100+ datasets found
  1. n

    Using GPS and GIS

    • library.ncge.org
    Updated Jul 27, 2021
    + more versions
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    NCGE (2021). Using GPS and GIS [Dataset]. https://library.ncge.org/documents/50b7245a36114c4387e4327782030633
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    Dataset updated
    Jul 27, 2021
    Dataset authored and provided by
    NCGE
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Author: A Lisson, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8Resource type: lessonSubject topic(s): gis, geographic thinkingRegion: united statesStandards: Minnesota Social Studies Standards

    Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

    1. Explain the difference between two types of geospatial technologies - GPS and GIS.
    2. Develop basic skills to effectively manipulate and use GPS receivers and ArcGIS software.
    3. Explain uses of GPS and GIS.Summary: Students use GPS coordinates to discover geocaches at a local park, and they use ArcGIS to layer maps about the park. Frontenac State park is the example, but any park or area (including school grounds) could be used. Students also investigate careers that use GIS.
  2. M

    DNRGPS

    • gisdata.mn.gov
    • data.wu.ac.at
    windows_app
    Updated Sep 7, 2022
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    Natural Resources Department (2022). DNRGPS [Dataset]. https://gisdata.mn.gov/dataset/dnrgps
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    windows_appAvailable download formats
    Dataset updated
    Sep 7, 2022
    Dataset provided by
    Natural Resources Department
    Description

    DNRGPS is an update to the popular DNRGarmin application. DNRGPS and its predecessor were built to transfer data between Garmin handheld GPS receivers and GIS software.

    DNRGPS was released as Open Source software with the intention that the GPS user community will become stewards of the application, initiating future modifications and enhancements.

    DNRGPS does not require installation. Simply run the application .exe

    See the DNRGPS application documentation for more details.

    Compatible with: Windows (XP, 7, 8, 10, and 11), ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

    Limited Compatibility: Interactions with ArcMap layer files and ArcMap graphics are no longer supported. Instead use shapefile or geodatabase.

    Prerequisite: .NET 4 Framework

    DNR Data and Software License Agreement

    Subscribe to the DNRGPS announcement list to be notified of upgrades or updates.

  3. G

    GIS Data Collector Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Mar 22, 2025
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    Market Report Analytics (2025). GIS Data Collector Report [Dataset]. https://www.marketreportanalytics.com/reports/gis-data-collector-21401
    Explore at:
    ppt, pdf, docAvailable download formats
    Dataset updated
    Mar 22, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

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

    The global GIS data collector market is experiencing robust growth, driven by increasing adoption of precision agriculture, expanding infrastructure development projects, and the rising demand for accurate geospatial data across various industries. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching approximately $4.2 billion by 2033. Key drivers include the increasing availability of affordable and high-precision GPS technology, coupled with advancements in data processing and cloud-based solutions. The integration of GIS data collectors with other technologies, such as drones and IoT sensors, is further fueling market expansion. The demand for high-precision GIS data collectors is particularly strong in sectors like surveying, mapping, and construction, where accuracy is paramount. While the market faces challenges such as high initial investment costs and the need for specialized expertise, the overall growth trajectory remains positive. The market is segmented by application (agriculture, industrial, forestry, and others) and by type (general precision and high precision). North America and Europe currently hold significant market shares, but the Asia-Pacific region is anticipated to experience rapid growth in the coming years due to substantial infrastructure development and increasing government investments in geospatial technologies. The competitive landscape is characterized by both established players like Trimble, Garmin, and Hexagon (Leica Geosystems) and emerging companies offering innovative solutions. These companies are constantly innovating, integrating advanced technologies like AI and machine learning to enhance data collection and analysis capabilities. This competition is driving down prices and improving product quality, benefiting end-users. The increasing use of mobile GIS and cloud-based data management solutions is also transforming the industry, making data collection and analysis more accessible and efficient. Future growth will be largely influenced by the advancement of 5G networks, enabling faster data transmission and real-time applications, and the increasing adoption of automation and AI in data processing workflows. Furthermore, government regulations promoting the use of accurate geospatial data for sustainable development and environmental monitoring are creating new opportunities for the market’s expansion.

