72 datasets found
  1. f

    Features of different accessibility analysis methods.

    • figshare.com
    • plos.figshare.com
    xls
    Updated Sep 14, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kairan Yang; Yujun Xie; Hengtao Guo (2023). Features of different accessibility analysis methods. [Dataset]. http://doi.org/10.1371/journal.pone.0291235.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Sep 14, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kairan Yang; Yujun Xie; Hengtao Guo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Features of different accessibility analysis methods.

  2. Road Network Data of Hong Kong

    • hub.arcgis.com
    • opendata.esrichina.hk
    Updated Aug 22, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri China (Hong Kong) Ltd. (2018). Road Network Data of Hong Kong [Dataset]. https://hub.arcgis.com/datasets/188a2dfc78bd44d19fa99edfe87b20e7
    Explore at:
    Dataset updated
    Aug 22, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri China (Hong Kong) Ltd.
    Area covered
    Hong Kong
    Description

    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

  3. Geographic Information System (GIS) In Telecom Sector Market Analysis APAC,...

    • technavio.com
    Updated Jun 15, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Technavio (2024). Geographic Information System (GIS) In Telecom Sector Market Analysis APAC, North America, Europe, South America, Middle East and Africa - China, US, UK, Canada, Italy - Size and Forecast 2024-2028 [Dataset]. https://www.technavio.com/report/gis-market-in-telecom-sector-industry-analysis
    Explore at:
    Dataset updated
    Jun 15, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global, United Kingdom, United States
    Description

    Snapshot img

    GIS In Telecom Sector Market Size 2024-2028

    The GIS in telecom sector market size is forecast to increase by USD 1.91 billion at a CAGR of 14.68% between 2023 and 2028.

    Geographic Information Systems (GIS) have gained significant traction In the telecom sector due to the increasing adoption of advanced technologies such as big data, sensors, drones, and LiDAR. The use of GIS enables telecom companies to effectively manage and analyze large volumes of digital data, including satellite and GPS information, to optimize infrastructure monitoring and antenna placement. In the context of smart cities, GIS plays a crucial role in enabling efficient communication between developers and end-users by providing real-time data on construction progress and infrastructure status. Moreover, the integration of LiDAR technology with drones offers enhanced capabilities for surveying and mapping telecom infrastructure, leading to improved accuracy and efficiency.
    However, the implementation of GIS In the telecom sector also presents challenges, including data security concerns and the need for servers and computers to handle the large volumes of data generated by these technologies. In summary, the telecom sector's growing reliance on digital technologies such as GIS, big data, sensors, drones, and LiDAR is driving market growth, while the need for effective data management and security solutions presents challenges that must be addressed.
    

    What will be the Size of the GIS In Telecom Sector Market During the Forecast Period?

    Request Free Sample

    The Geographic Information System (GIS) market In the telecom sector is experiencing significant growth due to the increasing demand for electronic information and visual representation of data in various industries. This market encompasses a range of hardware and software solutions, including GNSS/GPS antennas, Lidar, GIS collectors, total stations, imaging sensors, and more. Major industries such as agriculture, oil & gas, architecture, and infrastructure monitoring are leveraging GIS technology for data analysis and decision-making. The adoption rate of GIS In the telecom sector is driven by the need for efficient data management and analysis, as well as the integration of real-time data from various sources.
    Data formats and sources vary widely, from satellite and aerial imagery to ground-based sensors and IoT devices. The market is also witnessing innovation from startups and established players, leading to advancements in data processing capabilities and integration with other technologies like 5G networks and AI. Applications of GIS In the telecom sector include smart urban planning, smart utilities, and smart public works, among others.
    

    How is this GIS In Telecom Sector Industry segmented and which is the largest segment?

