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

Shortest Route Analysis Of Dhaka City Roads Using Various Gis Techniques (Dataset And Sample Outputs)
This dataset falls under the category Public Transport Transport Network Geometries (Geodata).
It contains the following data: This repository is the dataset of the related paper "Shortest Route Analysis of Dhaka City Roads Using Various GIS Techniques".The data presented here are collected and gathered together from several separate locations. All the probable original sources of the dataset are open-source or free to distribute licensed. The dataset has the following items: 1. Road network of Dhaka city. 2. Bus Route network of Dhaka city. 3. Future metro Route network of Dhaka city. 4. All the bus stands in Bangladesh. 5. All planned metro station in Dhaka city. 6. The output of some sample random two points shortest or cheapest path from the related paper.
This dataset was scouted on 2022-02-23 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://data.mendeley.com/datasets/j5b93k2xhk/1\ Please note: This link leads to an external resource. If you experience any issues with its availability, please try again later.

Features of different accessibility analysis methods.

This table contains a list of the participants, or named organizations, of the Social Network Analysis done as part of the Pacific Northwest Coastal Conservation Blueprint which is a component of the Pacific Northwest Coast Landscape Conservation Design. A social network analysis maps out the who, what, and where of conservation collaboration, helping us to think more strategically about conservation at the landscape scale by identifying who entities collaborate with, and the conservation priorities, strategies, capacity needs, strengths, and geographic areas of interest.For more information on the larger Pacific Northwest Coast Landscape Conservation Design project that the Social Network Analysis is a part of please see the project website: http://columbiacoastblueprint.org/

ArcGIS tool and tutorial to convert the shapefiles into network format. The latest version of the tool is available at http://csun.uic.edu/codes/GISF2E.htmlUpdate: we now have added QGIS and python tools. To download them and learn more, visit 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 Telecom Sector Market Size 2025-2029

The GIS in telecom sector market size is valued to increase USD 2.35 billion, at a CAGR of 15.7% from 2024 to 2029. Increased use of GIS for capacity planning will drive the GIS in telecom sector market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 28% growth during the forecast period.
By Product - Software segment was valued at USD 470.60 billion in 2023
By Deployment - On-premises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 256.91 million
Market Future Opportunities: USD 2350.30 million
CAGR from 2024 to 2029: 15.7%

Market Summary

The market is experiencing significant growth as communication companies increasingly adopt Geographic Information Systems (GIS) for network planning and optimization. Core technologies, such as satellite imagery and location-based services, are driving this trend, enabling telecom providers to improve network performance and customer experience. One major application of GIS in the telecom sector is capacity planning, which allows companies to optimize their network infrastructure based on real-time data.
However, the integration of GIS with big data and other advanced technologies presents a communication gap between developers and end-users, requiring a focus on user-friendly interfaces and training programs. Additionally, regulatory compliance and data security remain significant challenges for the market. Despite these hurdles, the opportunities for innovation and improved operational efficiency make the market an exciting and evolving space.

What will be the Size of the GIS In Telecom Sector Market during the forecast period?

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How is the GIS In Telecom Sector Market Segmented ?

The GIS in telecom sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Software
  Data
  Services


Deployment

  On-premises
  Cloud


Application

  Mapping
  Telematics and navigation
  Surveying
  Location based services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Product Insights

The software segment is estimated to witness significant growth during the forecast period.

The global telecom sector's reliance on Geographic Information Systems (GIS) continues to expand, with the market for GIS in telecoms projected to grow significantly. According to recent industry reports, the market for GIS data visualization and spatial data infrastructure in telecoms has experienced a notable increase of 18.7% in the past year. Furthermore, the demand for advanced spatial analysis tools, such as building penetration analysis, geospatial asset management, and work order management systems, has risen by 21.3%. Telecom companies utilize GIS for network performance monitoring, data integration platforms, and network planning. For instance, GIS enables network design, radio frequency interference analysis, route optimization software, mobile network optimization, signal propagation modeling, and service area mapping.

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The Software segment was valued at USD 470.60 billion in 2019 and showed a gradual increase during the forecast period.

Additionally, it plays a crucial role in infrastructure management, location-based services, emergency response planning, maintenance scheduling, and telecom network design. Moreover, the adoption of 3D GIS modeling, LIDAR data processing, and customer location mapping has gained traction, contributing to the market's expansion. The future outlook is promising, with industry experts anticipating a 25.6% increase in the use of GIS for telecom network capacity planning and telecom outage prediction. These trends underscore the continuous evolution of the market and its applications across various sectors.

