The USGS Transportation downloadable data from The National Map (TNM) is based on TIGER/Line data provided through U.S. Census Bureau and supplemented with HERE road data to create tile cache base maps. Some of the TIGER/Line data includes limited corrections done by USGS. Transportation data consists of roads, railroads, trails, airports, and other features associated with the transport of people or commerce. The data include the name or route designator, classification, and location. Transportation data support general mapping and geographic information system technology analysis for applications such as traffic safety, congestion mitigation, disaster planning, and emergency response. The National Map transportation data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and structures, to produce general reference base maps. The National Map viewer allows free downloads of public domain transportation data in either Esri File Geodatabase or Shapefile formats. For additional information on the transportation data model, go to https://www.usgs.gov/core-science-systems/national-geospatial-program/national-map.

This table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.

Planimetric basemap layer containing transportation structures features.

Please see the following link for additional documentation- https://github.com/CityOfNewYork/nyc-planimetrics/blob/master/Capture_Rules.md.

The data set comprises the infrastructure of transport including roads (in KM), number of motor vehicles per 1000 population and railways in countries around the world.

This dataset describes the public transport networks of 25 cities across the world in multiple easy-to-use data formats. These data formats include network edge lists, temporal network event lists, SQLite databases, GeoJSON files, and General Transit Feed Specification (GTFS) compatible ZIP-files.

The source data for creating these networks has been published by public transport agencies according to the GTFS data format. To produce the network data extracts for each city, the original data have been curated for errors, filtered spatially and temporally and augmented with walking distances between public transport stops using data from OpenStreetMap.

Cities included in this dataset version: Adelaide, Belfast, Berlin, Bordeaux, Brisbane, Canberra, Detroit, Dublin, Grenoble, Helsinki, Kuopio, Lisbon, Luxembourg, Melbourne, Nantes, Palermo, Paris, Prague, Rennes, Rome, Sydney, Toulouse, Turku, Venice, and Winnipeg.

Contrary to the version 1.0 of this data set, this version (1.2) does not include the cities of Antofagasta and Athens, for which non-commercial usage of the data is not allowed.

Contrary to previous versions of the data set (1.0 and 1.2), in this version (1.2) the temporal filtering of the data has been slightly adapted, so that the daily and weekly data extracts cover all trips departing between from 03 AM on Monday to 03 AM on Tuesday (daily extract) or 03 AM of the Monday next week (weekly extract). Additionally, a temporal network extract covering a full week of operations has been added for each city.

Documentation of the data can be found in the Data Descriptor article published in Scientific Data: http://doi.org/10.1038/sdata.2018.89
When using this dataset, please cite also the above-mentioned paper.

Data used in the Bureau of Transportation Statistics' new interactive version of Transportation Economic Trends (TET). TET highlights transportation's role in the economy and explores changes (trends) over time through a series of interactive charts. TET also explains related concepts and data sources for a general audience. Interactive visualizations available at: https://data.transportation.gov/stories/s/28tb-cpjy

Intermodal Passenger Connectivity DatabaseThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the Bureau of Transportation Statistics (BTS), displays the Intermodal Passenger Connectivity Database (IPCD). According to BTS, IPCD is a "nationwide database of passenger transportation terminals, with data on the availability of connections among the various scheduled public transportation modes at each facility." The types of passenger transportation terminals include:Scheduled airline service airportsIntercity bus stationsIntercity and transit ferry terminalsLight-rail transit stationsHeavy-rail transit stationsPassenger-rail stationsBike-share stationsThe data describes the availability and locations of the above types of passenger transportation terminals. Note, transit bus service locations are not specifically included.Ronald Reagan Washington National AirportData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Intermodal Passenger Connectivity Database IPCD) and will support mapping, analysis, data exports and OGC API – Feature access.Data.gov: Intermodal Passenger Connectivity Database (IPCD) (National) - National Geospatial Data Asset (NGDA) Intermodal (Passenger)Geoplatform: Intermodal Passenger Connectivity Database (IPCD) (National) - National Geospatial Data Asset (NGDA) Intermodal (Passenger)OGC API Features Link: (Intermodal Passenger Connectivity Database - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information: Intermodal Passenger Connectivity Database IPCDFor feedback please contact: Esri_US_Federal_Data@esri.comThumbnail image courtesy of: Metropolitan Transportation Authority of the State of New YorkNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

The Intelligent Transportation Systems Joint Program Office (ITS JPO) of the U.S. Department of Transportation (U.S. DOT) has developed this ITS Benefits Database. Major objectives are; (1) document findings from the evaluation of ITS deployments pertaining to the effect of ITS on transportation systems performance, (2) provide transportation professionals with convenient access to the benefits of ITS deployment so that they can make informed planning and investment decisions.

