33 datasets found
  1. d

    Development of Interactive Data Visualization Tool for the Predictive...

    • search.dataone.org
    • borealisdata.ca
    • +1more
    Updated Dec 28, 2023
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    Chan, Wai Chung Wilson (2023). Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project [Dataset]. http://doi.org/10.5683/SP3/7RVB70
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Chan, Wai Chung Wilson
    Description

    Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.

  2. Vietnam Geospatial Analytics Market Report by Component (Solution,...

    • imarcgroup.com
    pdf,excel,csv,ppt
    Updated Dec 26, 2023
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    IMARC Group (2023). Vietnam Geospatial Analytics Market Report by Component (Solution, Services), Type (Surface and Field Analytics, Network and Location Analytics, Geovisualization, and Others), Technology (Remote Sensing, GIS, GPS, and Others), Enterprise Size (Large Enterprises, Small and Medium-sized Enterprises), Deployment Mode (On-premises, Cloud-based), Vertical (Automotive, Energy and Utilities, Government, Defense and Intelligence, Smart Cities, Insurance, Natural Resources, and Others), and Region 2024-2032 [Dataset]. https://www.imarcgroup.com/vietnam-geospatial-analytics-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Dec 26, 2023
    Dataset provided by
    Imarc Group
    Authors
    IMARC Group
    License

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

    Time period covered
    2024 - 2032
    Area covered
    Vietnam, Global
    Description

    Market Overview:

    The Vietnam geospatial analytics market size is projected to exhibit a growth rate (CAGR) of 8.90% during 2024-2032. The increasing product utilization by government authorities in various sectors, various technological advancements in satellite technology, remote sensing, and data collection methods, and the rising development of smart cities represent some of the key factors driving the market.

    Report Attribute
    Key Statistics
    Base Year
    2023
    Forecast Years
    2024-2032
    Historical Years
    2018-2023
    Market Growth Rate (2024-2032)8.90%


    Geospatial analytics is a field of data analysis that focuses on the interpretation and analysis of geographic and spatial data to gain valuable insights and make informed decisions. It combines geographical information systems (GIS), advanced data analysis techniques, and visualization tools to analyze and interpret data with a spatial or geographic component. It also enables the collection, storage, analysis, and visualization of geospatial data. It provides tools and software for managing and manipulating spatial data, allowing users to create maps, perform spatial queries, and conduct spatial analysis. In addition, geospatial analytics often involves integrating geospatial data with other types of data, such as demographic data, environmental data, or economic data. This integration helps in gaining a more comprehensive understanding of complex phenomena. Moreover, geospatial analytics has a wide range of applications. For example, it can be used in urban planning to optimize transportation routes, in agriculture to manage crop yield and soil quality, in disaster management to assess and respond to natural disasters, in wildlife conservation to track animal migrations, and in business for location-based marketing and site selection.

    Vietnam Geospatial Analytics Market Trends:

    The Vietnamese government has recognized the importance of geospatial analytics in various sectors, including urban planning, agriculture, disaster management, and environmental monitoring. Initiatives to develop and utilize geospatial data for public projects and policy-making have spurred demand for geospatial analytics solutions. In addition, Vietnam is experiencing rapid urbanization and infrastructure development. Geospatial analytics is critical for effective urban planning, transportation management, and infrastructure optimization. This trend is driving the adoption of geospatial solutions in cities and regions across the country. Besides, Vietnam's agriculture sector is a significant driver of its economy. Geospatial analytics helps farmers and agricultural businesses optimize crop management, soil health, and resource allocation. Consequently, precision farming techniques, enabled by geospatial data, are becoming increasingly popular, which is also propelling the market. Moreover, the development of smart cities in Vietnam relies on geospatial analytics for various applications, such as traffic management, public safety, and energy efficiency. Geospatial data is central to building the infrastructure needed for smart city initiatives. Furthermore, advances in satellite technology, remote sensing, and data collection methods have made geospatial data more accessible and affordable. This has lowered barriers to entry and encouraged the use of geospatial analytics in various sectors. Additionally, the telecommunications sector in Vietnam is expanding, and location-based services, such as navigation and advertising, rely on geospatial analytics. This creates opportunities for geospatial data providers and analytics solutions in the telecommunications industry.

    Vietnam Geospatial Analytics Market Segmentation:

    IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the country level for 2024-2032. Our report has categorized the market based on component, type, technology, enterprise size, deployment mode, and vertical.