  4. Gis Data Collector Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Gis Data Collector Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/gis-data-collector-market
    Explore at:
    pdf, pptx, csvAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    GIS Data Collector Market Outlook



    The global GIS Data Collector market size is anticipated to grow from USD 4.5 billion in 2023 to approximately USD 12.3 billion by 2032, at a compound annual growth rate (CAGR) of 11.6%. The growth of this market is largely driven by the increasing adoption of GIS technology across various industries, advances in technology, and the need for effective spatial data management.



    An important factor contributing to the growth of the GIS Data Collector market is the rising demand for geospatial information across different sectors such as agriculture, construction, and transportation. The integration of advanced technologies like IoT and AI with GIS systems enables the collection and analysis of real-time data, which is crucial for effective decision-making. The increasing awareness about the benefits of GIS technology and the growing need for efficient land management are also fuelling market growth.



    The government sector plays a significant role in the expansion of the GIS Data Collector market. Governments worldwide are investing heavily in GIS technology for urban planning, disaster management, and environmental monitoring. These investments are driven by the need for accurate and timely spatial data to address critical issues such as climate change, urbanization, and resource management. Moreover, regulatory policies mandating the use of GIS technology for infrastructure development and environmental conservation are further propelling market growth.



    Another major growth factor in the GIS Data Collector market is the continuous technological advancements in GIS software and hardware. The development of user-friendly and cost-effective GIS solutions has made it easier for organizations to adopt and integrate GIS technology into their operations. Additionally, the proliferation of mobile GIS applications has enabled field data collection in remote areas, thus expanding the scope of GIS technology. The advent of cloud computing has further revolutionized the GIS market by offering scalable and flexible solutions for spatial data management.



    Regionally, North America holds the largest share of the GIS Data Collector market, driven by the presence of key market players, advanced technological infrastructure, and high adoption rates of GIS technology across various industries. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, primarily due to rapid urbanization, government initiatives promoting GIS adoption, and increasing investments in smart city projects. Other regions such as Europe, Latin America, and the Middle East & Africa are also experiencing significant growth in the GIS Data Collector market, thanks to increasing awareness and adoption of GIS technology.



    The role of a GPS Field Controller is becoming increasingly pivotal in the GIS Data Collector market. These devices are essential for ensuring that data collected in the field is accurate and reliable. By providing real-time positioning data, GPS Field Controllers enable precise mapping and spatial analysis, which are critical for applications such as urban planning, agriculture, and transportation. The integration of GPS technology with GIS systems allows for seamless data synchronization and enhances the efficiency of data collection processes. As the demand for real-time spatial data continues to grow, the importance of GPS Field Controllers in the GIS ecosystem is expected to rise, driving further innovations and advancements in this segment.



    Component Analysis



    The GIS Data Collector market is segmented by component into hardware, software, and services. Each of these components plays a crucial role in the overall functionality and effectiveness of GIS systems. The hardware segment includes devices such as GPS units, laser rangefinders, and mobile GIS devices used for field data collection. The software segment encompasses various GIS applications and platforms used for data analysis, mapping, and visualization. The services segment includes consulting, training, maintenance, and support services provided by GIS vendors and solution providers.



    In the hardware segment, the demand for advanced GPS units and mobile GIS devices is increasing, driven by the need for accurate and real-time spatial data collection. These devices are equipped with high-precision sensors and advanced features such as real-time kinematic (RTK) positioning, which enhance

  5. d

    Data from: GIS database

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Win, Nang Tin (2023). GIS database [Dataset]. http://doi.org/10.7910/DVN/TV7J27
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Win, Nang Tin
    Time period covered
    Oct 1, 2020 - Sep 30, 2022
    Description

    It is about updating to GIS information database, Decision Support Tool (DST) in collaboration with IWMI. With the support of the Fish for Livelihoods field team and IPs (MFF, BRAC Myanmar, PACT Myanmar, and KMSS) staff, collection of Global Positioning System GPS location data for year-1 (2019-20) 1,167 SSA farmer ponds, and year-2 (2020-21) 1,485 SSA farmer ponds were completed with different GPS mobile applications: My GPS Coordinates, GPS Status & Toolbox, GPS Essentials, Smart GPS Coordinates Locator and GPS Coordinates. The Soil and Water Assessment Tool (SWAT) model that integrates climate change analysis with water availability will provide an important tool informing decisions on scaling pond adoption. It can also contribute to a Decision Support Tool to better target pond scaling. GIS Data also contribute to identify the location point of the F4L SSA farmers ponds on the Myanmar Map by fiscal year from 1 to 5.

