This dataset compiles a comprehensive database containing 90,327 street segments in New York City, covering their street design features, streetscape design, Vision Zero treatments, and neighborhood land use. It has two scales-street and street segment group (aggregation of same type of street at neighborhood). This dataset is derived based on all publicly available data, most from NYC Open Data. The detailed methods can be found in the published paper, Pedestrian and Car Occupant Crash Casualties Over a 9-Year Span of Vision Zero in New York City. To use it, please refer to the metadata file for more information and cite our work. A full list of raw data source can be found below:

Motor Vehicle Collisions – NYC Open Data: https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95

Citywide Street Centerline (CSCL) – NYC Open Data: https://data.cityofnewyork.us/City-Government/NYC-Street-Centerline-CSCL-/exjm-f27b

NYC Building Footprints – NYC Open Data: https://data.cityofnewyork.us/Housing-Development/Building-Footprints/nqwf-w8eh

Practical Canopy for New York City: https://zenodo.org/record/6547492

New York City Bike Routes – NYC Open Data: https://data.cityofnewyork.us/Transportation/New-York-City-Bike-Routes/7vsa-caz7

Sidewalk Widths NYC (originally from Sidewalk – NYC Open Data): https://www.sidewalkwidths.nyc/

LION Single Line Street Base Map - The NYC Department of City Planning (DCP): https://www.nyc.gov/site/planning/data-maps/open-data/dwn-lion.page

NYC Planimetric Database Median – NYC Open Data: https://data.cityofnewyork.us/Transportation/NYC-Planimetrics/wt4d-p43d

NYC Vision Zero Open Data (including multiple datasets including all the implementations): https://www.nyc.gov/content/visionzero/pages/open-data

NYS Traffic Data - New York State Department of Transportation Open Data: https://data.ny.gov/Transportation/NYS-Traffic-Data-Viewer/7wmy-q6mb

Smart Location Database - US Environmental Protection Agency: https://www.epa.gov/smartgrowth/smart-location-mapping

Race and ethnicity in area - American Community Survey (ACS): https://www.census.gov/programs-surveys/acs

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,

"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.

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.

White to Non-White Racial Dissimilarity (5-year estimate) Index for Orleans County, NY was 34.12% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for Orleans County, NY reached a record high of 40.84 in January of 2009 and a record low of 30.37 in January of 2019. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for Orleans County, NY - last updated from the United States Federal Reserve on July of 2025.

White to Non-White Racial Dissimilarity (5-year estimate) Index for Orange County, NY was 37.43% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for Orange County, NY reached a record high of 40.06 in January of 2012 and a record low of 37.43 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for Orange County, NY - last updated from the United States Federal Reserve on July of 2025.

White to Non-White Racial Dissimilarity (5-year estimate) Index for Queens County, NY was 52.77% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for Queens County, NY reached a record high of 54.87 in January of 2012 and a record low of 52.68 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for Queens County, NY - last updated from the United States Federal Reserve on July of 2025.

Data shows polygon locations of Potential Environmental Justice Areas (PEJA) and is defined in the PEJA field. PEJA's have been identified based on data from the 2014-2018 5-year American Community Survey (ACS), conducted by the US Census Bureau. Environmental justice efforts focus on improving the environment in communities, specifically minority and low-income communities, and addressing disproportionate adverse environmental impacts that may exist in those communities. The information balloon for each census block group area displays the census block group ID, population, percent minority, percent below poverty level, county, municipality, and a link to more information on the Department of Environmental Conservation's website https://www.dec.ny.gov/public/333.html The data was collected by the US Census Bureau as part of the American Community Survey. Reported income and race/ethnicity data were analyzed by OEJ to determine the presence of Potential Environmental Justice Areas. The designated areas are then considered for additional outreach within the permitting process, for grant eligibility, and for targeted enforcement of Environmental Conservation Law violations. Utilized established methods as originally detailed in the Interim Environmental Justice Policy, US EPA Region 2, December 2000, and recommended by the Environmental Justice Advisory Group, Recommendations for the New York State Department of Environmental Conservation Environmental Justice Program, January 2, 2002. Individual thresholds for low-income populations (statewide), minority populations (rural communities), and minority populations (urban communities) were determined by using ArcGIS 10.3 (used to indicate if census block groups overlapped Census designated urban areas) and IBM SPSS Statistics 26 (to conduct a K-means clustering algorithm on ACS data for the three categories). More detail is provided under processing steps. Service updated annually. For more information or to download layer see https://gis.ny.gov/gisdata/inventories/details.cfm?DSID=1273Download the metadata to learn more information about how the data was created and details about the attributes. Use the links within the metadata document to expand the sections of interest see http://gis.ny.gov/gisdata/metadata/nysdec.PEJA.xml

A dataset listing New York counties by population for 2024.

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

White to Non-White Racial Dissimilarity (5-year estimate) Index for Bronx County, NY was 62.09% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for Bronx County, NY reached a record high of 68.02 in January of 2009 and a record low of 61.22 in January of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for Bronx County, NY - last updated from the United States Federal Reserve on June of 2025.

This dataset contains ecological characteristics of infaunal Fishers diversity (prediction of the number of species at different levels of abundance) in the central Long Island Sound Pilot Area based on grab samples and analyses of high definition photos and video.View Dataset on the Gateway

White to Non-White Racial Dissimilarity (5-year estimate) Index for New York County, NY was 50.90% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for New York County, NY reached a record high of 62.33 in January of 2009 and a record low of 50.90 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for New York County, NY - last updated from the United States Federal Reserve on July of 2025.

Historic land uses on lots that were vacant, privately owned, and zoned for manufacturing in 2009. Information came from a review of several years of historical Sanborn maps over the past 100 years.

