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.

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.

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.

TransportationThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau, displays primary roads, secondary roads, local roads and railroads in the United States. According to the USCB, "This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways."Interstates 20 and 635Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (TIGERweb/Transportation) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 155 (Series Information for All Roads County-based TIGER/Line Shapefiles, Current)OGC API Features Link: (Transportation - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: Census Feature Class Codes (CFCC)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

OSNI Open Data 50k Transport Points. The transport layer contains all motorways, A, B, C class and minor roads in Northern Ireland.

By download or use of this dataset you agree to abide by the LPS Open Government Data License.

The Open Data Hub is the central location for all Transport for NSW open data. The Open Data Hub was established in April 2016 at the Future Transport summit and replaced the Transport Data Exchange (TDX) Program. Since the launch of the Hub we have welcomed more than 35,700+ registered users who have created 9000+ applications via the Open Data Hub. Browse our data catalogue to explore our available APIs, downloadable datasets, interactive maps and insights. The Open Data Hub now hosts over 200 datasets with over 1000 resources (APIs, files and other documents) and counting. Use topics, tags and formats to narrow down to your interest area. If you are interested in geospatial in particular, check out our datasets with geospatial resources. The maps are interactive allowing you to search, filter, zoom in/out. Maps data is downloadable as geospatial files resources within the same dataset. For visualisations and insights on transport related matters, you can go directly by selecting Browse Insights. Transport Open Data is sourced by many developers to feed reference or real time data into their apps which service millions of NSW citizens. To support developers getting started on using Transport Open Data, we have compiled under Developers section a collection of useful resources including step-by-step user guide, documentation, and developer information. Transport Open Data team works and collaborates continuously with various Transport teams and partners to enhance and enrich its platform, its features, data & insights available. See our Data Stories to find out some examples of how we are leveraging Transport data to provide passengers and communities with up to date and real time information Each year we run multiple Innovation Challenges, aimed at encouraging finding new ways of using data, innovation in the NSW transport sector and improving the customer experience across all transport modes in NSW. Head over to our Innovation Challenges page to view current and past challenges. Data collaborations and partnerships play an important role in enabling improvements or new ways of using Transport data, with significant positive outcomes for Transport passengers and NSW communities, in line with Transport strategies. Through co-design, co-create or data exchange with other government, research, education or industry organisations we leverage partners’ expertise and resources, enable whole of government outcomes, improve transport outcomes across the sector, all for the benefit of people of NSW. The Open Data Forum is the place to go to seek advice from our community of developers and TfNSW staff who are on hand to help. You can ask questions, discuss ideas, brag about your latest creation, or simply browse posts from a wide range of categories.

Your one-stop shop for all things active transport.\r \r \r Active transport provides tangible benefits by increasing daily physical activity levels and reducing greenhouse gas emissions through a reduction in cars on the road. Other benefits include improved social well-being and a greater sense of community.\r \r \r This data set contains links to the various data sets available on the Open Data Hub that relate to Active Transport.\r \r \r * Pop Up Cycleway \r * Cycling Propensity \r * Cycling Count \r * Cycle Network - City of Sydney \r * Cycleway Data \r * Sydney Spring Cycle 2017 - Road Closures \r * Smart Pedestrian Project \r * Active Transport: Walking \r * Smart Cities Macquarie Park \r * Walking Count Sites \r * Eurobodalla Shire Council Cycleway \r * UNSW Bicycling Dashboards \r \r

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.

This dataset and documentation contains detailed information of the iTEM Open Database, a harmonized transport data set of historical values, 1970 - 2018. It aims to create transparency through two key features: Open-Data: Assembling a comprehensive collection of publicly-available transportation data Open-Code: All code and documentation will be publicly accessible and open for modification and extension. https://github.com/transportenergy The iTEM Open Database is comprised of individual datasets collected from public sources. Each dataset is downloaded, cleaned, and harmonised to the common region and technology definitions defined by the iTEM consortium https://transportenergy.org. For each dataset, we describe the name of the dataset, the web link to the original source, the web link to the cleaning script (in python), variables, and explain the data cleaning steps (which explains the data cleaning script in plain English).

This asset includes all data collected by EPA in support of this program to address greenhouse gas emissions, fuel consumption, and criteria pollutants (NOx and PM) associated with ground freight transportation operations.

This dataset is intended to represent the location and basic attributes of known, recorded, active transport features (including Bicycle Hoop, Bicycle Rack, Bicycle Locker, Bicycle Repair Station, Bicycle Room/Compound, Bicycle Banana Rail, Bicycle Chicane assets) within the Sunshine Coast LGA. Features within this dataset have been captured by various Sunshine Coast Council personnel and methodologies.

Turkey TR: Total Inland Freight Transport: %: Road data was reported at 96.234 % in 2023. This records an increase from the previous number of 95.235 % for 2022. Turkey TR: Total Inland Freight Transport: %: Road data is updated yearly, averaging 94.795 % from Dec 1994 (Median) to 2023, with 30 observations. The data reached an all-time high of 96.234 % in 2023 and a record low of 91.933 % in 1994. Turkey TR: Total Inland Freight Transport: %: Road data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Turkey – Table TR.OECD.ITF: Freight Transport by Mode of Transport: OECD Member: Annual. [COVERAGE] Road freight transport is any movement of goods using a road vehicle on a given road network. When a road vehicle is being carried on another vehicle, only the movement of the carrying vehicle (active mode) is considered. TOTAL INLAND FREIGHT TRANSPORT Rail freight transport is any movement of goods using a railway vehicle or a given railway network. When a railway is being carries on another rail vehicle only the movement of the carrying vehicle (active mode) is being considered. Inland waterways freight transport is any movement of goods using IWT vessels which is undertaken wholly or partly on navigable inland waterways. Bunkers and stores supplied to vessels in ports are excluded. When an IWT vessel is being carried on another vehicle, only the movement of the carrying vehicle (active mode) is taken into account. [COVERAGE] Road freight transport includes transport on the roads under the responsibility of DG of Highways (motorways, state highways and provincial roads).

China Transport: Average Distance: Passenger: Highway data was reported at 43.000 km in 2023. This records a decrease from the previous number of 67.886 km for 2022. China Transport: Average Distance: Passenger: Highway data is updated yearly, averaging 44.000 km from Dec 1950 (Median) to 2023, with 74 observations. The data reached an all-time high of 71.311 km in 2021 and a record low of 25.000 km in 1972. China Transport: Average Distance: Passenger: Highway 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 and Freight Average Distance.

Global High Speed Data Transport HSDT Solutions market size 2025 is $6880.5 Million whereas according out published study it will reach to $12560.9 Million by 2033. High Speed Data Transport HSDT Solutions market will be growing at a CAGR of 7.814% during 2025 to 2033.

This is a "daily difference" dataset. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information. Records for carriers/brokers/freight forwarders with active, inactive, or pending authorities (common or contract). It includes the DOT number and MC/FF/MX number for the carrier/broker/freight forwarder, along with company census data, e.g., types of authority, address, types of insurance on file, and amounts of insurance on file.

The attached data set includes socio economic and travel characteristics data of formal public transport and paratransit users in Visakhapatnam, India

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.

The USA: Transport prices, world average = 100: The latest value from 2021 is 115.97 index points, an increase from 110.32 index points in 2017. In comparison, the world average is 92.43 index points, based on data from 165 countries. Historically, the average for the USA from 2017 to 2021 is 113.15 index points. The minimum value, 110.32 index points, was reached in 2017 while the maximum of 115.97 index points was recorded in 2021.