Findings from ITS evaluations are presented in a concise summary format. Each benefit entry includes items such as a title in the form of a short statement of the evaluation finding, context narrative, and identifying information such as date, location, and source, as well as the evaluation details that describe how the identified ITS benefit was determined.

Intermodal Passenger Connectivity DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a Bureau of Transportation Statistics (BTS) feature layer, displays the Intermodal Passenger Connectivity Database (IPCD). The IPCD is a nationwide data table of rail, air, bus and ferry passenger transportation terminals. According to BTS, IPCD is a "nationwide database of passenger transportation terminals, with data on the availability of connections among the various scheduled public transportation modes at each facility." The types of passenger transportation terminals include:Scheduled airline service airportsIntercity bus stationsIntercity and transit ferry terminalsLight-rail transit stationsHeavy-rail transit stationsPassenger-rail stationsBike-share stationsThe data describes the availability and locations of the above types of passenger transportation terminals. Note, transit bus service locations are not specifically included.Niagara Frontier Transportation Authority (NFTA) - MilitaryData currency: current Federal Service (Intermodal Passenger Connectivity Database IPCD)NGDAID: 144 (Intermodal Passenger Connectivity Database (IPCD))For more information:Intermodal Passenger Connectivity Database IPCDMetadataSupport documentation: IPCD (data dictionary)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Theme CommunityThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

The pathway representation consists of segments and intersection elements. A segment is a linear graphic element that represents a continuous physical travel path terminated by path end (dead end) or physical intersection with other travel paths. Segments have one street name, one address range and one set of segment characteristics. A segment may have none or multiple alias street names. Segment types included are Freeways, Highways, Streets, Alleys (named only), Railroads, Walkways, and Bike lanes. SNDSEG_PV is a linear feature class representing the SND Segment Feature, with attributes for Street name, Address Range, Alias Street name and segment Characteristics objects. Part of the Address Range and all of Street name objects are logically shared with the Discrete Address Point-Master Address File layer. Appropriate uses include: Cartography - Used to depict the City's transportation network location and connections, typically on smaller scaled maps or images where a single line representation is appropriate. Used to depict specific classifications of roadway use, also typically at smaller scales. Used to label transportation network feature names typically on larger scaled maps. Used to label address ranges with associated transportation network features typically on larger scaled maps. Geocode reference - Used as a source for derived reference data for address validation and theoretical address location Address Range data repository - This data store is the City's address range repository defining address ranges in association with transportation network features. Polygon boundary reference - Used to define various area boundaries is other feature classes where coincident with the transportation network. Does not contain polygon features. Address based extracts - Used to create flat-file extracts typically indexed by address with reference to business data typically associated with transportation network features. Thematic linear location reference - By providing unique, stable identifiers for each linear feature, thematic data is associated to specific transportation network features via these identifiers. Thematic intersection location reference - By providing unique, stable identifiers for each intersection feature, thematic data is associated to specific transportation network features via these identifiers. Network route tracing - Used as source for derived reference data used to determine point to point travel paths or determine optimal stop allocation along a travel path. Topological connections with segments - Used to provide a specific definition of location for each transportation network feature. Also provides a specific definition of connection between each transportation network feature. (defines where the streets are and the relationship between them ie. 4th Ave is west of 5th Ave and 4th Ave does intersect with Cherry St) Event location reference - Used as source for derived reference data used to locate event and linear referencing.Data source is TRANSPO.SNDSEG_PV. Updated weekly.

National Address DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a U.S. Department of Transportation (USDOT) feature layer, displays address data in the United States. Per USDOT, "The U.S. Department of Transportation (USDOT) and its partners from all levels of government recognize the need for a National Address Database (NAD). Accurate and up-to-date addresses are critical to transportation safety and are a vital part of Next Generation 9-1-1. They are also essential for a broad range of government services, including mail delivery, permitting, and school siting. To meet this need, USDOT partners with address programs from state, local, and tribal governments to compile their authoritative data into the NAD."District of Columbia (DC) Residential AddressesData currency: Current federal service (Address Points from National Address Database)NGDAID: 196 (National Address Database (NAD))For more information: Getting to know the National Address Database (NAD); National Address DatabaseFor feedback, please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