  6. e

    Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot...

    • knb.ecoinformatics.org
    • search.dataone.org
    • +1more
    Updated Jun 26, 2023
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    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers (2023). Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA [Dataset]. http://doi.org/10.15485/1804896
    Explore at:
    Dataset updated
    Jun 26, 2023
    Dataset provided by
    ESS-DIVE
    Authors
    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers
    Time period covered
    Jan 1, 2008 - Jan 1, 2012
    Area covered
    Description

    This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

  7. GIS data

    • figshare.com
    txt
    Updated Jan 19, 2016
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    Andrew Thomas (2016). GIS data [Dataset]. http://doi.org/10.6084/m9.figshare.1101470.v1
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    txtAvailable download formats
    Dataset updated
    Jan 19, 2016
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Andrew Thomas
    License

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

    Description

    Geo-referenced datasets.

  8. Geographic Information System GIS Tools Market Report | Global Forecast From...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 12, 2024
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    Dataintelo (2024). Geographic Information System GIS Tools Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-geographic-information-system-gis-tools-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Sep 12, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Geographic Information System (GIS) Tools Market Outlook



    The global Geographic Information System (GIS) tools market size was valued at approximately USD 10.8 billion in 2023, and it is projected to reach USD 21.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2032. The increasing demand for spatial data analytics and the rising adoption of GIS tools across various industries are significant growth factors propelling the market forward.



    One of the primary growth factors for the GIS tools market is the surging demand for spatial data analytics. Spatial data plays a critical role in numerous sectors, including urban planning, environmental monitoring, disaster management, and natural resource exploration. The ability to visualize and analyze spatial data provides organizations with valuable insights, enabling them to make informed decisions. Advances in technology, such as the integration of artificial intelligence (AI) and machine learning (ML) with GIS, are enhancing the capabilities of these tools, further driving market growth.



    Moreover, the increasing adoption of GIS tools in the construction and agriculture sectors is fueling market expansion. In construction, GIS tools are used for site selection, route planning, and resource management, enhancing operational efficiency and reducing costs. Similarly, in agriculture, GIS tools aid in precision farming, crop monitoring, and soil analysis, leading to improved crop yields and sustainable farming practices. The ability of GIS tools to provide real-time data and analytics is particularly beneficial in these industries, contributing to their widespread adoption.



    The growing importance of location-based services (LBS) in various applications is another key driver for the GIS tools market. LBS are extensively used in navigation, logistics, and transportation, providing real-time location information and route optimization. The proliferation of smartphones and the development of advanced GPS technologies have significantly increased the demand for LBS, thereby boosting the GIS tools market. Additionally, the integration of GIS with other technologies, such as the Internet of Things (IoT) and Big Data, is creating new opportunities for market growth.



    Regionally, North America holds a significant share of the GIS tools market, driven by the high adoption of advanced technologies and the presence of major market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, owing to increasing investments in infrastructure development, smart city projects, and the growing use of GIS tools in emerging economies such as China and India. Europe, Latin America, and the Middle East & Africa are also expected to contribute to market growth, driven by various government initiatives and increasing awareness of the benefits of GIS tools.



    Component Analysis



    The GIS tools market can be segmented by component into software, hardware, and services. The software segment is anticipated to dominate the market due to the increasing demand for advanced GIS software solutions that offer enhanced data visualization, spatial analysis, and decision-making capabilities. GIS software encompasses a wide range of applications, including mapping, spatial data analysis, and geospatial data management, making it indispensable for various industries. The continuous development of user-friendly and feature-rich software solutions is expected to drive the growth of this segment.



    Hardware components in the GIS tools market include devices such as GPS units, remote sensing devices, and plotting and digitizing tools. The hardware segment is also expected to witness substantial growth, driven by the increasing use of advanced hardware devices that provide accurate and real-time spatial data. The advancements in GPS technology and the development of sophisticated remote sensing devices are key factors contributing to the growth of the hardware segment. Additionally, the integration of hardware with IoT and AI technologies is enhancing the capabilities of GIS tools, further propelling market expansion.



