United States of America transport data

Traffic Analysis Zones (Labels) is a vector dataset published by the US Census Bureau. Each feature represents a labeled traffic analysis zone, identified by a GEOID, BASENAME, and NAME. The data covers the United States of America.

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 workers' place of residence by mode of commute. This is shown by tract, county, and state boundaries. 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 by the percentage of workers who drove alone. 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): B08301 (Not all lines of this ACS table are available in this feature layer.)Data 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.

Impact fees for road maintenance are levied as part of the permitting process for new commercial development projects within the City of Durham. They vary based on the impact fee zone that the request for development falls within.

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

This feature layer depicts the main roads, highways, and highway exits in Tempe. It contains three vector data layers, highway exits, roads, and highways. It includes details on road names, highway numbers, and highway exit names relevant to the Tempe EVCI suitability analysis.  This data is sourced from the City of Tempe's data catalog and is a component of ongoing efforts to development EV charging infrastructure in Tempe. Data Scope  Includes main roads and highways leading into, and through Tempe. Created October 2025   Data Use  Intended to be used in the Tempe EVCI Development Strategy Map   Data Dictionary (Layer: Highways Exits) Data Dictionary (Layer: Roads) Data Dictionary (Layer: Highways)   Additional Information Contact Name: Sustainability Division Contact Email: sustainability@tempe.gov Data Source:  City of Tempe Data Source Type:  GIS Feature Layer  Preparation Method:  Roads were included in this dataset if they contained highway exits Publish Method:  Manual Publish Frequency:  One-time

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

Segments of the National Highway System within the City of Santa Monica

Freight and Passenger maintenance facilities in California.

Wake County Street Intersection Points, updated weekly.

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

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

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

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.

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

This dataset is used to map the location of Pharmacies in Mecklneburg County. Pharmacies are often inside of other businesses such as grocery stores or other retailers. Some pharmacies are standalone businesses.

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

Rehabilitation projects for roadways, sidewalks, alleys and markings from ProTrack+. When approved this point can be selected in project solicitation phase to associate it with a Solicitation Number and/or Contract Number. All project locations must be added during initiation. As the District Department of Transportation (DDOT) works to meet the goals of quality roadways, it has taken into account road quality assessment and community requests allowing the department to first address the streets that are in greatest need and highest priority to the community. Keeping DC roads in good condition provides maximum benefit to the traveling public by enhancing the safety of the roadway and improving the ride comfort of the road surface. View our weekly construction update to find out where DDOT crews are scheduled to be working over the coming days

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

Roads included in the US Forest Service's Motor Vehicle Use Map to a modified Kentucky boundary that includes the Tennessee areas of the Land Between the Lakes and Big South Fork National Recreation Area. The feature class indicates the specific types of motorized vehicles allowed on the designated routes and their seasons of use. The feature class is designed to be consistent with the Motor Vehicle Use Map (MVUM). Only roads with a SYMBOL attribute value of 1, 2, 3, 4, 11, and 12 are Forest Service System roads and contain data concerning their availability for OHV (Off Highway Vehicle) use. This data is published and refreshed on a unit by unit basis as needed. Information for each individual unit must be verified as to be consistent with the published MVUMs prior to inclusion in this data. Not every National Forest has data included in this feature class. Data Download: https://ky.box.com/v/kymartian-usfs-roads-muvm

Intersection Treatments include:Bike Boxes Bike Chevrons Bike Crossings Protected Intersections Roundabouts Traffic Circles Two Stage Bike Turns

These resources offer non-emergency transportation to medical appointments, grocery stores, social activities, etc., and may be government or private services. This list includes programs supported through District funding for older adults, as well as services that offer support inclusive to individuals with dementia. Some of these services are available to all older adults, while others are restricted to members of organizations, such as the DC Villages. This resource guide does not include private rideshare companies such as Lyft, Uber, or Go Go Grandparent.

Sea ports, harbours and ferry terminals. Useful for maritime logistics, supply-chain analysis, and coastal access planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: industrial=port, harbour, port, amenity=ferry_terminal, building=ferry_terminal - Part of the country exports on HDX by HOT

Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT

Road network across the area tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT

Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT

April 1, 2025: data feeds from DMV are currently offline while the agency works to migrate reporting systems. The most recent data available is from December 2024. Open Data DC is working with DMV to restore data feeds as soon as possible. This dataset contains DMV business customer information. Typically DMV business customers are entities that can carry out customer transactions, on behalf of the DMV, to obtain various approved services such as tags and titling of vehicles. These entities could be dealerships, registered vehicle owners, title holders, government agencies and so forth.

The data includes the five condition categories, excellent, good, fair, poor and failed. The data reflects a sidewalk condition index score ranging from 0 to 11. The higher the value, the better the sidewalk condition. The data also includes the primary and secondary material type of the sidewalk. It also entails the 8 most common conditions and the value expressed numerically.