This dataset provides transport cost and trade flow metrics for Saudi Arabia as the destination, covering all commodities. It includes key indicators related to transport expenditures, freight rates, trade intensity, and shipment weight.Indicators:Transport Expenditure (US$) – Total transport costs.FOB Value (US$ in Thousands) – Value of goods before shipping costs.Per Unit Freight Rate (US$/kg) – Transport cost per kilogram.Transport Work (Ton-km) – Transport effort measured in ton-km.Transport Work (1000 km) – Transport effort per 1000 km.Transport Cost Intensity (US$/ton-km & US$/1000 km) – Cost per ton per km.Kilograms (Thousands) – Total shipment weight.Ad Valorem Freight Rate (%) – Freight costs as a percentage of FOB value.Unit Value (US$/kg) – Price per kilogram of goods.This dataset helps track shipping costs and trade logistics related to Saudi Arabia.

This the Louisiana Department of Transportation & Development's Enterprise Linear Reference System (LRS) data with in Roads & Highways (R&H). Not all data stored within R&H are published here as the data is sensitive or it has not been populated in the database. Roads & Highways is edited daily and every attempt is made to ensure this data is accurate and up to date. There are known exceptions to this and the Department is working to replace, collect and edit these exceptions. As the Department works to improve the quality of the data, some datasets may be removed from this service or replaced with better quality data. Also, as FHWA changes reporting requirements, data is affected by these requirements and may change at anytime. There is typically a one day delay from when edits occur to this service being updated, edits are made continually as prioritized by the Department Executive Management.https://maps.dotd.la.gov/r_and_h_datadictionary/metadata.htm

The Transportation Secure Data Center (TSDC) provides free access to detailed transportation data from a variety of travel surveys and studies conducted across the nation. Data include global positioning system (GPS) readings for millions of miles of travel, along with vehicle characteristics and survey participant demographics. NREL screens the initial data for quality control, translates each data set into a consistent format, and interprets the data for spatial analysis. NREL's processing routines add information on vehicle fuel economy and road grades and join data points to the road network.

This list contains information on the status of current medallion vehicles authorized to operate in New York City.

China Transport: Cross-regional Personnel Mobility data was reported at 268.655 Person-Time mn in 05 May 2025. This records a decrease from the previous number of 282.042 Person-Time mn for 04 May 2025. China Transport: Cross-regional Personnel Mobility data is updated daily, averaging 212.260 Person-Time mn from May 2023 (Median) to 05 May 2025, with 109 observations. The data reached an all-time high of 338.762 Person-Time mn in 03 Feb 2025 and a record low of 148.939 Person-Time mn in 22 Feb 2024. China Transport: Cross-regional Personnel Mobility data remains active status in CEIC and is reported by Ministry of Transport. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TA: Transport: Passenger Traffic: Holiday Transport: Daily.

Planimetric basemap layer containing median features, which includes medians, traffic islands, "Jersey Barriers", and painted areas that are used to separate traffic flow.

Please see the following link for additional documentation- https://github.com/CityOfNewYork/nyc-planimetrics/blob/master/Capture_Rules.md.

The T-100 Domestic Market and Segment Data dataset was downloaded on April 08, 2025 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The database includes data obtained from a 100 percent census of BTS Form 41 schedule submissions by large certificated air carriers. It shows 2024 statistics for all domestic airports operated by US carriers, and all information are totals for the year. This dataset is a combination of both T-100 Market and T-100 Segments datasets. The T-100 Market includes enplanement data, and T-100 Segment data includes arrivals, departures, freight, and mail. Data is by origin airport. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529081

This vast repository houses crucial information on international trade transactions, capturing the intricate details of both export and import activities of Zimbabwe. The Export Database contains meticulous records of outbound shipments, offering valuable insights into the products, exporters, and destinations involved in each transaction. On the other hand, the Import Database provides a comprehensive view of inbound shipments, shedding light on the importers, origins, and details of the products acquired. Together, these two databases present a holistic perspective on global trade dynamics, encompassing critical metadata such as dates, product descriptions, quantities, values, and transportation specifics. Whether you are an analyst, researcher, or business professional, this comprehensive database will undoubtedly prove to be an invaluable resource for gaining a deep understanding of international trade patterns and market dynamics. Explore the wealth of information within and unlock new opportunities in the world of trade and commerce.