    The services segment includes consulting, integration, maintenance, and support services related to GIS tools. This segment is expected to grow significantly, driven by the increasing demand for specialized services that help organizations effectively implement and manage GIS solutions. Consulting services assist organizations in selecting the right GIS tools and optimizing their use, while integration services ensure seamless integr

  9. a

    GPS Roads Maya Forest GIS

    • spatialdiscovery-ucsb.opendata.arcgis.com
    • library-ucsb.opendata.arcgis.com
    • +1more
    Updated Jan 1, 2000
    + more versions
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    University of California, Santa Barbara (2000). GPS Roads Maya Forest GIS [Dataset]. https://spatialdiscovery-ucsb.opendata.arcgis.com/datasets/gps-roads-maya-forest-gis-1/about
    Explore at:
    Dataset updated
    Jan 1, 2000
    Dataset authored and provided by
    University of California, Santa Barbara
    Area covered
    Description

    In the 2000 field season of the BRASS/El Pilar Program, the UCSB Maya Forest GIS collected and processed GPS data for drivable roads in parts of Western Belize and the Peten of Guatemala. Selected for the work were Garmin GPS units accurate from 3-10m (after the US government released Selective Availability SA of error).

  10. w

    Dataset of books called The Global Positioning System and GIS : an...

    • workwithdata.com
    Updated Apr 17, 2025
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    Work With Data (2025). Dataset of books called The Global Positioning System and GIS : an introduction [Dataset]. https://www.workwithdata.com/datasets/books?f=1&fcol0=book&fop0=%3D&fval0=The+Global+Positioning+System+and+GIS+%3A+an+introduction
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    Dataset updated
    Apr 17, 2025
    Dataset authored and provided by
    Work With Data
    License

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

    Description

    This dataset is about books. It has 2 rows and is filtered where the book is The Global Positioning System and GIS : an introduction. It features 7 columns including author, publication date, language, and book publisher.

  11. Windmill Islands GIS data update from various sources

    • data.aad.gov.au
    • researchdata.edu.au
    • +1more
    Updated Mar 29, 2010
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    HARRIS, URSULA (2010). Windmill Islands GIS data update from various sources [Dataset]. https://data.aad.gov.au/metadata/gis164
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    Dataset updated
    Mar 29, 2010
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    HARRIS, URSULA
    License

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

    Time period covered
    Apr 1, 1997 - Mar 1, 2010
    Area covered
    Description

    The Australian Antarctic Data Centre's topographic GIS data for the Windmill Islands, Antarctica were originally mapped mainly from aerial photography: refer to the metadata record 'Windmill Islands 1:50000 Topographic GIS Dataset'. Since then features from various sources have been added to this data.

    The data are available for download as part of the Windmill Islands GIS dataset from a Related URL.

    The data are formatted according to the SCAR Feature Catalogue (see Related URL). Data that are part of this dataset have Dataset_id = 164 in the SCAR Feature Catalogue format.

  12. S

    Spatial Location Services Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 9, 2025
    + more versions
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    Market Report Analytics (2025). Spatial Location Services Report [Dataset]. https://www.marketreportanalytics.com/reports/spatial-location-services-73816
    Explore at:
    pdf, ppt, docAvailable download formats
    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

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

    The global spatial location services market is experiencing robust growth, driven by increasing demand for precise location intelligence across diverse sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, the proliferation of smart devices and the Internet of Things (IoT) is generating massive location data, which fuels the need for sophisticated spatial analysis and location-based services. Secondly, advancements in technologies like GPS, GIS, and machine learning are enhancing the accuracy and capabilities of location services, enabling innovative applications in various industries. Thirdly, the growing adoption of location-based marketing and advertising strategies is creating lucrative opportunities for businesses to engage with customers more effectively. Finally, government initiatives focusing on infrastructure development and smart city projects are further propelling market growth. The market is segmented by application (commercial, municipal, military, others) and type (indoor, outdoor positioning). Commercial applications currently dominate, but the municipal and military segments are expected to witness significant growth in the coming years due to increasing investments in smart city infrastructure and defense modernization programs. The competitive landscape is characterized by a mix of established technology providers, GIS specialists, and consulting firms. Major players like Google Cloud, Oracle, IBM, and HERE Technologies are leveraging their extensive data resources and technological expertise to gain a strong foothold. However, smaller, specialized firms are also thriving by offering niche solutions and innovative applications. Regional variations exist, with North America and Europe currently dominating the market due to higher technology adoption rates and well-established infrastructure. However, the Asia-Pacific region is poised for rapid expansion, driven by increasing smartphone penetration and government support for digitalization initiatives. The market faces challenges such as data privacy concerns, cybersecurity risks, and the need for seamless integration of diverse location data sources. Nevertheless, the overall outlook remains highly positive, indicating substantial growth potential for spatial location services in the years to come.