    Component Insights:

    Vietnam Geospatial Analytics Market Reporthttps://www.imarcgroup.com/CKEditor/2e6fe72c-0238-4598-8c62-c08c0e72a138other-regions1.webp" style="height:450px; width:800px" />

    • Solution
    • Services

    The report has provided a detailed breakup and analysis of the market based on the component. This includes solution and services.

    Type Insights:

    • Surface and Field Analytics
    • Network and Location Analytics
    • Geovisualization
    • Others

    A detailed breakup and analysis of the market based on the type have also been provided in the report. This includes surface and field analytics, network and location analytics, geovisualization, and others.

    Technology Insights:

    • Remote Sensing
    • GIS
    • GPS
    • Others

    The report has provided a detailed breakup and analysis of the market based on the technology. This includes remote sensing, GIS, GPS, and others.

    Enterprise Size Insights:

    • Large Enterprises
    • Small and Medium-sized Enterprises

    A detailed breakup and analysis of the market based on the enterprise size have also been provided in the report. This includes large enterprises and small and medium-sized enterprises.

    Deployment Mode Insights:

    • On-premises
    • Cloud-based

    The report has provided a detailed breakup and analysis of the market based on the deployment mode. This includes on-premises and cloud-based.

    Vertical Insights:

    • Automotive
    • Energy and Utilities
    • Government
    • Defense and Intelligence
    • Smart Cities
    • Insurance
    • Natural Resources
    • Others

    A detailed breakup and analysis of the market based on the vertical have also been provided in the report. This includes automotive, energy and utilities, government, defense and intelligence, smart cities, insurance, natural resources, and others.

    Regional Insights:

    Vietnam Geospatial Analytics Market Reporthttps://www.imarcgroup.com/CKEditor/bbfb54c8-5798-401f-ae74-02c90e137388other-regions6.webp" style="height:450px; width:800px" />

    • Northern Vietnam
    • Central Vietnam
    • Southern Vietnam

    The report has also provided a comprehensive analysis of all the major regional markets, which include Northern Vietnam, Central Vietnam, and Southern Vietnam.

    Competitive Landscape:

    The market research report has also provided a comprehensive analysis of the competitive landscape in the market. Competitive analysis such as market structure, key player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided.

    Vietnam Geospatial Analytics Market Report Coverage:

    <td

    Report FeaturesDetails
    Base Year of the Analysis2023
    Historical Period
  3. D

    Digital Earth Platform Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Mar 16, 2025
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    Market Research Forecast (2025). Digital Earth Platform Report [Dataset]. https://www.marketresearchforecast.com/reports/digital-earth-platform-36073
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    doc, ppt, pdfAvailable download formats
    Dataset updated
    Mar 16, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

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

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

    The Digital Earth Platform market is experiencing robust growth, driven by increasing government initiatives for infrastructure development, rising demand for precise location-based services, and the expanding adoption of advanced technologies like AI and machine learning for data analysis. The market's compound annual growth rate (CAGR) is estimated to be around 15% between 2025 and 2033, indicating a significant expansion opportunity. Key segments driving this growth include government departments and enterprise applications, which leverage the platform's capabilities for efficient resource management, urban planning, and environmental monitoring. The use of GPS and GIS technologies is central to the platform's functionality, enabling accurate mapping, spatial analysis, and real-time data visualization. North America and Europe currently hold the largest market share due to high technological adoption and robust government investments. However, the Asia-Pacific region is projected to witness significant growth in the coming years, fuelled by rapid urbanization and infrastructure development in countries like China and India. Competition in the market is intense, with major players including Microsoft, Google, and ESRI vying for market dominance through technological innovation and strategic partnerships. Market restraints include the high initial investment costs associated with implementing and maintaining Digital Earth Platforms, along with concerns surrounding data security and privacy. Despite these challenges, the long-term outlook for the Digital Earth Platform market remains exceptionally positive, driven by the increasing need for data-driven decision-making across various sectors. The market segmentation reveals diverse application scenarios. Government departments utilize the platform for comprehensive urban planning, disaster response, and environmental monitoring. Enterprises leverage its capabilities for optimizing logistics, supply chain management, and market analysis. Public services benefit from improved infrastructure management and resource allocation. Technological advancements are constantly shaping the market, with emerging trends focusing on cloud-based solutions, improved data analytics, and integration with Internet of Things (IoT) devices. This convergence of technologies promises enhanced data processing speeds, more comprehensive analysis, and the capacity to manage increasingly large and complex datasets efficiently. The continuous refinement of GPS and GIS technologies also contributes to the platform’s growing precision and usefulness across various applications. The market’s success hinges on the continuous development and deployment of user-friendly interfaces that allow seamless data access and visualization across a variety of devices and applications.