    The GIS in telecom sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

    Product
    
      Software
      Data
      Services
    
    
    Deployment
    
      On-premises
      Cloud
    
    
    Geography
    
      APAC
    
        China
    
    
      North America
    
        Canada
        US
    
    
      Europe
    
        UK
        Italy
    
    
      South America
    
    
    
      Middle East and Africa
    

    By Product Insights

    The software segment is estimated to witness significant growth during the forecast period. The telecom sector's Global GIS market encompasses software solutions for desktops, mobiles, cloud, and servers, along with developers' platforms. companies provide industry-specific GIS software, expanding the growth potential of this segment. Telecom companies heavily utilize intelligent maps generated by GIS for informed decisions on capacity planning and enhancements, such as improved service and next-generation networks. This drives significant growth In the software segment. Commercial entities offer open-source GIS software to counteract the threat of counterfeit products.
    GIS technologies are integral to telecom network management, spatial data analysis, infrastructure planning, location-based services, network coverage mapping, data visualization, asset management, real-time network monitoring, design, wireless network mapping, integration, maintenance, optimization, and geospatial intelligence. Key applications include 5G network planning, network visualization, outage management, geolocation, mobile network optimization, and smart infrastructure planning. The GIS industry caters to major industries, including agriculture, oil & gas, architecture, engineering, construction, mining, utilities, retail, healthcare, government, and smart city planning. GIS solutions facilitate real-time data management, spatial information, and non-spatial information, offering enterprise solutions and transportation applications.
    

    Get a glance at the market report of share of variou

  4. Key cities based on information diffusing.

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yakun He; Jiadong Jiang; Shuo Li (2023). Key cities based on information diffusing. [Dataset]. http://doi.org/10.1371/journal.pone.0248037.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Yakun He; Jiadong Jiang; Shuo Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Key cities based on information diffusing.

  5. Shortest Route Analysis Of Dhaka City Roads Using Various Gis Techniques...

    • hub.tumidata.org
    url, zip
    Updated Jun 4, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TUMI (2024). Shortest Route Analysis Of Dhaka City Roads Using Various Gis Techniques (Dataset And Sample Outputs) [Dataset]. https://hub.tumidata.org/dataset/shortest_route_analysis_of_dhaka_city_roads_using_various_gis_techniques_dataset_and_sample_outputs_
    Explore at:
    url, zip(94209013)Available download formats
    Dataset updated
    Jun 4, 2024
    Dataset provided by
    Tumi Inc.http://www.tumi.com/
    Area covered
    Dhaka
    Description

    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\

  6. FWS R1 PNW Coastal Conservation Blueprint: Social Network Analysis Survey...

    • gis-fws.opendata.arcgis.com
    • hub.arcgis.com
    Updated Mar 22, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Fish & Wildlife Service (2018). FWS R1 PNW Coastal Conservation Blueprint: Social Network Analysis Survey Participants [Dataset]. https://gis-fws.opendata.arcgis.com/datasets/fws-r1-pnw-coastal-conservation-blueprint-social-network-analysis-survey-participants
    Explore at:
    Dataset updated
    Mar 22, 2018
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Authors
    U.S. Fish & Wildlife Service
    Description

    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/

  7. Top 10 circulation paths (according to the number of circulation paths).

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yakun He; Jiadong Jiang; Shuo Li (2023). Top 10 circulation paths (according to the number of circulation paths). [Dataset]. http://doi.org/10.1371/journal.pone.0248037.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Yakun He; Jiadong Jiang; Shuo Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Top 10 circulation paths (according to the number of circulation paths).

  8. Pedestrian Network Data of Hong Kong

    • hub.arcgis.com
    Updated Mar 17, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri China (Hong Kong) Ltd. (2021). Pedestrian Network Data of Hong Kong [Dataset]. https://hub.arcgis.com/datasets/48e295256fd84032a87b27000cea35cd
    Explore at:
    Dataset updated
    Mar 17, 2021
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri China (Hong Kong) Ltd.
    Area covered
    Description

    This data contains general information about Pedestrian Network in Hong Kong. Pedestrian Network is a set of 3D line features derived from road features and road furniture from Lands Department and Transport Department. A number of attributes are associated with the pedestrian network such as spatially related street names. Besides, the pedestrian network includes information like wheelchair accessibility and obstacles to facilitate the digital inclusion for the needy. Please refer to this video to learn how to use 3D Pedestrian Network Dataset in ArcGIS Pro to facilitate your transportation analysis.The data was provided in the formats of JSON, GML and GDB by Lands Department and downloaded via GEODATA.GOV.HK website.

    The original data files were processed and converted into an Esri file geodatabase. Wheelchair accessibility, escalator/lift, staircase walking speed and street gradient were used to create and build a network dataset in order to demonstrate basic functions for pedestrian network and routing analysis in ArcMap and ArcGIS Pro. There are other tables and feature classes in the file geodatabase but they are not included in the network dataset, users have to consider the use of information based on their requirements and make necessary configurations. The 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 Lands Department at https://geodata.gov.hk/gs/download-datadict/201eaaee-47d6-42d0-ac81-19a430f63952.

