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

GIS Maps, Transportation Data, and Reports for all modes of travel throughout Massachusetts.

GIS in Transportation Market Outlook

The global GIS in Transportation market size was valued at USD 9.5 billion in 2023 and is expected to reach USD 21.8 billion by 2032, growing at a CAGR of 9.5%. This rapid growth is driven by advancements in spatial data analytics and the increasing need for efficient transportation management systems across various sectors. The surge in urbanization, coupled with the rising adoption of smart city initiatives, has propelled the demand for geographic information systems (GIS) in transportation, making it an indispensable tool for urban planners and transportation authorities.

One of the primary growth factors in the GIS in Transportation market is the rising need for traffic management solutions. With increasing vehicle ownership and congested road networks, the implementation of GIS-based traffic management systems has become crucial. These systems help in real-time traffic monitoring, congestion management, and route optimization, thereby enhancing overall transportation efficiency. Additionally, the integration of GIS with Internet of Things (IoT) devices and sensors provides valuable data to city planners and traffic authorities, enabling better decision-making and improved traffic flow.

Another significant driver for the market is the growing emphasis on asset management in the transportation sector. GIS technology plays a pivotal role in tracking and managing transportation infrastructure assets such as roads, bridges, and tunnels. By leveraging GIS, transportation agencies can efficiently monitor the condition of these assets, schedule maintenance activities, and allocate resources effectively. This not only extends the lifespan of infrastructure assets but also ensures safety and reduces operational costs, thus driving the adoption of GIS in the transportation sector.

Moreover, the increasing focus on sustainable and eco-friendly transportation solutions is fostering the growth of the GIS in Transportation market. Governments and transportation authorities worldwide are promoting the use of public transit and non-motorized transportation modes to reduce carbon emissions and combat climate change. GIS technology aids in public transit planning and route optimization, ensuring efficient and sustainable transportation systems. Additionally, GIS-based solutions enable the assessment of environmental impacts and support the implementation of green transportation initiatives, further bolstering market growth.

Regionally, North America holds a significant share in the GIS in Transportation market, attributed to the early adoption of advanced technologies and substantial investments in transportation infrastructure. The presence of key market players and the implementation of smart city projects in the United States and Canada further drive the market's growth in this region. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, propelled by rapid urbanization, increasing government initiatives for smart transportation, and the expansion of transportation networks in countries like China and India.

Component Analysis

The GIS in Transportation market is segmented by component into software, hardware, and services. The software segment dominates the market, driven by the rising demand for advanced GIS applications that provide comprehensive spatial analysis, mapping, and visualization capabilities. GIS software solutions, such as geographic information systems for traffic management and route planning, are extensively utilized by transportation authorities and urban planners to improve operational efficiency and decision-making processes. The continuous evolution of GIS software, incorporating advanced features like real-time data integration and predictive analytics, further propels market growth.

Hardware components, although smaller in market share compared to software, play a crucial role in the GIS in Transportation market. Hardware components include GPS devices, sensors, and data collection tools, which are essential for gathering accurate spatial data. The increasing deployment of IoT devices and sensors in transportation infrastructure enhances data collection capabilities, thus supporting the effective implementation of GIS solutions. The integration of GIS hardware with software solutions provides a holistic approach to transportation management, driving the adoption of GIS technology in this sector.

The services segment encompasses a wide range of professional services, including consulting, implementation, and maint

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 structure ...

Tool and data set of road networks for 80 of the most populated urban areas in the world. The data consist of a graph edge list for each city and two corresponding GIS shapefiles (i.e., links and nodes).Make your own data with our ArcGIS, QGIS, and python tools available at: http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

