road Trip Map:Student GeneratedLION New York City Single Line Street Base Map:https://www1.nyc.gov/site/planning/data-maps/open-data/dwn-lion.page 1930s Manhattan Census Data:https://s4.ad.brown.edu/Projects/UTP2/ncities.htm Mapping Inequality Redlining Data:https://dsl.richmond.edu/panorama/redlining/#loc=12/40.794/-74.072&city=manhattan-ny&text=downloads 1940 The Green Book Document:Schomburg Center for Research in Black Culture, Manuscripts, Archives and Rare Books Division, The New York Public Library. "The Negro Motorist Green-Book: 1940" The New York Public Library Digital Collections, 1940, https://digitalcollections.nypl.org/items/dc858e50-83d3-0132-2266-58d385a7b928. 1950 The Green Book Document:Schomburg Center for Research in Black Culture, Manuscripts, Archives and Rare Books Division, The New York Public Library. "The Negro Motorist Green-Book: 1950" The New York Public Library Digital Collections, 1950, https://digitalcollections.nypl.org/items/283a7180-87c6-0132-13e6-58d385a7b928. 1960 The Green Book Document:Schomburg Center for Research in Black Culture, Manuscripts, Archives and Rare Books Division, The New York Public Library. "The Travelers' Green Book: 1960" The New York Public Library Digital Collections, 1960, https://digitalcollections.nypl.org/items/a7bf74e0-9427-0132-17bf-58d385a7b928. 1966 The Green Book Document:Schomburg Center for Research in Black Culture, Manuscripts, Archives and Rare Books Division, The New York Public Library. "Travelers' Green Book: 1966-67 International Edition" The New York Public Library Digital Collections, 1966, https://digitalcollections.nypl.org/items/27516920-8308-0132-5063-58d385a7bbd0. Hyperlink Credits (In Order of Appearance)Referenced Hyperlink #1: Coen, Ross. “Sundown Towns.” Black Past, 23 Aug. 2020, blackpast.org/african-american-history/sundown-towns.Referenced Hyperlink #2: Foster, Mark S. “In the Face of ‘Jim Crow’: Prosperous Blacks and Vacations, Travel and Outdoor Leisure, 1890-1945.” The Journal of Negro History, vol. 84, no. 2, 1999, pp. 130–149., doi:10.2307/2649043. Referenced Hyperlink #3:Driskell, Jay. “An Atlas of Self-Reliance: The Negro Motorist's Green Book (1937-1964).” National Museum of American History, Smithsonian Institution, 30 July 2015, americanhistory.si.edu/blog/negro-motorists-green-book. Referenced Hyperlink #4:Kahn, Eve M. “The 'Green Book' Legacy, a Beacon for Black Travelers.” The New York Times, The New York Times, 6 Aug. 2015, www.nytimes.com/2015/08/07/arts/design/the-green-book-legacy-a-beacon-for-black-travelers.html. Referenced Hyperlink #5:Giorgis, Hannah. “The Documentary Highlighting the Real 'Green Book'.” The Atlantic, Atlantic Media Company, 25 Feb. 2019, www.theatlantic.com/entertainment/archive/2019/02/real-green-book-preserving-stories-of-jim-crow-era-travel/583294/. Referenced Hyperlink #6:Staples, Brent. “Traveling While Black: The Green Book's Black History.” The New York Times, The New York Times, 25 Jan. 2019, www.nytimes.com/2019/01/25/opinion/green-book-black-travel.html. Referenced Hyperlink #7:Pollak, Michael. “How Official Is Official?” The New York Times, The New York Times, 15 Oct. 2010, www.nytimes.com/2010/10/17/nyregion/17fyi.html. Referenced Hyperlink #8:“New Name: Avenue Becomes a Boulevard.” The New York Times, The New York Times, 22 Oct. 1987, www.nytimes.com/1987/10/22/nyregion/new-name-avenue-becomes-a-boulevard.html. Referenced Hyperlink #9:Norris, Frank. “Racial Dynamism in Los Angeles, 1900–1964.” Southern California Quarterly, vol. 99, no. 3, 2017, pp. 251–289., doi:10.1525/scq.2017.99.3.251. Referenced Hyperlink #10:Shertzer, Allison, et al. Urban Transition Historical GIS Project, 2016, https://s4.ad.brown.edu/Projects/UTP2/ncities.htm. Referenced Hyperlink #11:Mitchell, Bruce. “HOLC ‘Redlining’ Maps: The Persistent Structure Of Segregation And Economic Inequality.” National Community Reinvestment Coalition, 20 Mar. 2018,

Chart and table of population level and growth rate for the state of New York from 1900 to 2024.