  4. Geospatial Solutions Market is Growing at CAGR of 16.50% from 2024 to 2031

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Apr 4, 2024
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    Cognitive Market Research (2024). Geospatial Solutions Market is Growing at CAGR of 16.50% from 2024 to 2031 [Dataset]. https://www.cognitivemarketresearch.com/geospatial-solutions-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Apr 4, 2024
    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 Geospatial Solutions market size is USD 508421.2million in 2024 and will expand at a compound annual growth rate (CAGR) of 16.50% from 2024 to 2031.

    North America held the major market of more than 40% of the global revenue with a market size of USD 203368.48 million in 2024 and will grow at a compound annual growth rate (CAGR) of 14.7% from 2024 to 2031.
    Europe accounted for a share of over 30% of the global market size of USD 152526.36 million.
    Asia Pacific held the market of around 23% of the global revenue with a market size of USD 116936.88 million in 2024 and will grow at a compound annual growth rate (CAGR) of 18.5% from 2024 to 2031.
    Latin America market of more than 5% of the global revenue with a market size of USD 25421.06 million in 2024 and will grow at a compound annual growth rate (CAGR) of 15.9% from 2024 to 2031.
    Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 10168.42 million in 2024 and will grow at a compound annual growth rate (CAGR) of 16.2% from 2024 to 2031.
    The hospitals held the highest Geospatial Solutions market revenue share in 2024.
    

    Key Driver of the Geospatial Solutions Market

    Growing Demand for Location-based Data and Insights to Increase the Demand Globally
    

    Businesses and organizations prioritize making well-informed decisions, driving demand for location-based data and insights. Having accurate and comprehensive information about people, places, and things is becoming increasingly important. Geospatial solutions play a crucial role in gathering, evaluating, and presenting this data, which drives market growth. These technologies help with resource allocation, market targeting, and strategy planning by providing advanced tools for interpreting spatial data. Businesses use geospatial data to improve customer experiences, optimize operations, and gain competitive advantages due to the development of GPS, remote sensing, and GIS. Because of this, the geospatial industry is expanding rapidly and satisfying the changing demands of various industries looking for useful location-based insights.

    Advancements in Technology to Propel Market Growth
    

    The geospatial industry is expanding significantly due to technological advancements, including aerial images, remote sensing, GNSS (Global Navigation Satellite Systems), and LiDAR (Light Detection and Ranging). These developments provide ever-more accurate, affordable, and easily accessible ways to collect geospatial data. While GNSS offers precise global location data, remote sensing technologies allow data collection from inaccessible or remote areas. LiDAR and aerial images improve data resolution and detail, allowing for more complex analysis and visualization. The geospatial market is growing due to the ongoing development of these technologies, which enables businesses and organizations in various industries to make wise decisions, maximize operations, and seize new possibilities.

    Restraints factor of the Geospatial Solutions Market

    Data Privacy and Security Concerns to Limit the Sales
    

    The widespread use of geographical data gives rise to serious privacy and security problems. The increasing accessibility and utilization of location-based data across many businesses underscores the need for strong data governance frameworks to preserve individuals' privacy and prevent potential compromises of sensitive data. Furthermore, upholding moral principles and legal compliance depends on gaining users' trust via open data policies and permission procedures. Companies may promote the responsible and ethical use of location-based information by addressing these concerns and fostering better stakeholder confidence. Additionally, companies should limit risks connected with gathering, sharing, and utilizing geospatial data.

    Impact of COVID-19 on the Geospatial Solutions Market

    The geospatial solutions market has experienced varying effects from the COVID-19 epidemic. Due to supply chain disruptions and economic uncertainty, several industries faced a brief pause. Still, others saw faster development as a result of the pressing need for location-based data to solve pandemic-related issues. Geospatial technologies are increasingly used in industries, including healthcare, logistics, and urban planning, to track the virus's spread, allocate resourc...