The City of Seattle Transportation GIS Datasets | https://data-seattlecitygis.opendata.arcgis.com/datasets?t=transportation | Lifecycle status: Production | Purpose: to enable open access to SDOT GIS data. This website includes over 60 transportation-related GIS datasets from categories such as parking, transit, pedestrian, bicycle, and roadway assets. | PDDL: https://opendatacommons.org/licenses/pddl/ | The City of Seattle makes no representation or warranty as to its accuracy. The City of Seattle has created this service for our GIS Open Data website. We do reserve the right to alter, suspend, re-host, or retire this service at any time and without notice. | Datasets: 2007 Traffic Flow Counts, 2008 Traffic Flow Counts, 2009 Traffic Flow Counts, 2010 Traffic Flow Counts, 2011 Traffic Flow Counts, 2012 Traffic Flow Counts, 2013 Traffic Flow Counts, 2014 Traffic Flow Counts, 2015 Traffic Flow Counts, 2016 Traffic Flow Counts, 2017 Traffic Flow Counts, 2018 Traffic Flow Counts, Areaways, Bike Racks, Blockface, Bridges, Channelization File Geodatabase, Collisions, Crash Cushions, Curb Ramps, dotMaps Active Projects, Dynamic Message Signs, Existing Bike Facilities, Freight Network, Greater Downtown Alleys, Guardrails, High Impact Areas, Intersections, Marked Crosswalks, One-Way Streets, Paid Area Curbspaces, Pavement Moratoriums, Pay Stations, Peak Hour Parking Restrictions, Planned Bike Facilities, Public Garages or Parking Lots, Radar Speed Signs, Restricted Parking Zone (RPZ) Program, Retaining Walls, SDOT Capital Projects Input, Seattle On Street Paid Parking-Daytime Rates, Seattle On Street Paid Parking-Evening Rates, Seattle On Street Paid Parking-Morning Rates, Seattle Streets, SidewalkObservations, Sidewalks, Snow Ice Routes, Stairways, Street Design Concept Plans, Street Ends (Shoreline), Street Furnishings, Street Signs, Street Use Permits Use Addresses, Streetcar Lines, Streetcar Stations, Traffic Beacons, Traffic Cameras, Traffic Circles, Traffic Detectors, Traffic Lanes, Traffic Signals, Transit Classification, Trees.

This map presents transportation data, including highways, roads, railroads, and airports for the world.

The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.

A style file containing a collection of realistic 3D transportation symbols.

The market for GIS in Transportation is expected to grow from USD XXX million in 2025 to USD XXX million by 2033, at a CAGR of XX%. The growth of this market is attributed to the increasing adoption of GIS technology by transportation agencies to improve their planning, operations, and decision-making. GIS allows transportation agencies to visualize and analyze data on road networks, traffic patterns, and other transportation-related factors, which helps them to identify and address inefficiencies and improve the overall efficiency of the transportation system. Some of the key drivers of the GIS in Transportation market include the increasing demand for real-time traffic information, the need for improved infrastructure planning, and the growing adoption of smart city initiatives. The market is also witnessing the emergence of new trends, such as the use of artificial intelligence (AI) and machine learning (ML) to improve the accuracy and efficiency of GIS analysis. However, the market is also facing certain restraints, such as the high cost of GIS software and the lack of skilled professionals in this field.

HEPGIS is a web-based interactive geographic map server that allows users to navigate and view geo-spatial data, print maps, and obtain data on specific features using only a web browser. It includes geo-spatial data used for transportation planning. HEPGIS previously received ARRA funding for development of Economically distressed Area maps. It is also being used to demonstrate emerging trends to address MPO and statewide planning regulations/requirements , enhanced National Highway System, Primary Freight Networks, commodity flows and safety data . HEPGIS has been used to help implement MAP-21 regulations and will help implement the Grow America Act, particularly related to Ladder of Opportunities and MPO reforms.

The National Transit Map - Stops dataset was compiled on June 02, 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 National Transit Map (NTM) is a nationwide catalog of fixed-guideway and fixed-route transit service in America. It is compiled using General Transit Feed Specification (GTFS) Schedule data. The NTM Stops dataset shows stops where vehicles pick up or drop off riders. This dataset uses the GTFS stops.txt file. The GTFS schedule format and structure documentation is available at, https://gtfs.org/schedule/. To improve the spatial accuracy of the NTM Stops, the Bureau of Transportation Statistics (BTS) adjusts transit stops using context from the submitted GTFS source data and/or from other publicly available information about the transit service. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529049

GIS in Transportation Market Analysis The global GIS in transportation market is anticipated to reach a valuation of $XX million by 2033, expanding at a CAGR of XX% from 2025. The market's growth is primarily driven by the increasing demand for efficient and sustainable transportation systems, the growing adoption of GIS technology for infrastructure planning and management, and the need for real-time data for traffic management and optimization. Additionally, the emergence of smart cities and autonomous vehicles is further fueling market demand. The market is segmented by type (software, services, data) and application (road, rail, others). The software segment holds a significant share due to the high demand for GIS software for planning, design, and analysis. The road application segment dominates the market due to the extensive use of GIS for road network management, traffic analysis, and route optimization. Key players in the market include Autodesk, Bentley Systems, ESRI, Hexagon, and MDA. The North American region is expected to maintain its market dominance, followed by Europe and Asia Pacific. The market is expected to witness continued growth over the forecast period, driven by ongoing technological advancements and the rising need for efficient and data-driven transportation solutions.