    For details about the data, source format and terms of conditions of usage, please refer to the website of GEODATA STORE at https://geodata.gov.hk.Dataset last updated on: 2022 Oct

  9. d

    Replication data for: The spread of the cult of Asclepius in the context of...

    • search.dataone.org
    • dataverse.azure.uit.no
    • +1more
    Updated Jan 5, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Glomb, Tomas (2024). Replication data for: The spread of the cult of Asclepius in the context of the Roman army benefited from the presence of physicians: A spatial proximity analysis [Dataset]. https://search.dataone.org/view/sha256%3A7332b74ace83f428ef99914070f955d44f0cdbd6448514f2fb8bcec0be9c8cb7
    Explore at:
    Dataset updated
    Jan 5, 2024
    Dataset provided by
    DataverseNO
    Authors
    Glomb, Tomas
    Description

    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.

  10. f

    Summary of the key cities identified by various indicators.

    • plos.figshare.com
    xls
    Updated Jun 11, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yakun He; Jiadong Jiang; Shuo Li (2023). Summary of the key cities identified by various indicators. [Dataset]. http://doi.org/10.1371/journal.pone.0248037.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Yakun He; Jiadong Jiang; Shuo Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summary of the key cities identified by various indicators.

  11. a

    Network Screening Risk Safety Analysis

    • geo-massdot.opendata.arcgis.com
    • gis.data.mass.gov
    • +2more
    Updated May 9, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Massachusetts geoDOT (2023). Network Screening Risk Safety Analysis [Dataset]. https://geo-massdot.opendata.arcgis.com/maps/1fa76247846942c2af2e9e00553b00f4
    Explore at:
    Dataset updated
    May 9, 2023
    Dataset authored and provided by
    Massachusetts geoDOT
    Area covered
    Description
  12. A

    ‘GIS area of Natura 2000 network’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 14, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘GIS area of Natura 2000 network’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-europa-eu-gis-area-of-natura-2000-network-5ab0/612b8657/?iid=005-309&v=presentation
    Explore at:
    Dataset updated
    Jan 14, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘GIS area of Natura 2000 network’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/dat-110-en on 14 January 2022.

    --- Dataset description provided by original source is as follows ---

    GIS area of Natura 2000 network calculated on the data set versions published end 2009 onwards

    --- Original source retains full ownership of the source dataset ---

  13. a

    OpenStreetMap - Road Network (Australia) 2020 - Dataset - AURIN

    • data.aurin.org.au
    Updated Jun 28, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2023). OpenStreetMap - Road Network (Australia) 2020 - Dataset - AURIN [Dataset]. https://data.aurin.org.au/dataset/osm-osm-roads-2020-na
    Explore at:
    Dataset updated
    Jun 28, 2023
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    Australia
    Description

    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.

  14. a

    Point

    • scwp-hub-lacounty.hub.arcgis.com
    • geohub.oregon.gov
    • +9more
    Updated Dec 31, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    County of Los Angeles (2024). Point [Dataset]. https://scwp-hub-lacounty.hub.arcgis.com/datasets/point-1
    Explore at:
    Dataset updated
    Dec 31, 2024
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    South Pacific Ocean, Pacific Ocean
    Description

    Abstract: The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee. Use the metadata link, http://nhdgeo.usgs.gov/metadata/nhd_high.htm, for additional information. Purpose: The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all.

  15. e

    Geodatabase for the Baltimore Ecosystem Study Spatial Data

    • portal.edirepository.org
    • search.dataone.org
    application/vnd.rar
    Updated May 4, 2012
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jarlath O'Neal-Dunne; Morgan Grove (2012). Geodatabase for the Baltimore Ecosystem Study Spatial Data [Dataset]. http://doi.org/10.6073/pasta/377da686246f06554f7e517de596cd2b
    Explore at:
    application/vnd.rar(29574980 kilobyte)Available download formats
    Dataset updated
    May 4, 2012
    Dataset provided by
    EDI
    Authors
    Jarlath O'Neal-Dunne; Morgan Grove
    Time period covered
    Jan 1, 1999 - Jun 1, 2014
    Area covered
    Description

    The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making.

       BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions.
    
