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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

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

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.

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.

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

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

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.

Uncover Market Research Intellect's latest GIS In Transportation Market Report, valued at USD 6.2 billion in 2024, expected to rise to USD 12.3 billion by 2033 at a CAGR of 8.5% from 2026 to 2033.

Global GIS in Transportation market size 2025 was XX Million. GIS in Transportation Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

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 GIS-T Symposium brings together professionals from government and private industry interested in the use of GIS for transportation. Get together and share experiences, see state-of-art software, and learn more about this field. Join your fellow professionals in addition to the 40+ exhibitors in the technology hall.

The Symposium offers keynote speakers, discussion forums, workshops, presentations, and a technology hall where exhibitors showcase their services. Organizations and individuals with information related to GIS in transportation are encouraged to share their experience by presenting at the Symposium.

Over 40,000 road crossings in Maine are maintained by Maine Department of Transportation (MaineDOT) managers, emergency managers, natural resource planners, and municipalities. Resource managers need a way to quickly and comprehensively assess, during the planning stages of potential transportation-related projects, how ecological, hydrologic, and structural characteristics of bridges and culverts and their watersheds could adversely affect project schedules and budgets. Factors that are critical to evaluate and incorporate into overall assessments of project risk include basin, land-use, and climatic characteristics; vulnerability to specific events, such as floods; and complicating factors in the watershed, such as endangered species, evacuation routes, and historical sites. A Python script tool has been built for ArcGIS Pro as an automated screening tool that draws on existing geographic information system (GIS) data layers to identify potential risk factors and quantify risk scores for bridges and culverts. This tool can help resource managers quickly evaluate projects, during early planning, in terms of variables that may adversely affect schedules or budgets.

GapMaps GIS Data by Azira uses location data on mobile phones sourced by Azira which is collected from smartphone apps when the users have given their permission to track their location. It can shed light on consumer visitation patterns (“where from” and “where to”), frequency of visits, profiles of consumers and much more.

Businesses can utilise GIS data to answer key questions including: - What is the demographic profile of customers visiting my locations? - What is my primary catchment? And where within that catchment do most of my customers travel from to reach my locations? - What points of interest drive customers to my locations (ie. work, shopping, recreation, hotel or education facilities that are in the area) ? - How far do customers travel to visit my locations? - Where are the potential gaps in my store network for new developments?
- What is the sales impact on an existing store if a new store is opened nearby? - Is my marketing strategy targeted to the right audience? - Where are my competitor's customers coming from?

Mobile Location data provides a range of benefits that make it a valuable GIS Data source for location intelligence services including: - Real-time - Low-cost at high scale - Accurate - Flexible - Non-proprietary - Empirical

Azira have created robust screening methods to evaluate the quality of Mobile location data collected from multiple sources to ensure that their data lake contains only the highest-quality mobile location data.

This includes partnering with trusted location SDK providers that get proper end user consent to track their location when they download an application, can detect device movement/visits and use GPS to determine location co-ordinates.

Data received from partners is put through Azira's data quality algorithm discarding data points that receive a low quality score.

Use cases in Europe will be considered on a case to case basis.

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.

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 Means of Transportation to Work dataset was compiled using information from December 31, 2023 and updated December 12, 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 Means of Transportation to Work table from the 2023 American Community Survey (ACS) 5-year estimates was joined to 2023 tract-level geographies for all 50 States, District of Columbia and Puerto Rico provided by the Census Bureau. A new file was created that combines the demographic variables from the former with the cartographic boundaries of the latter. The national level census tract layer contains data on the number and percentage of commuters (workers 16 years and over) that used various transportation modes to get to work.

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.

INFP and CRMD have recently developed a framework capable of analyzing direct and indirect implications of natural hazards on transportation networks. This is currently embedded into an ArcGIS toolbox entitled Network-risk, which has been successfully tested for Bucharest, contributing to an insightful evaluation of emergency intervention times for ambulances and firefighters, in the case of an earthquake.

You will find in the files two versions of the toolbox: 1 (explained and used in Toma-Danila et al., 2020) and 2 (under review, along with the sample dataset for Bucharest). New improved versions are soon going to be published.