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TwitterGIS Maps, Transportation Data, and Reports for all modes of travel throughout Massachusetts.
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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.
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The size of the GIS in Transportation market was valued at USD XXX million in 2023 and is projected to reach USD XXX million by 2032, with an expected CAGR of XX% during the forecast period.
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Check Market Research Intellect's GIS In Transportation Market Report, pegged at USD 6.2 billion in 2024 and projected to reach USD 12.3 billion by 2033, advancing with a CAGR of 8.5% (2026-2033).Explore factors such as rising applications, technological shifts, and industry leaders.
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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
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GIS in Transportation Market size was valued at USD 13250.25 million in 2024 and the revenue is expected to grow at a CAGR of 9.15% from 2025 to 2032
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TwitterHEPGIS 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.
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TwitterThe FDOT GIS Roads with Median Types feature class provides spatial information on Florida Median Types distinguishing between lawn, paved, painted, and curbed medians. It also notes where a fence, guardrail, or barrier wall divides the two sides of a divided road. A median is defined as a barrier or other physical separation between two lanes of traffic traveling in opposite directions, which can either be raised, painted, or paved. This information is required for all functionally classified roadways On or Off the SHS. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 11/08/2025.For more details please review the FDOT RCI Handbook Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/median_type.zip
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TwitterCook County, Illinois Department of Transportation and Highways expanded GIS data for highway road assets including striping, curbs, raised medians, linear reference system (LRS), mile markers, mileposts, traffic signals, construction projects, bridges and survey monumentation.
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TwitterHEPGIS 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.
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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.
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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.
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TwitterTIGER 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.
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TwitterA style file containing a collection of realistic 3D transportation symbols.
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TwitterHEPGIS 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.
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
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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 ...
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Twitterhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/CKYCHUhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/CKYCHU
The GIS data maintained by HPPM includes information on buildings and grounds related to Harvard University. Our "standard" base layers are available to Harvard affiliates and their service providers (for example, architects) working on Harvard projects in AutoCAD DWG, ESRI SHP or File Geodatabase format. Additional datasets are sometimes available by special arrangement. http://home.hppm.harvard.edu/pages/gis-data-layers
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The Geographic Information System (GIS) Solutions market is experiencing robust growth, driven by increasing adoption across diverse sectors. The market, estimated at $15 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a Compound Annual Growth Rate (CAGR) of approximately 8%. This growth is attributed to several key factors. Firstly, the rising need for precise spatial data analysis and visualization across industries like agriculture (precision farming), oil & gas (resource exploration and management), and construction (infrastructure planning and development) is driving demand. Secondly, advancements in GIS software and services, including cloud-based solutions and AI-powered analytics, are enhancing efficiency and accessibility. Thirdly, government initiatives promoting smart cities and infrastructure development are further boosting market expansion. The market is segmented by application (Agriculture, Oil & Gas, AEC, Transportation, Mining, Government, Healthcare, Others) and type (Software, Services), with software solutions currently holding a larger market share due to increasing digitization and data-driven decision-making. North America and Europe are currently the leading regional markets, benefiting from established infrastructure and high technology adoption rates, but Asia-Pacific is poised for significant growth driven by rapid urbanization and infrastructure development. Despite the promising growth trajectory, certain challenges remain. High initial investment costs for GIS software and implementation can be a barrier to entry for smaller businesses. Furthermore, the need for skilled professionals to effectively utilize and manage GIS data poses a considerable constraint. However, the ongoing development of user-friendly interfaces and accessible training programs is mitigating this issue. The competitive landscape is characterized by a mix of established players like ESRI, Hexagon, and Pitney Bowes, alongside emerging technology providers. These companies are actively investing in R&D and strategic partnerships to maintain their competitive edge and capitalize on the market's expansion. The long-term outlook for the GIS solutions market remains positive, with continuous innovation and expanding applications across various sectors paving the way for sustained growth throughout the forecast period.
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TwitterGapMaps 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.
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TwitterDetailed street center lines for Baltimore City. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. This dataset depicts the linear boundaries for street and paved areas in Baltimore City and has an extremely high degree of positional accuracy. For the best available transportation data use the Roads_GDT_MSA dataset.
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.
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.
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TwitterGIS Maps, Transportation Data, and Reports for all modes of travel throughout Massachusetts.