    
       Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself.
    
    
       For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise.
    
    
       Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. 
    
    
       This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery.
    
    
       See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt
    
    
       See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt
    
  16. National Hydrography Dataset Plus Version 2.1

    • geodata.colorado.gov
    Updated Aug 16, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Esri (2022). National Hydrography Dataset Plus Version 2.1 [Dataset]. https://geodata.colorado.gov/maps/4bd9b6892530404abfe13645fcb5099a
    Explore at:
    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses. For more information on the NHDPlus dataset see the NHDPlus v2 User Guide.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territories not including Alaska.Coordinate System: Web Mercator Auxiliary Sphere Extent: The United States not including Alaska, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Number of Features: 3,035,617 flowlines, 473,936 waterbodies, 16,658 sinksSource: EPA and USGSPublication Date: March 13, 2019Prior to publication, the NHDPlus network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the NHDPlus Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, On or Off Network (flowlines only), Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original NHDPlus dataset. No data values -9999 and -9998 were converted to Null values for many of the flowline fields.What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute. Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map. Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

  17. Brazil Geospatial Analytics Market Size & Share Analysis - Industry Research...

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Mordor Intelligence, Brazil Geospatial Analytics Market Size & Share Analysis - Industry Research Report - Growth Trends [Dataset]. https://www.mordorintelligence.com/industry-reports/brazil-geospatial-analytics-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset authored and provided by
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    Brazil
    Description

    The Brazil Geospatial Analytics Market is Segmented by Type (Surface Analysis, Network Analysis, and Geovisualization), End-User Vertical (Agriculture, Utility and Communication, Defence and Intelligence, Government, Mining and Natural Resources, Automotive and Transportation, Healthcare, Real Estate and Construction, and Other End-Users). The Market Sizes and Forecasts are Provided in Terms of Value in USD for all the Above Segments.

  18. G

    GIS in the Telecom Sector Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Feb 3, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Pro Market Reports (2025). GIS in the Telecom Sector Market Report [Dataset]. https://www.promarketreports.com/reports/gis-in-the-telecom-sector-market-18018
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Feb 3, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global GIS in the Telecom Sector Market size was valued at USD 4.55 billion in 2025 and is projected to reach USD 9.41 billion by 2033, exhibiting a CAGR of 6.77% during the forecast period (2025-2033). The market's growth can be attributed to the increasing adoption of GIS technologies by telecom service providers to enhance network planning, optimization, and customer experience. Key drivers of the market include the growing need for efficient network management and infrastructure planning, the increasing use of location-based services by telecom users, and the government initiatives to improve infrastructure and provide better connectivity. The market is segmented by technology, deployment model, application, end user, data type, and region. North America is the largest market for GIS in the Telecom Sector, followed by Europe and Asia-Pacific. Key drivers for this market are: 1. Network optimization and planning 2. 5G deployment support 3. Location-based services expansion 4. Real-time infrastructure management 5. Data analytics integration. Potential restraints include: increased demand for real-time data, growing investment in network infrastructure; rise in location-based services; & need for enhanced operational efficiency & integration of advanced analytics tools.

  19. c

    Global GIS in Telecom Sector market size is USD XX million in 2024.

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Jan 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Cognitive Market Research (2025). Global GIS in Telecom Sector market size is USD XX million in 2024. [Dataset]. https://www.cognitivemarketresearch.com/gis-in-telecom-sector-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    According to Cognitive Market Research, the global GIS in Telecom Sector market size is USD XX million in 2024. It will expand at a compound annual growth rate (CAGR) of 15.00% from 2024 to 2031.

    North America held the major market share for more than 40% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 13.2% from 2024 to 2031.
    Europe accounted for a market share of over 30% of the global revenue with a market size of USD XX million.
    Asia Pacific held a market share of around 23% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 17.0% from 2024 to 2031.
    Latin America had a market share for more than 5% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 14.4% from 2024 to 2031.
    Middle East and Africa hada market share of around 2% of the global revenue and was estimated at a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 14.7% from 2024 to 2031.
    Large enterprises dominate the GIS in telecom sector market as primary end-users. These companies possess extensive telecom infrastructure and resources, making them ideal candidates for comprehensive GIS solutions.
    