This map layer is a subset of the Columbus Points of Interest layer and shows transportation facilities in the City of Columbus. Transportation facilities include airports, bus stops, parking lots, and parking garages. This layer is maintained through a cooperative effort by multiple departments of the City of Columbus using first-hand knowledge of the area as well as a variety of authoritative data sources. While significant effort is made to ensure the data is as accurate and comprehensive as possible, some points of interest may be excluded and included points may not be immediately updated as change occurs.

HEPGIS is a web-based interactive geographic map server that allows users to navigate and view geo-spatial data, print maps, and obtain data on specific features using only a web browser. It includes geo-spatial data used for transportation planning. HEPGIS previously received ARRA funding for development of Economically distressed Area maps. It is also being used to demonstrate emerging trends to address MPO and statewide planning regulations/requirements , enhanced National Highway System, Primary Freight Networks, commodity flows and safety data . HEPGIS has been used to help implement MAP-21 regulations and will help implement the Grow America Act, particularly related to Ladder of Opportunities and MPO reforms.

VDOT's mission is to plan, deliver, operate and maintain a transportation system that is safe, enables easy movement of people and goods, enhances the economy and improves our quality of life.VDOT ArcGIS Online is an interactive portal through which VDOT staff, business partners, and the public can access web mapping applications, map publications, and geospatial data pertaining to transportation in Virginia. Users can learn about, browse, search, and/or download data from this site.The products on this site are for informational purposes and may not have been prepared for legal, engineering or surveying purposes. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information.Questions? Contact the Spatial Intelligence Group.

Formerly published as TRANS_NOC_GTLF_PUB_UNK_LINE This standard houses linear features on BLM lands as well as transportation features that provide access to BLM transportation routes. In order to meet the local or state field office needs, each state may extend its GTLF data standard to collect data to fulfill local data requirements as long as the state or field office data can be cross-walked into the National GTLF data standard format. This dataset is an ongoing process, updated periodically when better data is available. The National BLM GTLF data provides standardized transportation information for use in BLM programs and analysis. At the core, this standard stores transportation information gathered, inventoried, analyzed and recorded in a BLM Transportation Management Plan or TMP. The TMP analyzes transportation options and incorporates public participation to assist in determining travel routes, modes of travel, and season of use on selected and surrounding BLM managed lands. The Idaho BLM maintains only GTLF routes that have been recorded in a TMP. This route data is identified by COORD_SRC2 = ‘TMP – Plan Name’ and PLAN_ROUTE_DSGNTN_AUTH = ‘BLM’. All other data is considered Non-BLM authoritative, administered and maintained transportation data and is provided only as spatial and tabular reference material. As new or existing transportation data is analyzed and recorded through the TMP process, the resulting data will be incorporated into the Idaho BLM GTLF authoritative data maintenance program. The Idaho BLM GTLF data contains transportation data from many different sources across the state including the TMP process, and as such may contain a variety of spatial and tabular inaccuracies and may include errors of omission or commission. The purpose for collecting and maintaining an Idaho state-wide compilation is to provide a broad overview of the transportation network for properly focused analysis or inventory purposes and to provide connectivity between BLM managed routes and the broader transportation network. As with all spatial data, this Idaho BLM GTLF data only represents an approximate or generalized spatial and tabular description of the actual transportation route. All BLM disclaimers apply to this data and that the use of this data is at the risk of the user. Additional Notes. The purpose of this dataset is to create an Idaho BLM feature class with existing routes. Due to the lack of finalized Travel Management Plans (TMP) throughout the state the best available data was used. Where TMP data was not available we used a larger collection of 1:24,000-scale "Resource Base Data" GIS road features gathered by Idaho BLM and a variety of other data collected from the state. May 4 2018: fields added for use by ID BLM for cartographic purposes. Jan 2020 update to GTLF Schema v3.0. This data set was created and is maintained by the Bureau of Land Management staff in Idaho for only those roads identified by the metadata. All other roads are included only as background source material and are not maintained in GIS or on the ground by BLM. For more information contact us at blm_id_stateoffice@blm.gov.