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Regional Analysis

APAC is estimated to contribute 28% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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In China, the construction of smart cities in Qingdao, Hangzhou, and Xiamen, among others, is driving the demand for Geographic Information Systems (GIS) in various sectors. By 2025, China aims to build more smart cities, leading to significant growth opportunities for GIS companies. Esri Global Inc., a leading player

These CSV files contain data extracted from the “PhD Origin and Current Affiliation of Global GIS Faculty” dataset, filtered by continent. They are prepared for creating network graphs in Gephi, including one global network graph and four continental network graphs. The focus is on faculty relationships between their PhD origin and current affiliations across different continents.

The Intelligent Road Network dataset provided by the Transport Department includes traffic directions, turning restrictions at road junctions, stopping restrictions, on-street parking spaces and other road traffic data for supporting the development of intelligent transport system, fleet management system and car navigation etc. by the public.

Esri China (HK) has prepared this File Geodatabase containing a Network Dataset for the Intelligent Road Network to support Esri GIS users to use the dataset in ArcGIS Pro without going through long configuration steps. Please refer to this guideline to use the Road Network Dataset in ArcGIS Pro for routing analysis. This network dataset has been configured and deployed the following restrictions:

Speed LimitTurnIntersectionTraffic FeaturesPedestrian ZoneTraffic Sign of ProhibitionVehicle RestrictionThe coordinate system of this dataset is Hong Kong 1980 Grid.The objectives of uploading the network dataset to ArcGIS Online platform are to facilitate our Hong Kong ArcGIS users to utilize the data in a spatial ready format and save their data conversion effort.For details about the schema and information about the content and relationship of the data, please refer to the data dictionary provided by Transport Department at https://data.gov.hk/en-data/dataset/hk-td-tis_15-road-network-v2.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.Dataset last updated on: 2021 July

Download In State Plane Projection Here. ** The Street Centerline feature class now follows the NG911/State of Illinois data specifications including a StreetNameAlias table. The download hyperlink above also contains a full network topology for use with the Esri Network Analyst extension ** These street centerlines were developed for a myriad of uses including E-911, as a cartographic base, and for use in spatial analysis. This coverage should include all public and selected private roads within Lake County, Illinois. Roads are initially entered using recorded documents and then later adjusted using current aerial photography. This dataset should satisfy National Map Accuracy Standards for a 1:1200 product. These centerlines have been provided to the United States Census Bureau and were used to conflate the TIGER road features for Lake County. The Census Bureau evaluated these centerlines and, based on field survey of 109 intersections, determined that there is a 95% confidence level that the coordinate positions in the centerline dataset fall within 1.9 meters of their true ground position. The fields PRE_DIR, ST_NAME, ST_TYPE and SUF_DIR are formatted according to United States Postal Service standards. Update Frequency: This dataset is updated on a weekly basis.

The Bridges of Pittsburgh is a highly interdisciplinary and collaborative public-facing project that pays homage both to an innovative, field-defining mathematical problem and to one of the defining features of our city. We proposed to discover how many of Pittsburgh’s 446 bridges could be traversed without crossing the same bridge twice, in the process addressing issues in processing crowdsourced GIS data, performing graph traversal with complex constraints, and using network analysis to compare communities formed by this road network to the historically-defined neighborhoods of Pittsburgh.This ZIP file contains an RStudio project, with package dependencies bundled via packrat (https://rstudio.github.io/packrat/).- The osmar/ directory contains OSM data, our processing code, and outputs used to generate the map at https://bridgesofpittsburgh.net - 2019_final_community_analysis/ contains code and derived datasets for the community analysis portion of the projectwar- The legacy/ directory contains experimental datasets and code from the earliest phase of this project, which were later superseded by the main pipeline in the osmar/ directory.Each directory contains further README.md files documenting their structure.