    Market Dynamics of GIS in Telecom Sector Market

    Key Drivers for GIS in Telecom Sector Market

    Increasing Demand for Efficient Network Planning and Optimization Solutions to Increase the Demand Globally

    One of the primary drivers of the GIS in the telecom sector market is the escalating need for efficient network planning and optimization solutions. As telecom operators strive to enhance their network coverage and capacity, GIS technology plays a crucial role in providing detailed spatial analysis and visualization. This enables telecom companies to plan and optimize their networks more accurately, reducing operational costs and improving service quality. The capability of GIS to integrate various data layers, such as demographic, topographic, and network performance data, allows for precise decision-making and strategic deployment of resources, thereby driving its adoption in the telecom sector.

    Expansion of Telecom Infrastructure in Emerging Markets to Propel Market Growth

    Another significant driver is the expansion of telecom infrastructure in emerging markets. As countries in regions such as Asia-Pacific, Latin America, and Africa experience rapid economic growth, there is a substantial increase in the deployment of telecom networks to meet the rising demand for connectivity. GIS technology is instrumental in these large-scale infrastructure projects, providing essential tools for site selection, route optimization, and infrastructure management. By enabling telecom companies to efficiently plan and deploy their networks in challenging and diverse geographical landscapes, GIS helps accelerate the rollout of telecom services, enhancing connectivity and fostering economic development in these regions.

    Restraint Factor for the GIS in Telecom Sector Market

    High Initial Investment and Implementation Costs t to Limit the Sales

    A significant restraint in the GIS in telecom sector market is the high initial investment and implementation costs. Integrating GIS technology into telecom operations requires substantial financial resources, including the cost of sophisticated software, high-performance hardware, and specialized personnel. Additionally, the implementation process can be complex and time-consuming, often necessitating significant changes to existing workflows and systems. These factors can be particularly challenging for smaller telecom operators and those in emerging markets, potentially hindering the widespread adoption of GIS solutions despite their long-term benefits. This financial barrier remains a critical challenge for the market's growth.

    Impact of Covid-19 on the GIS in Telecom Sector Market

    The COVID-19 pandemic has had a profound impact on the GIS in telecom sector market, accelerating the adoption of digital solutions and reshaping operational strategies. With the surge in remote work, online education, and digital services, the demand for reliable and expansive telecom networks has skyrocketed. GIS technology has become indispensable for telecom companies in managing this increased demand, aiding in network optimization ...

  20. d

    National Hydrography Dataset (NHD) Water Bodies - Medium Resolution -...

    • catalog.data.gov
    • datadiscoverystudio.org
    Updated Sep 2, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Under Secretary / Management (2021). National Hydrography Dataset (NHD) Water Bodies - Medium Resolution - NHD_CONUS_HI_Hydrography [Dataset]. https://catalog.data.gov/sr/dataset/national-hydrography-dataset-nhd-water-bodies-medium-resolution-nhd-conus-hi-hydrography
    Explore at:
    Dataset updated
    Sep 2, 2021
    Dataset provided by
    Under Secretary / Management
    Description

    The National Hydrography Dataset combines elements of the DLG and RF3spatial accuracy and comprehensiveness from the DLG and network relationships, names, and a unique identifier (reach code) for surface water features from RF3. The NHD supersedes DLG and RF3 by incorporating them, not by replacing them. Users of DLG and RF3 will find the National Hydrography Dataset both familiar and greatly expanded and refined. The NHD provides a national framework for assigning reach addresses to water-related entities such as industrial dischargers, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network in a manner similar to street addresses. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities and any associated information about them can be analyzed using software tools ranging from spreadsheets to Geographic Information Systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use, and population, to help better understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addresses and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all. The National Hydrography Dataset is designed to provide comprehensive coverage of hydrologic data for the US. While initially based on 1:100,000-scale data, the NHD is designed to incorporate and encourage the development of higher-resolution data required by many users. It will facilitate the improved integration of water-related data in support of the application requirements of a growing national user community and will enable shared maintenance and enhancement.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Kairan Yang; Yujun Xie; Hengtao Guo (2023). Features of different accessibility analysis methods. [Dataset]. http://doi.org/10.1371/journal.pone.0291235.t001

Features of different accessibility analysis methods.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Sep 14, 2023
Dataset provided by
PLOS ONE
Authors
Kairan Yang; Yujun Xie; Hengtao Guo
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Features of different accessibility analysis methods.

Search
Clear search
Close search
Google apps
Main menu