  13. Casey Station Fire Hydrants GIS Dataset

    • data.aad.gov.au
    • researchdata.edu.au
    • +4more
    Updated Feb 2, 2010
    + more versions
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    HARRIS, URSULA (2010). Casey Station Fire Hydrants GIS Dataset [Dataset]. https://data.aad.gov.au/metadata/gis20
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    Dataset updated
    Feb 2, 2010
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    HARRIS, URSULA
    License

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

    Time period covered
    Oct 1, 1999 - Sep 1, 2000
    Area covered
    Description

    This GIS dataset shows the locations of fire hydrants at Casey Station. The data are formatted according to the SCAR Feature Catalogue (see Related URL). Data quality information for each feature is located in the attribute table.

  14. a

    Utah TURN GPS BaseLines

    • hub.arcgis.com
    • opendata.gis.utah.gov
    • +2more
    Updated Jun 2, 2015
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    Utah Automated Geographic Reference Center (AGRC) (2015). Utah TURN GPS BaseLines [Dataset]. https://hub.arcgis.com/maps/utah::utah-turn-gps-baselines
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    Dataset updated
    Jun 2, 2015
    Dataset authored and provided by
    Utah Automated Geographic Reference Center (AGRC)
    License

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

    Area covered
    Description

    This data represents the measured distance between the The Utah Reference Network Global Positioning System (TURN GPS) base stations. It models the current coverage of the network and in some areas extends past the boundary of Utah. Baselines with a distance greater than 70 km will start to decrease your precision.

  15. Survey of the road between Casey Station and Old Casey Station, 9 March 1999...

    • data.aad.gov.au
    • researchdata.edu.au
    • +1more
    Updated Sep 14, 2009
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    RUDDELL, ANDREW (2009). Survey of the road between Casey Station and Old Casey Station, 9 March 1999 [Dataset]. https://data.aad.gov.au/metadata/gis22
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    Dataset updated
    Sep 14, 2009
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    RUDDELL, ANDREW
    License

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

    Time period covered
    Mar 9, 1999
    Area covered
    Description

    A GPS survey by Andrew Ruddell (AAD Glaciology) on 9 March 1999 at Casey Station, Antarctica. The survey was conducted along the road from Casey Station to Old Casey. The aim of the survey was to investigate the cause of the 'disappearance' of road gravel applied to the compacted snow road in the depression between Casey Station to Old Casey. This dataset consists of point data with an elevation (above mean sea level) attribute. The data, in Excel and shapefile formats, and Andrew's report are available for download (see Related URL below).

  16. Whitney Point Adelie Penguin Colonies, Vector GIS Layer

    • data.aad.gov.au
    • cloud.csiss.gmu.edu
    • +4more
    Updated Feb 9, 2017
    + more versions
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    WOEHLER, ERIC (2017). Whitney Point Adelie Penguin Colonies, Vector GIS Layer [Dataset]. https://data.aad.gov.au/metadata/ASAC_1219_AAT_WP_ADPE_Colonies
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    Dataset updated
    Feb 9, 2017
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    WOEHLER, ERIC
    License

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

    Time period covered
    Feb 10, 2006 - Feb 24, 2006
    Area covered
    Description

    An ArcGIS shapefile layer showing the extent of all extant and relic Adelie penguin (Pygoscelis adeliae) colonies at Whitney Point, Windmill Islands, February 2006. The field 'Status' describes each polygon as extant, relic or maximum. Extant refers to the area used by breeding birds in the summer 2005/06. Maximum refers to the historic maximal extent of the colony. Relic refers to any colony which was not occupied by any breeding pairs during 2005/06.