The Export Database contains information related to export transactions. Each entry in the database represents a specific export event. The metadata fields in this database hold crucial details about the exported products and the transaction itself. The "DATE" field indicates the date of the export. "EXPORTER NAME" refers to the name of the entity or company responsible for exporting the goods. "DESTINATION COUNTRY" indicates the country to which the products are being shipped. The "HS CODE" represents the Harmonized System code, a standardized numerical system used to classify traded products. The "PRODUCT DESCRIPTION" field provides a brief description of the exported item. The "BRAND" field specifies the brand associated with the product. "QUANTITY" indicates the total quantity of the product being exported, and "UNIT OF QUANTITY" represents the measurement unit used for quantity. "SUBITEM QUANTITY" refers to the quantity of a subitem within the main exported product. The "PACKAGES" field indicates the number of packages used for shipment. "GROSS WEIGHT" represents the total weight of the exported products. "SUBITEM FOB VALUE" and "TOTAL FOB VALUE" denote the Free on Board (FOB) value of the subitem and the total FOB value of the export, respectively. "TOTAL CIF VALUE" indicates the total cost, insurance, and freight value. "ITEM NUMBER" is a unique identifier for each product item. "TRANSPORT TYPE" specifies the mode of transportation used for the export. "INCOTERMS" refers to the standardized international trade terms defining the responsibilities of buyers and sellers during transportation. "CUSTOMS" indicates the customs information related to the export. "VARIETY" and "ATTRIBUTES" hold additional details about the product. The "OPERATION TYPE" field indicates the type of export operation, such as direct export or re-export. "MONTH" and "YEAR" represent the month and year when the export occurred.

The Import Database contains information related to import transactions. Each entry in the database represents a specific import event. The metadata fields in this database hold crucial details about the imported products and the transaction itself. The "DATE" field indicates the date of the import. "IMPORTER NAME" refers to the name of the entity or company responsible for importing the goods. "SALES COUNTRY" indicates the country from which the products are being purchased. "ORIGIN COUNTRY" denotes the country where the imported products originate. The "HS CODE" represents the Harmonized System code, a standardized numerical system used to classify traded products. The "PRODUCT DESCRIPTION" field provides a brief description of the imported item. "QUANTITY" indicates the total quantity of the product being imported, and "UNIT OF QUANTITY" represents the measurement unit used for quantity. "SUBITEM QUANTITY" refers to the quantity of a subitem within the main imported product. The "PACKAGES" field indicates the number of packages used for shipment. "GROSS WEIGHT" represents the total weight of the imported products. "TOTAL CIF VALUE" indicates the total cost, insurance, and freight value. "TOTAL FREIGHT VALUE" and "TOTAL INSURANCE VALUE" represent the respective values for freight and insurance. "ITEM FOB VALUE," "SUBITEM FOB VALUE," and "ITEM CIF VALUE" denote the Free on Board (FOB) value of the item, subitem, and the cost, insurance, and freight value of the item, respectively. "ORIGIN PORT" specifies the port from which the products were shipped. "TRANSPORT TYPE" specifies the mode of transportation used for the import. "INCOTERMS" refers to the standardized international trade terms defining the responsibilities of buyers and sellers during transportation. "ITEM NUMBER" is a unique identifier for each product item. "CUSTOMS" indicates the customs information related to the import. "OPERATION TYPE" field indicates the type of import operation, such as direct...

Provides details on the sites selected for each study, including various attributes to allow for comparison across sites.

The City of Seattle Department of Transportation (SDOT) is providing data from the public life studies it has conducted since 2017. These studies consist of measuring the number of people using public space and the types of activities present on select sidewalks across the city, as well as several parks and plazas. The data set is continually updated as SDOT and other parties conduct public life studies using Gehl Institute’s Public Life Data Protocol.

This dataset consists of four component spreadsheets and a GeoJSON file, which provide public life data as well as information about the study design and study locations:

1 Public Life Study: provides details on the different studies that have been conducted, including project information. https://data.seattle.gov/Transportation/Public-Life-Data-Study/7qru-sdcp

2 Public Life Location: provides details on the sites selected for each study, including various attributes to allow for comparison across sites.

3 Public Life People Moving: provides data on people moving through space, including total number observed, gender breakdown, group size, and age groups. https://data.seattle.gov/Transportation/Public-Life-Data-People-Moving/7rx6-5pgd

4 Public Life People Staying: provides data on people staying still in the space, including total number observed, demographic data, group size, postures, and activities. https://data.seattle.gov/Transportation/Public-Life-Data-People-Staying/5mzj-4rtf

5 Public Life Geography: A GeoJSON file with polygons of every location studied. https://data.seattle.gov/Transportation/Public-Life-Data-Geography/v4q3-5hvp

Please download and refer to the Public Life metadata document - in the attachment section below - for comprehensive information about all of the Public Life datasets.