This map answers the question "What is the most common, or predominant, education level for people in this area?" The map shows predominant educational attainment in each census tract. Darker colors indicate a greater gap between the predominant group and the next largest group.The U.S. Census Bureau asks citizens to indicate how far they went in formal education. The database includes seven different columns, each representing a count of population by that education level. A simple routine in compares the seven columns of information, and finds which one has the highest value, writing that to a string field. Each tract's transparency is set by a transparency field added to the data.Predominance maps can be created in ArcGIS Online by adding two fields, calculating their values, and setting up the renderer based on those two fields. See this blog by Jim Herries for details on how to create a predominance map in ArcGIS Online from any feature layer.See this GitHub repo by Jennifer Bell for a script you can run in ArcMap as a script tool, to calculate predominance for any columns of data you have.

Resident Population in Manhattan, KS (MSA) was 134.89200 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, Resident Population in Manhattan, KS (MSA) reached a record high of 137.83000 in January of 2012 and a record low of 109.03900 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for Resident Population in Manhattan, KS (MSA) - last updated from the United States Federal Reserve on July of 2025.

Many residents of New York City speak more than one language; a number of them speak and understand non-English languages more fluently than English. This dataset, derived from the Census Bureau's American Community Survey (ACS), includes information on over 1.7 million limited English proficient (LEP) residents and a subset of that population called limited English proficient citizens of voting age (CVALEP) at the Community District level. There are 59 community districts throughout NYC, with each district being represented by a Community Board.

The Metro Region Explorer is an interactive map showing population, housing, and employment trends within the tri-state New York City metropolitan region, and sharing key insights about how the region has changed from 2000 to today.Developed in collaboration between DCP Planning Labs and DCP Regional Planning, this tool will be maintained as part of our ongoing commitment to the public access and understand information about planning issues affecting NYC and the metro region.Check back for new data additions and map updates. To let us know how this app could be better, add a GitHub issue or send a tweet to @NYCPlanningLabs. If you have questions about the data and analysis, send an email to regional@planning.nyc.gov

The Capital Planning Platform is a new resource for collaborative planning, powered by open data and open source technology.The New York City Department of City Planning pioneered open data with Bytes of the Big Apple a decade ago. With the creation of the DCP"s Capital Planning Division in 2014, we envisioned a new civic technology resource: the Capital Planning Platform - a place for planners to access the maps, data, and analytics that they need to plan for public investments in neighborhoods and collaborate with one another. The NYC Facilities Explorer (beta) is a first step in building this vision. Over the months and years to come, we plan to add more map layers, new and improved datasets, and new analysis tools to this mapping platform to help automate a broad array of planning analyses and make the capital planning process more efficient, coordinated, and strategic across the public and private sectors in New York City.The Capital Planning Platform complements other data and maps that DCP produces. We also encourage users to explore the following resources, among others, on DCP"s website.NYC Census FactFinder - An interactive tool for creating demographic, social, economic, and housing profiles for neighborhoods and user-defined groupings of Census tracts.PLUTO and MapPLUTO - Extensive land use and geographic data at the tax lot level in multiple formats.Zoning and Land use Application (ZoLA) – ZoLA provides a simple way to research zoning regulations in New York City.Waterfront Access Map - This interactive map identifies and provides information about New York City’s inventory of publicly-accessible waterfront spaces.Community Portal - The DCP Community Portal offers resources on a variety of topics related to land use, community planning, and demographic trends for each of New York City’s 59 Community Boards

