Note: These layers were compiled by Esri's Demographics Team using data from the Census Bureau's American Community Survey. These data sets are not owned by the City of Rochester.Overview of the map/data: This map shows the percentage of the population living below the federal poverty level over the previous 12 months, shown by tract, county, and state boundaries. Estimates are from the 2018 ACS 5-year samples. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Current Vintage: 2019-2023ACS Table(s): B17020, C17002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer will be updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico.Census tracts with no population are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

This archive reproduces a figure titled "Figure 3.2 Boone County population distribution" from Wang and vom Hofe (2007, p.60). The archive provides a Jupyter Notebook that uses Python and can be run in Google Colaboratory. The workflow uses the Census API to retrieve data, reproduce the figure, and ensure reproducibility for anyone accessing this archive.The Python code was developed in Google Colaboratory, or Google Colab for short, which is an Integrated Development Environment (IDE) of JupyterLab and streamlines package installation, code collaboration, and management. The Census API is used to obtain population counts from the 2000 Decennial Census (Summary File 1, 100% data). Shapefiles are downloaded from the TIGER/Line FTP Server. All downloaded data are maintained in the notebook's temporary working directory while in use. The data and shapefiles are stored separately with this archive. The final map is also stored as an HTML file.The notebook features extensive explanations, comments, code snippets, and code output. The notebook can be viewed in a PDF format or downloaded and opened in Google Colab. References to external resources are also provided for the various functional components. The notebook features code that performs the following functions:install/import necessary Python packagesdownload the Census Tract shapefile from the TIGER/Line FTP Serverdownload Census data via CensusAPI manipulate Census tabular data merge Census data with TIGER/Line shapefileapply a coordinate reference systemcalculate land area and population densitymap and export the map to HTMLexport the map to ESRI shapefileexport the table to CSVThe notebook can be modified to perform the same operations for any county in the United States by changing the State and County FIPS code parameters for the TIGER/Line shapefile and Census API downloads. The notebook can be adapted for use in other environments (i.e., Jupyter Notebook) as well as reading and writing files to a local or shared drive, or cloud drive (i.e., Google Drive).

Allows users to confirm eligibility of summer meal sites by accessing census tract and census block group (CBG) data. This tool can also be used to conduct weighted averaging as discussed in SFSP Policy Memorandum 10-2015, “Area Eligibility in Child Nutrition Programs,” published Nov. 21, 2014, available at http://www.fns.usda.gov/area-eligibility-child-nutrition-programs-0. Instructions for determining eligibility using these data are available at: http://www.fns.usda.gov/sites/default/files/Census%20Instructions%202014_0.pdf. The instructions offer two different tools to determine eligibility: the FNS Area Eligibility Mapper and a map developed by the Food Research and Action Center (FRAC). The FRAC map is constructed from the same data files and also may be used to determine eligibility. Additionally, State agencies may request the data file for every CBG and census tract, including Federal Information Processing Standards (FIPS) codes for Geographic Information System (GIS) efforts, in their State. State agencies also may provide these data to institutions and partners upon request. This tool can also be used to identify locations that are area eligible for participation in other Child Nutrition Programs.

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City map highlighting 2024 qualified census tracts (QCT) in Mesa. Low-Income Housing Tax Credit Qualified Census Tracts must have 50 percent of households with incomes below 60 percent of the Area Median Gross Income (AMGI) or have a poverty rate of 25 percent or more. Maps of Qualified Census Tracts are available at: https://www.huduser.gov/portal/datasets/qct.html

This interactive map is updated continually and shows more than 800 variables at the neighborhood level (using the 2010 Census Tract geography boundaries). The data comes from various sources such as the U.S. Census Bureau’s 2010 Decennial Census, the U.S. Census Bureau’s latest American Community Survey five-year product (currently 2011-2015), Georgia Department of Public Health, and the Georgia Department of Labor. The map uses the Weave interactive platform, which allows the user to select data variables and customize related data visualizations (charts/graphs).