  5. Geospatial Analytics Market Size, Insights, Trends & Share Report, 2035

    • rootsanalysis.com
    Updated Sep 9, 2024
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    Roots Analysis (2024). Geospatial Analytics Market Size, Insights, Trends & Share Report, 2035 [Dataset]. https://www.rootsanalysis.com/geospatial-analytics-market
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    Dataset updated
    Sep 9, 2024
    Dataset provided by
    Authors
    Roots Analysis
    License

    https://www.rootsanalysis.com/privacy.htmlhttps://www.rootsanalysis.com/privacy.html

    Time period covered
    2021 - 2031
    Area covered
    Global
    Description

    The geospatial analytics market size is predicted to rise from $93.49 billion in 2024 to $362.45 billion by 2035, growing at a CAGR of 13.1% from 2024 to 2035.

  6. H

    CELL5M: A Multidisciplinary Geospatial Database for Africa South of the...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Dec 5, 2017
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    Harvard Dataverse (2017). CELL5M: A Multidisciplinary Geospatial Database for Africa South of the Sahara [Dataset]. http://doi.org/10.7910/DVN/G4TBLF
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 5, 2017
    Dataset provided by
    Harvard Dataverse
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Sub-Saharan Africa, Africa
    Dataset funded by
    CGIAR Research Program on Policies, Institutions, and Markets (PIM)
    The Bill and Melinda Gates Foundation
    Description

    Spatially-explicit data is increasingly becoming available across disciplines, yet they are often limited to a specific domain. In order to use such datasets in a coherent analysis, such as to decide where to target specific types of agricultural investment, there should be an effort to make such datasets harmonized and interoperable. For Africa South of the Sahara (SSA) region, the HarvestChoice CELL5M Database was developed in this spirit of moving multidisciplinary data into one harmonized, geospatial database. The database includes over 750 biophysical and socio-economic indicators, many of which can be easily expanded to global scale. The CELL5M database provides a platform for cross-cutting spatial analyses and fine-grain visualization of the mix of farming systems and populations across SSA. It was created as the central core to support a decision-making platform that would enable development practitioners and researchers to explore multi-faceted spatial relationships at the nexus of poverty, health and nutrition, farming systems, innovation, and environment. The database is a matrix populated by over 350,000 grid cells covering SSA at five arc-minute spatial resolution. Users of the database, including those conduct researches on agricultural policy, research, and development issues, can also easily overlay their own indicators. Numerical aggregation of the gridded data by specific geographical domains, either at subnational level or across country borders for more regional analysis, is also readily possible without needing to use any specific GIS software. See the HCID database (http://dx.doi.org/10.7910/DVN/MZLXVQ) for the geometry of each grid cell. The database also provides standard-compliant data API that currently powers several web-based data visualization and analytics tools.

  7. d

    Places Data | Known Polygon Search

    • datarade.ai
    .json, .csv
    Updated Jul 31, 2024
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    Sovereign Intelligence (2024). Places Data | Known Polygon Search [Dataset]. https://datarade.ai/data-products/sovereign-intelligence-places-data-known-polygon-analytics-sovereign-intelligence
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    .json, .csvAvailable download formats
    Dataset updated
    Jul 31, 2024
    Dataset authored and provided by
    Sovereign Intelligence
    Area covered
    Sierra Leone, Kenya, Cameroon, Faroe Islands, Togo, Liechtenstein, Heard Island and McDonald Islands, Fiji, Bahamas, Trinidad and Tobago
    Description

    Aurora:GeoStudio® is a cutting-edge geospatial analysis platform that excels in supporting Point of Interest (POI) data, providing detailed and comprehensive information about specific locations or landmarks. POI data includes essential details such as the name, address, coordinates, and category of locations, ranging from restaurants and hotels to parks and tourist attractions. This data is vital for enhancing mapping and navigation applications, making it easier for users to find relevant and nearby points of interest.