The Freight Analysis Framework (FAF5) - Network Links dataset was created from 2017 base year data and was published on April 11, 2022 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 FAF (Version 5) Network contains 487,384 link features. All link features are topologically connected to permit network pathbuilding and vehicle assignment using a variety of assignment algorithms. The FAF Link and the FAF Node datasets can be used together to create a network. The link features include all roads represented in prior FAF networks, and all roads in the National Highway System (NHS) and the National Highway Freight Network (NHFN) that are currently open to traffic. Other included links provide connections between intersecting routes, and to select intermodal facilities and all U.S. counties. The network consists of over 588,000 miles of equivalent road mileage. The dataset covers the 48 contiguous States plus the District of Columbia, Alaska, and Hawaii. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529027

The input file contains supply data (based on data from geoportal of piedmont and OSM data) and flood map (based on data from geoportal of piedmont) for the Alessandria area in Italy, detailing both basic and disrupted flood scenarios to be analyzed in GIS software. It includes information on closed bridges during flood events. The output file presents the analysis results for both the basic and disrupted scenarios.

Dataset of variables and results for spatial network analysis of shortest distances on Roman roads between the proxies for the positions of Roman soldiers and the worship of Asclepius, Apollo, Minerva, and Jupiter, and the positions of Roman physicians in the selected provinces of the Roman Empire. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 892604.

The Geographic Information System (GIS) in Telecom market is experiencing steady growth, projected to reach $1099.9 million in 2025, with a Compound Annual Growth Rate (CAGR) of 3.1% from 2025 to 2033. This growth is fueled by several key drivers. The increasing need for efficient network planning and optimization within the telecom sector is a major catalyst. GIS technology enables telecom companies to visualize network infrastructure, identify coverage gaps, and plan for network expansion strategically, optimizing resource allocation and reducing operational costs. Furthermore, the rising adoption of cloud-based GIS solutions offers scalability, flexibility, and cost-effectiveness, attracting a wider range of telecom operators, from SMEs to large enterprises. The integration of GIS with other technologies, such as IoT and big data analytics, further enhances its utility, enabling predictive maintenance, improved customer service, and more accurate network performance monitoring. Competitive pressures are also pushing telecom companies to leverage GIS for improved efficiency and better customer experiences. The market segmentation reveals a strong preference for cloud-based solutions, driven by their inherent advantages in scalability and accessibility. Large enterprises, with their complex network infrastructures and vast data sets, are major adopters of GIS technology. Geographically, North America and Europe currently hold significant market share due to early adoption and advanced technological infrastructure. However, the Asia-Pacific region is expected to witness rapid growth in the coming years, driven by increasing investments in telecom infrastructure and expanding mobile penetration. Challenges for the market include the high initial investment costs associated with implementing GIS systems and the need for skilled professionals to manage and utilize these complex systems. Despite these challenges, the long-term outlook for the GIS in Telecom market remains positive, driven by continuous technological advancements and the increasing reliance on data-driven decision-making within the telecom industry.

Statistical indicators of the networks.

The global GIS in Telecom market is projected to grow from USD 1092.7 million in 2025 to USD 1528.4 million by 2033, at a CAGR of 3.0% during the forecast period. The market is driven by the increasing adoption of GIS technology in the telecom industry to improve network planning, optimization, and management. The growing need for accurate and up-to-date geospatial data for telecom network management is also fueling the market growth. The software segment holds the largest market share and is expected to continue to dominate during the forecast period. The increasing adoption of GIS software for network planning, design, and optimization is driving the growth of this segment. The data segment is also expected to witness significant growth due to the increasing demand for geospatial data for various telecom applications. The services segment is projected to grow at a steady pace due to the rising need for consulting and support services from GIS vendors. The large enterprise segment holds the largest market share due to the high adoption of GIS technology by large telecom operators to manage their complex networks. GIS (Geographic Information Systems) plays a crucial role in the telecommunications industry, enabling network optimization, asset management, and customer service enhancements.

This road network dataset was created from data extracted from OpenStreetMap (OSM) across the geographic area of Australia on 05 August 2020. Its purpose is to represent motor-vehicle traversable public roads within Australia. Note, however, as the original dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. This road network has been topologically corrected for the purposes of network analysis for motor vehicles. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 05 August 2020. AURIN has filtered the original data and omitted features to present the topologically correct, motor-vehicle traversable road network.

These scripts prepare input data and complete the Civic Address Layers Analysis and GIS 911 Synchronization Analysis in support of Next Generation 9-1-1 Deployment in the Commonwealth of Virginia.Report Card Tools v1.1 December 2020Report Card Tools v1.0 March 2019See here for the user guide and other required resources.Additional resources and recommendations on GIS related topics are available on the VGIN 9-1-1 & GIS page.

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data. See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.

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.