    Positional accuracy is approx. 1-2 m, after accounting for dGPS errors and errors in identification of the boundaries of colonies. Mapping was conducted after the end of the breeding season, so boundaries were identified as the extent of nest pebbles/fresh faeces, and it was considered that they could be reliably identified to within 0.5m.

    Data were acquired using a Trimble Pro XH differential GPS. This work was completed as part of ASAC project 1219 (ASAC_1219).

    Also for this project, three aerial photographs of Whitney point showing the adelie penguin colonies and taken on 17 December 1990 were georeferenced. These aerial photographs are film ANTC1219 run 54 frames 21 to 23.

    Work on this project also utilised a Digital Elevation Model (DEM) created for Shirley Island. See the metadata record, 'A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica' for more information (linked below).

    Since the 2005/06 summer was a low-ice year the opportunity was also taken to survey with differential GPS a section of coastline about 230 metres long east of Whitney Point on Clark Peninsula. This section of coastline was ice free and accessible. The data was collected with differential GPS on 10 February 2006.

  17. S

    Spatial Location Services Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated May 4, 2025
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    Data Insights Market (2025). Spatial Location Services Report [Dataset]. https://www.datainsightsmarket.com/reports/spatial-location-services-508723
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    doc, pdf, pptAvailable download formats
    Dataset updated
    May 4, 2025
    Dataset authored and provided by
    Data Insights Market
    License

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

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

    The global spatial location services market is experiencing robust growth, driven by increasing adoption of location-based services across diverse sectors. The market, estimated at $50 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a compound annual growth rate (CAGR) of 15%. This expansion is largely attributed to several key factors. Firstly, the proliferation of smart devices and the rise of the Internet of Things (IoT) are generating vast amounts of location data, creating significant opportunities for service providers. Secondly, advancements in technologies such as GPS, GIS, and mapping software are enhancing the accuracy and efficiency of location-based services, making them more attractive to businesses and consumers alike. Thirdly, the increasing demand for location intelligence across diverse industries, including logistics, transportation, retail, and public safety, is propelling market growth. The commercial sector, currently the largest segment, is expected to maintain its dominance, followed by municipal and military applications. Indoor positioning technology is gaining traction, particularly in smart buildings and indoor navigation applications. North America and Europe currently hold the largest market share, but the Asia-Pacific region is poised for rapid expansion driven by economic growth and increasing digital adoption. Despite the positive outlook, the market faces certain challenges. Data privacy concerns and regulations are becoming increasingly significant, requiring service providers to prioritize data security and comply with evolving legal frameworks. Furthermore, the accuracy and reliability of location data remain critical considerations, and the development of robust and reliable technologies to address these issues is crucial for sustained market growth. Competitive intensity is another challenge. The market is populated by a mix of established technology giants and specialized location services providers. The need for innovation and the ability to adapt to evolving technologies and customer needs are critical for maintaining a competitive advantage. Successful players are leveraging partnerships and mergers and acquisitions to expand their market reach and service offerings. The long-term growth of this market depends on the continued advancement of location technology, addressing privacy concerns, and successfully penetrating new application areas.

  18. G

    Geospatial Analytics Market Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Mar 18, 2025
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    Market Report Analytics (2025). Geospatial Analytics Market Report [Dataset]. https://www.marketreportanalytics.com/reports/geospatial-analytics-market-10566
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Mar 18, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

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

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

    The geospatial analytics market, valued at $93.91 billion in 2025, is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 18.68% from 2025 to 2033. This significant expansion is fueled by several key factors. The increasing adoption of advanced technologies like GPS, GIS, and remote sensing across diverse sectors is a major driver. The BFSI (Banking, Financial Services, and Insurance), government and utilities, and telecom industries are particularly heavy users, leveraging geospatial analytics for improved risk assessment, resource management, and customer service. Furthermore, the rising demand for precise location-based services in manufacturing, automotive, and retail sectors is contributing to market growth. The integration of AI and machine learning into geospatial analytics platforms enhances analytical capabilities, further driving adoption. Government initiatives promoting digital transformation and smart city projects also significantly boost market demand. While data privacy and security concerns represent a potential restraint, the overall market outlook remains highly positive due to the expanding applications of geospatial analytics across various sectors and geographical regions. North America currently holds a dominant market share, primarily driven by the presence of major technology companies and significant investments in infrastructure development. However, the Asia-Pacific region is poised for rapid growth, fueled by increasing urbanization, rising digital adoption, and government investments in infrastructure development in countries like China and India. Europe also contributes significantly to market revenue, with strong growth expected in several key countries. The competitive landscape is characterized by a mix of large multinational corporations and specialized technology providers. Key players are focusing on strategic partnerships, acquisitions, and technological innovations to enhance their market position and cater to evolving customer demands. The market is expected to witness increased consolidation in the coming years as companies strive to expand their product offerings and geographical reach. The overall market dynamics indicate a bright future for geospatial analytics, with continued innovation and growth anticipated across all segments.