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This viewer contains data directly from the U.S. Census Bureau. Use this map viewer to identify 2020 Census tract, block group, or block at a location. Map is centered on the City of Long Beach and shows the City boundary as recorded in the Census incorporated places layer. Data source: https://www.census.gov/data/developers/data-sets/TIGERweb-map-service.htmlAbout Census Tracts: https://www.census.gov/programs-surveys/geography/about/glossary.html#par_textimage_13About Census Block Groups: https://www.census.gov/programs-surveys/geography/about/glossary.html#par_textimage_4About Census Blocks: https://www.census.gov/programs-surveys/geography/about/glossary.html#par_textimage_5

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City map with census tracts boundaries

This is a component of the Story Map: In Harm’s Way: Hurricane Ida’s Impact on Socially Vulnerable Communities.The race demographics by census tract layer was acquired from the Census Bureau's American Community Survey (ACS) and is shown in areas affected by Hurricane Ida in 2021.

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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.

This feature class has been reprojected to Web Mercator Auxilary Sphere (WKID 3857) for use with this map service.

© US Census Bureau (2010) This layer is a component of US Census Tracts (California).

This cenus tract map services was created for the California Department of Alcoholic Beverage Control, License Query System.

© CSR# 139724

Census Current (2022) Legal and Statistical Entities Web Map Service; January 1, 2022 vintage.

Census Tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity that are updated by local participants prior to each decennial census as part of the Census Bureau's Participant Statistical Areas Program. The Census Bureau delineates census tracts in situations where no local participant existed or where state, local, or tribal governments declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of statistical data.

Census tracts generally have a population size between 1,200 and 8,000 people with an optimum size of 4,000 people. A census tract usually covers a contiguous area; however the spatial size of census tracts varies widely depending on the density of settlement. Census tract boundaries are delineated with the intention of being maintained over a long time so that statistical comparisons can be made from census to census. Census tracts occasionally are split due to population growth or merged as a result of substantial population decline.

Census tract boundaries generally follow visible and identifiable features. They may follow non-visible legal boundaries, such as minor civil division (MCD) or incorporated place boundaries in some states and situations, to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. Tribal census tracts are a unique geographic entity defined within federally recognized American Indian reservations and can cross state and county boundaries. Tribal census tracts may be completely different from the census tracts and block groups defined by state and county.

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This map shows density surfaces derived from the 2010 US Census block points.This data shows % of people who identified themselves as 'single race' and 'Black'The block points were interpolated using the density function to a 2km x 2km grid of the continental US (with water and coastal data masks). There are many stories in these Maps:- What is that clean North/South Line through the center? Why do so many people live East of that line?- Notice the paths of the towns in the west – why are they so linear? And it seems there is a pattern to the spaces between the towns, why?- Looking at the ethnic maps, what explains the patterns? Look at the % Native American map – what are the areas of higher values? (note I did not make a % Asian map as at this scale there was not enough % to show any significant clusters.)

This is the shapefile of the mapped 1930 census data for Austin, Texas.

Map SummaryAbout this map:This web map shows the 2020 census boundaries that lie within the jurisdiction of the city of Rochester, NY, based on the 2020 boundaries established by the U.S. Census Bureau. Census tracts are small, relatively permanent statistical subdivisions of a county that are uniquely numbered with a numeric code. In this feature layer, you can identify the tracts by their FIPS (Federal Information Processing Standards) code. Nationally, census tracts are drawn to average about 4,000 inhabitants living within their boundaries. The U.S. Census Bureau reviews the census tract boundaries every 10 years (in conjunction with the decennial census) and may split or merge them, depending on population change: when the Census finds that a tract has grown to have more than 8,000 inhabitants, that tract is split into two or more tracts; tracts that have shrunk in population to less than 1,200 people are merged within a neighboring tract. This review and revision process also may make adjustments of boundaries due to changes in boundaries of governmental jurisdictions, changes to more accurately place boundaries relative to visible features, or decisions by courts.Census tracts are subdivided into block groups that contain between 600 and 3,000 inhabitants. For more information on census tracts and block groups, please see the U.S. Census Bureau's website.To view the data dictionary, select the desired layer of the map in the "Layers" section below for more information.