United States of America GIS data

Census Current (2026) WMS Legal and Statistical Entities Web Map Service; January 1, 2026 vintage

Legal and Statistical Entities Web Map Service; January 1, 2010 vintage

Metropolitan and Micropolitan Statistical Areas and Related Statistical Areas: Metropolitan NECTAs, Micropolitan NECTAs, Combined Statistical Areas, Metropolitan Statistical Areas, Micropolitan Statistical Areas; January 1, 2015 vintage; Generalized

Legal and Statistical Entities Web Map Service; January 1, 2010 vintage

Census Current (2020) Physical Features Web Map Service; January 1, 2020 vintage

Legal and Statistical Entities Web Map Service; January 1, 2020 vintage

Legal and Statistical Entities Web Map Service; January 1, 2020 vintage

ACS 2015 Legal and Statistical Entities Web Map Service; January 1, 2015 vintage

Congressional Districts, Voting Districts, State Legislative Districts - Upper, State Legislative Districts - Lower; January 1, 2022 vintage; Generalized

Congressional Districts, Voting Districts, State Legislative Districts - Upper, State Legislative Districts - Lower; January 1, 2015 vintage; Generalized

Legal and Statistical Entities Web Map Service; January 1, 2020 vintage

Legal and Statistical Entities Web Map Service; January 1, 2000 vintage

Retirement Notice: This item is in mature support as of February 2026 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This layer shows children by age group by parents' labor force participation. This is shown by tract, county, and state centroids. 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.   This layer is symbolized to show the count and percent of children with no available (residential) parent in the labor force.  To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top left.  Vintage: 2019-2023ACS Table(s): B23008Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.gov  The United States Census Bureau's American Community Survey (ACS):About the Survey   Geography & ACS   Technical Documentation   News & Updates   This 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. For more information about ACS layers, visit the FAQ. 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 is 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, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). 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 erased for cartographic and mapping purposes. For census tracts, 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 level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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 that occur in areas of water, such as oceans, 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., -4444...) have been set to null, with the exception of -5555... which has been set to zero. 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.

Dates of Images: Post-Event: July 4, 2026 Pre-Event: June 19, 2026 Date of Next Image: Unknown Summary: Normalized Differential Vegetation Index (NDVI) maps are produced by converting pixel values to NDVI = (Red – NIR)/(Red + NIR), NIR indicates the near infrared band. The dynamically generated Normalized Difference Vegetation Index (NDVI) layer is an index for quantifying green vegetation. It reflects the state of vegetation health based on how vegetation reflects light at certain wavelengths. NDVI change was created by subtracting the cloud-masked post-event NDVI from the cloud-masked pre-event NDVI to show areas of potentially impacted vegetation as negative values (darker shades) and healthy/unimpacted vegetation in positive values (lighter shades). NDVI change can give insights to impacts from an event (like the scouring of vegetation from the riverbeds) but can also show changes in unrelated areas like the clearing of agriculture fields. This layer is a binary NDVI change polygon (threshold of areas where NDVI decreased by -0.25 or more) for June 19, 2026 as compared to July 4, 2026. Suggested Use: NDVI change: Commonly used to distinguish healthy/active vegetation (positive values) from potentially unhealthy/impacted vegetation (negative values). This map shows a binary flag where NDVI decreased. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page

This digital geographic dataset contains point features that represent the Building Permits issued by the City of Miami Building Department since the year 2014. The attribute table contains extensive information regarding the building permit itself, including the applications, status, cost, days, review status and many other items of interest.

Congressional Districts, Voting Districts, State Legislative Districts - Upper, State Legislative Districts - Lower; January 1, 2021 vintage; Generalized

County Subdivisions, Subbarrios, Consolidated Cities, Incorporated Places, and Census Designated Places; January 1, 2015 vintage; Generalized

The Alternative Fuels Data Center (AFDC) provides a wealth of information and data on alternative and renewable fuels, advanced vehicles, fuel-saving strategies, and emerging transportation technologies.