AbstractUrbanization often substantially influences animal movement and gene flow. However, few studies to date have examined gene flow of the same species across multiple cities. In this study, we examine brown rats (Rattus norvegicus) to test hypotheses about the repeatability of neutral evolution across four cities: Salvador, Brazil; New Orleans, USA; Vancouver, Canada; New York City, USA. At least 150 rats were sampled from each city and genotyped for a minimum of 15,000 genome-wide SNPs. Levels of genome-wide diversity were similar across cities, but varied across neighborhoods within cities. All four populations exhibited high spatial autocorrelation at the shortest distance classes (< 500 m) due to limited dispersal. Coancestry and evolutionary clustering analyses identified genetic discontinuities within each city that coincided with a resource desert in New York City, major waterways in New Orleans, and roads in Salvador and Vancouver. Such replicated studies are crucial to assessing the generality of predictions from urban evolution, and have practical applications for pest management and public health. Future studies should include a range of global cities in different biomes, incorporate multiple species, and examine the impact of specific characteristics of the built environment and human socioeconomics on gene flow. Usage notesPLINK .map file for New Orleans rat SNP GenotypesPLINK .map file for New Orleans SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.NOL.plink.mapPLINK .ped file for New Orleans rat SNP GenotypesPLINK .ped file for New Orleans SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.NOL.plink.pedPLINK .map file for New York City rat SNP GenotypesPLINK .map file for New York City SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.NYC.plink.mapPLINK .ped file for New York City rat SNP GenotypesPLINK .ped file for New York City SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.NYC.plink.pedPLINK .map file for Salvador, Brazil rat SNP GenotypesPLINK .map file for Salvador, Brazil SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.SAL.plink.mapPLINK .ped file for Salvador, Brazil rat SNP GenotypesPLINK .ped file for Salvador, Brazil SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.SAL.plink.pedPLINK .map file for Vancouver rat SNP GenotypesPLINK .map file for Vancouver SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.VAN.plink.mapPLINK .ped file for Vancouver rat SNP GenotypesPLINK .ped file for Vancouver SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.VAN.plink.ped

Feature layer generated from running the Enrich layer solution. NYC_Community_Districts were enriched

A dataset listing New York counties by population for 2024.

Neighborhood Tabulation Areas (NTA) are medium-sized statistical geographies for reporting Decennial Census and American Community Survey (ACS). NTAs are created by aggregating census tracts and nest within Community District Tabulation Areas (CDTA). NTAs were created with the need for both geographic specificity and statistical reliability in mind. Consequently, each NTA contains enough population to mitigate sampling error associated with the ACS yet offers a unit of analysis that is smaller than a Community District.Though NTA boundaries and their associated names roughly correspond with many neighborhoods commonly recognized by New Yorkers, NTAs are not intended to definitively represent neighborhoods, nor are they intended to be exhaustive of all possible names and understandings of neighborhoods throughout New York City. Additionally, non-residential areas including large parks, airports, cemeteries, and other special areas are represented separately within this dataset and are assigned codes according to their type (See NTAType field).

Neighborhood Tabulation Areas (NTAs) were created to project populations at a small area level, from 2000 to 2030 for PlaNYC, the long-term sustainability plan for New York City. Since population size affects the error associated with population projections, these geographic units needed to have a minimum population, which we determined to be 15,000. This criterion resulted in combinations of neighborhoods that probably would not occur if one were solely designating boundaries of historical neighborhoods. Moreover, the neighborhood names associated with the neighborhood tabulation areas are not intended to be definitive. Another feature of the sustainability plan, was the creation of projections for Public Use Microdata Areas (PUMAs), which are approximations of New York City's Community Districts developed for use with the Census Bureau's Public Use Microdata Samples (PUMS). In order to make the boundaries consistent with PUMAs, NTAs were created using whole census tracts, from the 2010 census, within PUMAs. Since NTAs were not permitted to cross PUMA boundaries, this further restricted our ability to identify what may be thought of as historical neighborhood boundaries. Thus, users need to be cognizant of the reason why NTAs were created and the demographic/geographic constraints inherent in how they were configured. Despite these limitations, NTAs are a valuable summary level for use with both the 2010 Census and the American Community Survey (ACS). Regarding the decennial census, these geographic areas offer a good compromise between the very detailed data for census tracts (2,168) and the broad strokes provided by community districts (59). For the ACS, NTAs offer a statistically reliable alternative to the high sampling error that renders data for most individual census tracts unusable.

The 2020 NYC Public Use Microdata Areas (PUMAs) are statistical geographic areas defined for the dissemination of 2020 Public Use Microdata Sample (PUMS) data. PUMAs have a minimum population of 100,000, are aggregated from census tracts, and approximate Community Districts (CDs), or combinations of CDs (There are 59 CDs and only 55 NYC PUMAs because of such combinations). These boundary files are derived from the US Census Bureau's TIGER project and have been geographically modified to fit the New York City base map.