    Core Features:

      1.    Known Polygon Search (KPS) via OpenStreetMap®:
      •    Aurora:GeoStudio® integrates with OpenStreetMap® to offer Known Polygon Search functionality. This feature enables users to accurately identify and retrieve POI data within defined areas of interest. OpenStreetMap® provides a vast and up-to-date database of POIs, ensuring comprehensive coverage and accurate information.
      2.    Automatic Gridding and Area Analytics:
      •    The platform includes automatic gridding within areas of interest, facilitating detailed Area Usage and Area Visit analytics. This functionality divides the area into manageable grids, allowing users to analyze POI data effectively. The automated process supports the visualization of POI density, visitation patterns, and the impact of various factors on POI popularity and usage.
      3.    POI Data Visualization:
      •    Aurora:GeoStudio® offers advanced visualization capabilities, displaying POI data on customizable maps from providers like Google, Esri, Open, and Stamen. This visualization helps users understand the spatial distribution of POIs and their relationships within an area, aiding in effective decision-making and strategic planning.
    

    Applications:

      1.    Urban Planning:
      •    Urban planners can use POI data to understand the distribution of amenities and services within a city. This information helps in planning new developments, optimizing resource allocation, and ensuring that essential services are accessible to residents. By analyzing POI data, planners can create more livable and well-serviced urban areas.
      2.    Infrastructure Management:
      •    POI data is invaluable for managing infrastructure projects, including the placement of utilities, public transportation, and commercial services. Understanding the location and category of POIs allows for better planning and coordination of infrastructure improvements and expansions.
      3.    Spatial Analysis:
      •    Researchers and analysts can leverage POI data to conduct spatial analyses, such as identifying gaps in service provision, studying the impact of new developments, and evaluating the effectiveness of urban policies. Detailed POI data supports robust analysis and actionable insights.
      4.    Area Usage and Visit Analytics:
      •    Aurora:GeoStudio® enables users to track and analyze area usage and visit patterns related to POIs. This is particularly useful for businesses looking to optimize their location strategies, urban developers aiming to enhance public spaces, and government agencies seeking to improve service accessibility and urban experiences.
    

    Aurora:GeoStudio® provides exceptional support for Point of Interest (POI) data, making it a powerful tool for urban planning, infrastructure management, and spatial analysis. By integrating Known Polygon Search via OpenStreetMap® and incorporating automatic gridding and detailed area analytics, the platform offers valuable insights into POI usage and spatial relationships. This capability enhances decision-making processes, supports efficient resource management, and facilitates the development of vibrant and well-planned urban environments. Aurora:GeoStudio®’s advanced features empower users to gain a comprehensive understanding of urban dynamics and optimize their strategic initiatives.

  8. Global Cloud GIS Market By Type (SaaS, PaaS, IaaS), By Application...

    • verifiedmarketresearch.com
    Updated May 31, 2024
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    VERIFIED MARKET RESEARCH (2024). Global Cloud GIS Market By Type (SaaS, PaaS, IaaS), By Application (Government, Enterprises, Education, Healthcare, Retail), By Deployment Model (Public, Private, Hybrid), By Geographic Scope And Forecast [Dataset]. https://www.verifiedmarketresearch.com/product/cloud-gis-market/
    Explore at:
    Dataset updated
    May 31, 2024
    Dataset provided by
    Verified Market Researchhttps://www.verifiedmarketresearch.com/
    Authors
    VERIFIED MARKET RESEARCH
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Time period covered
    2024 - 2031
    Area covered
    Global
    Description

    Cloud GIS Market size was valued at USD 890.81 Million in 2023 and is projected to reach USD 2298.38 Million by 2031, growing at a CAGR of 14.5% from 2024 to 2031.

    Key Market Drivers
    • Increased Adoption of Cloud Computing: Cloud computing provides scalable resources that can be adjusted based on demand, making it easier for organizations to manage and process large GIS datasets. The pay-as-you-go pricing models of cloud services reduce the need for significant upfront investments in hardware and software, making GIS more accessible to small and medium-sized enterprises.
    • Growing Need for Spatial Data Integration: The ability to integrate and analyze large volumes of spatial and non-spatial data helps organizations make more informed decisions. The proliferation of Internet of Things (IoT) devices generates massive amounts of spatial data that can be processed and analyzed using Cloud GIS.
    • Advancements in GIS Technology: User-friendly interfaces and visualization tools make it easier for non-experts to use GIS applications. Advanced analytical tools and machine learning algorithms available in cloud platforms enhance the capabilities of traditional GIS.
    • Increased Demand for Real-Time Data: Industries like disaster management, transportation, and logistics require real-time data processing and analysis, which is facilitated by Cloud GIS. The need for up-to-date maps and spatial data drives the adoption of cloud-based GIS solutions.
    • Collaboration and Sharing Needs: The ability to access GIS data and collaborate from anywhere enhances productivity and supports remote work environments. Cloud GIS supports simultaneous access by multiple users, facilitating better teamwork and data sharing.
    • Urbanization and Smart Cities Initiatives: Cloud GIS is crucial for smart city initiatives, urban planning, and infrastructure development, providing the tools needed for efficient resource management. Supports planning and monitoring of sustainable development projects by providing comprehensive spatial analysis capabilities.
    • Government and Policy Support: Increased government investment in geospatial technologies and smart infrastructure projects drives the adoption of Cloud GIS. Compliance with regulatory requirements for environmental monitoring and land use planning necessitates the use of advanced GIS tools.
    • Industry-Specific Applications: Precision farming and land management benefit from the advanced analytics and data integration capabilities of Cloud GIS. Epidemiology and public health monitoring rely on spatial data analysis for tracking disease outbreaks and resource allocation.