Accurately surveyed coordinate location used to maintain survey control during acquistion of various products for Kentucky's Aerial Photography and Elevation Data programhttps://ky.box.com/v/kymartian-gcp-phase3

Historical energy consumption in kilowatt hours (kWh) by Nashville Electric Service (NES) customers, classified by TVA Revenue Codes. Source Link: https://www.nespower.com Metadata Document: NES Monthly Energy Consumption by TVA Revenue Code Metadata.pdfContact Data Owner: opendata@nashville.gov

Legal and Statistical Entities Web Map Service; January 1, 2010 vintage

Primary roads, secondary roads, local roads, and railroads; January 1, 2020

Campus plans defines University Areas. The dataset contains locations and attributes of University Areas, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of Zoning (DCOZ) and participating D.C. government agencies.

ACS 2019 Legal and Statistical Entities Web Map Service; January 1, 2019 vintage

Seven of Charlotte's most significant older neighborhoods have been designated by City Council as Local Historic Districts, in recognition of their importance in the history and character of the city. The Historic District Commission and its staff work with property owners and businesses in the districts to assure that development and renovation occurs in a manner that is consistent with the character of the neighborhood. The purpose of a local historic district is to encourage the restoration, preservation, rehabilitation, and conservation of historically significant areas, structures, buildings, sites, and objects and their surroundings from potentially adverse influences which may cause the decline, decay, or total destruction of important historical, architectural, and archaeological features, which are a part of the city’s heritage, and to review new construction design to ensure compatibility with the character of the district.

Potential mobility projects for Strategic Investment Areas have been grouped together in an effort to provide adaptable and scale project investments. Each group of potential projects has a specific mobility focus for the set of potential projects it represents.

Legal and Statistical Entities Web Map Service; January 1, 2020 vintage

Legal and Statistical Entities Web Map Service; January 1, 2010 vintage

Holdings of the Sonoma County Agricultural Preservation and Open Space District. Includes conservation easements, open space easements conveyed to Ag + Open Space through the County of Sonoma planning process, and Ag + Open Space fee properties. This dataset represents Ag + Open Space's current portfolio of protected lands. Superseded projects (e.g. former fee properties since transferred, easements since amended or rescinded and replaced) are housed in a separate dataset.

Legal and Statistical Entities Web Map Service; January 1, 2020 vintage

Public Use Microdata Areas and ZIP Code Tabulation Areas; 2010 Census - January 1, 2010 vintage; Generalized

Full Metadata This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The layers in this web service depict ecosystem services at the census block group level for all EnviroAtlas communities. These layers illustrate the ecosystems and natural resources that are associated with clean air, clean and plentiful water, natural hazard mitigation, climate stabilization, recreation, culture, and aesthetics, and biodiversity conservation, and factors that place stress on those resources. EnviroAtlas allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the conterminous United States as well as detailed metrics for select communities. Additional descriptive information about each attribute in this web service can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Unified School Districts, Secondary School Districts, Elementary School Districts; January 1, 2016 vintage; Generalized

ACS 2021 Legal and Statistical Entities Web Map Service; January 1, 2021 vintage

The US Bureau of Justice Statistics describes law enforcement agencies as "publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This dataset includes point locations for federal, state, local, and special jurisdiction law enforcement agency facilities. This dataset was created to provide a general purpose database of law enforcement facility locations. Law enforcement facility data can been used to asses whether the total police capability of a given area is adequate and to help local governments identify areas of greatest concern. The data are also a helpful resource for situational awareness planning, emergency response, and route analysis. A version of this data is also used to map Firearm Safe Harbor Storage Locations. The points in this dataset indicate the locations of law enforcement facilities (police stations, sheriff's offices, etc.) throughout the state of Utah. Each point includes attributes such as the facility name, street address, contact information, city, zip, county, and coordinates. Points have been placed on or near the main structure of the facility. UGRC originally derived this dataset from the Homeland Infrastructure Foundation-Level Data (HIFLD) database maintained by the US Bureau of Justice Statistics. The primary source for this database was the 2008 Census of State and Local Law Enforcement Agencies. The data are currently maintained by UGRC in collaboration with the Department of Public Safety's Bureau of Criminal Identification (BCI).

Blockface Segments are unbroken sections of the curb. A blockface can be made up of several subblocks, or just one subblock. There are blockfaces on both sides of the road, each dependent on an unbroken length of curb. For more information please visit DDOT's wiki page