  19. G

    GIS Collectors Report

    • promarketreports.com
    doc, pdf, ppt
    Updated May 27, 2025
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    Pro Market Reports (2025). GIS Collectors Report [Dataset]. https://www.promarketreports.com/reports/gis-collectors-219571
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    pdf, doc, pptAvailable download formats
    Dataset updated
    May 27, 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 market for GIS Collectors is experiencing robust growth, driven by increasing adoption of location-based services across various sectors. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by several key factors, including the rising need for precise geospatial data in urban planning, infrastructure development, environmental monitoring, and precision agriculture. Advancements in data acquisition technologies, such as improved GPS accuracy and the integration of sensors like LiDAR and hyperspectral imaging, are further boosting market expansion. The increasing availability of affordable and user-friendly GIS software and cloud-based solutions is also contributing to wider adoption across diverse user groups, from professional surveyors to citizen scientists. The competitive landscape is characterized by a mix of established players and emerging technology providers. Major companies like Hexagon, Trimble Geospatial, ESRI, Topcon, and Handheld are leveraging their existing market presence and technological expertise to expand their product portfolios and cater to evolving customer needs. Meanwhile, companies from regions like China, such as Wuhan South, are emerging as significant players, particularly in the provision of cost-effective solutions. While the market faces some restraints, such as the initial investment costs associated with GIS technology and the need for skilled professionals, the overall growth trajectory remains strongly positive, indicating considerable potential for continued market expansion throughout the forecast period. The increasing focus on data security and privacy regulations will also influence market trends, particularly regarding data storage and transmission. This comprehensive report provides an in-depth analysis of the global GIS Collectors market, projected to reach $5 billion by 2028. It delves into market concentration, key trends, dominant regions, product insights, and future growth catalysts, offering valuable insights for stakeholders across the geospatial technology sector. The report utilizes rigorous data analysis and industry expertise to provide actionable intelligence for informed decision-making.

  20. K

    Geo-referenced Annual Crop Yields - Processed

    • lter.kbs.msu.edu
    Updated Mar 18, 2024
    + more versions
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    Phil Robertson; Sven Bohm; Nick Haddad (2024). Geo-referenced Annual Crop Yields - Processed [Dataset]. https://lter.kbs.msu.edu/datatables/185
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    Dataset updated
    Mar 18, 2024
    Dataset provided by
    Michigan State University
    Authors
    Phil Robertson; Sven Bohm; Nick Haddad
    License

    https://lter.kbs.msu.edu/data/terms-of-use/https://lter.kbs.msu.edu/data/terms-of-use/

    Variables measured
    year, yield, species, latitude, moisture, longitude
    Description

    Annual crop harvest yields of corn, soy and wheat from the Main Cropping System Experiment at...

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NCGE (2021). Using GPS and GIS [Dataset]. https://library.ncge.org/documents/50b7245a36114c4387e4327782030633

Using GPS and GIS

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Dataset updated
Jul 27, 2021
Dataset authored and provided by
NCGE
License

Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically

Description

Author: A Lisson, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8Resource type: lessonSubject topic(s): gis, geographic thinkingRegion: united statesStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.Objectives: Students will be able to:

  1. Explain the difference between two types of geospatial technologies - GPS and GIS.
  2. Develop basic skills to effectively manipulate and use GPS receivers and ArcGIS software.
  3. Explain uses of GPS and GIS.Summary: Students use GPS coordinates to discover geocaches at a local park, and they use ArcGIS to layer maps about the park. Frontenac State park is the example, but any park or area (including school grounds) could be used. Students also investigate careers that use GIS.
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