When the SPEED 1.0 mapping application was created in 2009, OER had its vendor examine historic land use maps on vacant, privately-owned, industrially-zoned tax lots. Up to seven years of maps for each lot were examined, and information was recorded that indicated industrial uses or potential environmental contamination such as historic fill. Data for an additional 139 lots requested by community-based organizations was added in 2014. Each record represents the information from a map from a particular year on a particular tax lot at that time. Limitations of funding determined the number of lots included and entailed that not all years were examined for each lot.

White to Non-White Racial Dissimilarity (5-year estimate) Index for Seneca County, NY was 25.79% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for Seneca County, NY reached a record high of 52.78 in January of 2013 and a record low of 25.79 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for Seneca County, NY - last updated from the United States Federal Reserve on July of 2025.

This chart shows the trend in the percentage of NY residents age 18 and over without health care coverage by gender from 2007 to 2010. Behavioral Risk Factor Surveillance System (BRFSS) sample data were used to generate annual percentages of non-institutionalized adult (18+) NYS residents with/without health insurance coverage. Health care coverage percentages are provided for 2007 forward, and are available for a range of demographic groups (New York City/Rest of State; Sex; Race/Ethnicity; Age; Education; Income; Disability Status; Employment Status; Mental Health Status). BRFSS is a random digit dialing (RDD) phone survey of the health status and health behaviors of adult NYS residents. The sample covers between 6,000 and 9,000 completed interviews annually. For more information, check out: http://www.health.ny.gov/statistics/brfss/. The "About" tab contains additional details concerning this dataset.

This chart shows the trend in health care coverage status among NY residents age 18 and over by gender from 2007 to 2010. Behavioral Risk Factor Surveillance System (BRFSS) sample data were used to generate annual percentages of non-institutionalized adult (18+) NYS residents with/without health insurance coverage. Health care coverage percentages are provided for 2007 forward, and are available for a range of demographic groups (New York City/Rest of State; Sex; Race/Ethnicity; Age; Education; Income; Disability Status; Employment Status; Mental Health Status). BRFSS is a random digit dialing (RDD) phone survey of the health status and health behaviors of adult NYS residents. The sample covers between 6,000 and 9,000 completed interviews annually. For more information, check out: http://www.health.ny.gov/statistics/brfss/. The "About" tab contains additional details concerning this dataset.

White to Non-White Racial Dissimilarity (5-year estimate) Index for Rockland County, NY was 44.89% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for Rockland County, NY reached a record high of 46.13 in January of 2022 and a record low of 43.48 in January of 2016. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for Rockland County, NY - last updated from the United States Federal Reserve on July of 2025.

What is heat vulnerability? Vulnerability to heat is how likely a person is to be injured or harmed during periods of hot weather. Heat vulnerability has been linked to individuals’ characteristics (health status, age, race, income, language spoken, etc.) as well as certain aspects of the community where one lives (environment, community demographics). These characteristics or “heat vulnerability factors” can play an important role in one’s ability to adapt to heat. What is the Heat Vulnerability Index? The effects of extreme heat on health can often be prevented. Heat-related deaths and illness are more common during the summer, especially in vulnerable populations. Since vulnerability and adaptability to extreme heat in New York State (NYS) is a growing concern, the New York State Department of Health (NYSDOH) created the Heat Vulnerability Index (HVI) to help local and state public health officials identify and map heatvulnerable areas and populations in NYS (excluding New York City which has its own HVI). The HVI can assist in directing adaptation resources based on characteristics of vulnerable populations in that community and can inform long-term heat-mitigation planning efforts in the community. The HVI can help local agencies make decisions to: set up cooling centers in rural and vulnerable areas where many do not have access to air-conditioning at home provide transportation to and from cooling centers in low income neighborhoods where there may not be public transportation or few people own vehicles include risk communication and alert messaging in multiple languages especially among communities with high proportions of people who do not understand English wellarrange home visits of people in high risk groups like the elderly living alone How was the HVI developed? The HVI was developed to identify census tracts with populations that may have increased heat vulnerability. It is based on thirteen environmental and socio-demographic heat vulnerability factors that were identified from previous studies. Census tracts are subdivisions of counties and are defined by the US Census Bureau to collect, provide and present statistical data. Census tract level information for these heat vulnerability factors was obtained from the 2006-2010 and 2008-2012 US Census Bureau American Community Surveys (ACS) and 2011 National Land Cover Database (NLCD) for 2,723 census tracts in NYS (excluding New York City). Census tracts with zero population or missing census tract data were excluded. The 13 factors were grouped into four categories that represent different aspects of heat vulnerability, which in turn were used to estimate the overall HVI for each census tract. The four heat vulnerability categories include 1) language vulnerability; 2) socio-economic vulnerability; 3) environmental and urban vulnerability; and 4) elderly isolation and elderly vulnerability. The HVI and four heat vulnerability categories were mapped to display populations in NYS that are most vulnerable to heat. More Information on HVI:Heat Vulnerability Index: Statewide and County HVI maps can be found at https://www.health.ny.gov/environmental/weather/vulnerability_index/index.htm For more information on the HVI: Nayak SG et al. Development of the heat Vulnerability Index. Public Health 2017. Open access at https://www.sciencedirect.com/science/article/pii/S003335061730327X

White to Non-White Racial Dissimilarity (5-year estimate) Index for Greene County, NY was 40.54% in January of 2023, according to the United States Federal Reserve. Historically, White to Non-White Racial Dissimilarity (5-year estimate) Index for Greene County, NY reached a record high of 55.90 in January of 2009 and a record low of 39.81 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for White to Non-White Racial Dissimilarity (5-year estimate) Index for Greene County, NY - last updated from the United States Federal Reserve on June of 2025.