This dataset includes a multimodal assessment of the Cleveland Transportation Network, conducted as part of the Cleveland Moves initiative. It assesses need and comfort levels as we work to improve safety and mobility on Cleveland streets.The Pedestrian Crossing Level of Stress layer was created by our Cleveland Moves consultant, Toole Design. It uses information about the number of lanes, the speed limit, and the presence of a pedestrian island to calculate how stressful a crossing is for someone crossing. These attributes are provided by Ohio and City of Cleveland data about streets and intersections. This data was generated in 2024. The Bicycle Level of Traffic Stress layer was created by our Cleveland Moves consultant, Toole Design. It uses information about the number of lanes, the speed limit, the type of bikeway, and more to calculate the level of stress for someone riding a bicycle on a given street. These attributes are provided by Ohio and City of Cleveland data about streets and intersections. This data was generated in 2024. The ODOT Active Transportation Need layer was created by the Ohio Department of transportation, and uses several factors to determine need including access to a vehicle, poverty rates, and more.Update FrequencyThis dataset will be updated with additional analysis from the Cleveland Moves planning process by early 2025. After that point, it will be updated annually to reflect changes to Cleveland streets geared towards improving safety and mobility. Related ApplicationsA summary of this dataset can be found in the Cleveland Moves Network Assessment Dashboard.Data GlossaryThe ODOT Active Transportation Need dataset was developed by the Ohio Department of Transportation. More information about this dataset is available on their website: https://gis.dot.state.oh.us/tims_classic/Glossary ContactSarah Davis, Active Transportation Senior Plannersdavis2@clevelandohio.gov

[Metadata] Traffic Analysis Zones for the Island of Oahu, 2022. Source: Oahu Metropolitan Planning Organization (OMPO), Feb. 2024. A traffic analysis zone (TAZ) is a geographic unit used in transportation planning models. TAZs are used to represent the spatial distribution of trip origins and destinations. TAZ boundaries are defined based on Census geographies (block, block group and tract). Care has been taken so that TAZs nest within Census tracts wherever possible in order for more direct matching with Census data. TAZ boundaries are also defined by major transportation facilities (such as roadways), major environmental features (such as rivers), and with underlying land uses. The relative size of the TAZ was also a factor in determining new TAZ boundaries if the zone size was large and the zone was thought to have a significant amount of socioeconomic activity. Generally, TAZs in urban areas are smaller than those in suburban and rural areas. Note: Data is updated every 5 years or as needed.Data created by Oahu Metropolitan Planning Organization (OMPO) and vetted by the City and County of Honolulu, particularly the Department of Planning and Permitting (DPP) and the Department of Transportation Services (DTS).For more information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/taz_oah.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

TIGER road data for the MSA. When compared to high-resolution imagery and other transportation datasets positional inaccuracies were observed. As a result caution should be taken when using this dataset. TIGER, TIGER/Line, and Census TIGER are registered trademarks of the U.S. Census Bureau. ZCTA is a trademark of the U.S. Census Bureau. The Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States, Puerto Rico, and the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The boundary information in the TIGER/Line files are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement. The Census 2000 TIGER/Line files do NOT contain the Census 2000 urban areas which have not yet been delineated. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

The National Transit Map - Routes dataset was compiled on September 09, 2024 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 National Transit Map (NTM) is a nationwide catalog of fixed-guideway and fixed-route transit service in America. It is compiled using General Transit Feed Specification (GTFS) Schedule data. The NTM Routes dataset shows transit routes, which is a group of trips that are displayed to riders as a single service. To display the route alignment and trips for each route, this dataset combines the following GTFS files: routes.txt, trips.txt, and shapes.txt. The GTFS Schedule documentation is available at, https://gtfs.org/schedule/. To improve the spatial accuracy of the NTM Routes, the Bureau of Transportation Statistics (BTS) adjusts transit routes using context from the submitted GTFS source data and/or from other publicly available information about the transit service.