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).

This data logs bicycle and/or pedestrian data from our permanent counters. The permanent counters use loops, sensors, or camera systems to quantify such data. The counters continuously transmit the raw data from the location noted in the title. Counts are displayed in real-time and are grouped together in 60-minute intervals for reporting. Adjustment factors for data have not been applied to reflect field validation of equipment. Data validation is completed one year after the data is released – i.e. 2025 data will be validated by end of 2026. Data in this file is for 2026 forward. If data is needed for a project, please reach out to the Transportation and Mobility Department. Please note that this data comes from a third-party vendor, Eco-Counter, and the City of Boulder's data reporting process relies on the data extracted from their system.

Full Metadata This EnviroAtlas dataset estimates the percent of green space along walkable roads. Green space within 25 meters of the road centerline is included and the percentage is based on the total area between street intersections. Green space provides valuable benefits to neighborhood residents and walkers by providing shade, improved aesthetics, and outdoor gathering spaces. For specific information about each community's intersection density layer, consult their individual metadata records: Austin, TX; Birmingham, AL; Baltimore, MD; Brownsville, TX; Chicago, IL; Cleveland, OH; Des Moines, IA; Durham, NC; Fresno, CA; Green Bay, WI; Los Angeles, CA; Memphis, TN; Milwaukee, WI; Minneapolis/St. Paul, MN; New Bedford, MA; New Haven, CT; New York, NY; Philadelphia, PA; Phoenix, AZ; Pittsburgh, PA; Portland, ME; Paterson, NJ; Portland, OR; Salt Lake City, UT; Sonoma County, CA; St. Louis, MO; Tampa, FL; Virginia Beach/Williamsburg, VA; Washington, DC; and Woodbine, IA.

The City of Fort Worth established truck routes and commercial delivery routes in Ordinance 4750, which took effect in January 1963. The original ordinance was heavily amended by Ordinance 8077 in 1980 to simplify the code sections to be easier to enforce and follow. Additional amendments since have added and removed routes as needed. Today, the Truck Traffic ordinances are found in Article IV of Chapter 22 in Fort Worth's Code of Ordinances. Designated Truck Routes are found in § 22-114 while Commercial Delivery Routes are found in § 22-115. The overall purpose of the ordinance is to place through truck and delivery traffic onto highways, arterials and collectors, unless the trip starts or ends outside of a designated route. This GIS layer has its origins in a Bentley Microstation file based on 1994 data from the North Texas GIS Consortium. It has been revised as needed to add or remove sections designated by amendments to the ordinance.

April 1, 2025: data feeds from DMV are currently offline while the agency works to migrate reporting systems. The most recent data available is from December 2024. Open Data DC is working with DMV to restore data feeds as soon as possible. This dataset contains the active driver license information. The dataset only includes customer age, type of license( meaning noncommercial license or commercial license), permit type ( meaning learners, provisional, temporary, and regular), if it is real-id or not validated license, license expiration date, and status of the license.

Boulder County crashes mapped from CDOT data. The crash records have a variety of location information, so multiple methods were used to geolocate them, from using lat/long on CDOT roads to geocoding based on the 'loc_x" fields. The CDOT data is intact, except where street names were cleaned up for geocoding matches and city names were fixed. Then, summary information, intersection identification and corridor identification were added. The records include all crashes potentially going back to 1986 that were received from CDOT, and were mappable. This does not account for all crashes during that time period. Due to structural data changes (schema changes), this dataset contains historic crash information from 1999 thru the end of 2020. Crash data going forward will be in a new feature class named “Crashes”.

This file contains line data for pedestrian and rail bridges from AASHTO Bridge Management database.

A bar along the edge of something steep, such as stairs or a cliff, to prevent people or cars from falling off. Guard rail, guardrails, or protective guarding, are a boundary feature and may be a means to prevent or deter access to dangerous or off-limits areas while allowing light and visibility so you can see past it. In traffic engineering, a highway guardrail may prevent a vehicle from hitting roadside obstacles, which may be either man-made (signs, culvert inlets, utility poles, trees, or natural foundations), running off the road and going down a steep embankment, or veering off the roadway into oncoming traffic (commonly referred to as a median barrier). A guardrail is effectively one strong band that transfers the force of the vehicle to the rail elements, posts, and end terminals or anchors. A run of guardrail must be anchored at each terminating end either by transitioning the rail into a fixed anchor such as a bridge rail or with an end terminal or end anchor placed in the ground or within an embankment. This is a static feature class and is not updated daily.

The City of Fort Worth will have End of Road Barricades to maximize the safety of construction workers, pedestrians, and drivers. Type I style folding barricade is so named because it has only one reflective panel or rail. Type II barricades differ from Style I in that it has two reflective rails instead of one. Like Style I and Style II barricades, the Type III name refers to the number of reflective panels; in this case, three. The barricade feature class is static and is not updated on a daily basis.