  9. Data from: Developments for 3D gravity and magnetic modeling in spherical...

    • ecat.ga.gov.au
    Updated Jan 1, 2012
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    MNHD (2012). Developments for 3D gravity and magnetic modeling in spherical coordinates [Dataset]. https://ecat.ga.gov.au/geonetwork/srv/api/records/ccd76411-8088-39ce-e044-00144fdd4fa6
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    Dataset updated
    Jan 1, 2012
    Dataset provided by
    Geoscience Australiahttp://ga.gov.au/
    MNHD
    Description

    Abstract # : 1479734 Paper # : GP43B-1142 Session : GP43B Potential-field and EM methods for geologic problems of the mid and upper crust

    Developments for 3D gravity and magnetic modeling in spherical coordinates

    Richard Lane - Geoscience Australia - rjllane@gmail.com Qing Liang - China University of Geosciences (Wuhan) - qingliang.cug@gmail.com Chao Chen - China University of Geosciences (Wuhan) - chenchao@cug.edu.cn Yaoguo Li - Colorado School of Mines - ygli@mines.edu

    At Geoscience Australia (GA), Australia's Commonwealth Government geoscientific agency, we perform gravity and magnetic modeling at a range of scales, from broad regional crustal studies with thousands of kilometer lateral extent and tens of kilometer vertical extent, to detailed local studies with kilometer or less lateral extent and meters to hundreds of meters vertical extent. To achieve greater integration and coherence, and to better understand the geological significance of this work, we are investing in a number of development projects;

    • Spherical coordinate gravity and magnetic modeling,
    • Modeling using High Performance Computing facilities,
    • Utilizing rock property data as an input into the modeling and interpretation of gravity and magnetic data,
    • Better management of geoscience data and models, and
    • Visualization of spatial data in a Virtual Globe format.

    In collaboration with the Colorado School of Mines (CSM) and the China University of Geosciences (CUG), we are developing a capability to model gravity and magnetic data in a spherical coordinate framework. This will provide more accurate calculations and permit us to integrate the results into a single framework that more realistically reflects the shape of the Earth.

    Modeling gravity and magnetic data in a spherical coordinate framework is far more compute intensive than is the case when performing the corresponding calculations in a Cartesian (rectangular) coordinate framework. To reduce the time required to perform the calculations in a spherical coordinate framework, we will be deploying the modeling software on the National Computational Infrastructure (NCI) High Performance Computing (HPC) facility at the Australian National University (ANU). This will also streamline the management of these software relative to the other main option of establishing and maintaining HPC facilities in-house.

    We are a participant in the Deep Exploration Technologies Cooperative Research Centre (DET CRC). In combination with this involvement, we are expanding our support for systematic management of rock property data, and developing a better understanding of how these data can be used to provide constraints for the modeling work. We are also using the opportunities afforded through the DET CRC to make progress with documentation and standardization of data storage and transfer formats so that the tasks of management, discovery and delivery of this information to users are simplified and made more efficient.

    To provide the foundations of integration and analysis of information in a spatial context, we are utilizing and customizing 3D visualization software using a Virtual Globe application, NASA World Wind. This will permit us to view the full range of information types at global to local scales in a realistic coordinate framework.

    Together, these various development activities will play an important role in the on-going effort by Geoscience Australia to add value to the potential field, rock property, and geological information that we possess. We will then be better able to understand the geology of the Australian region and use this knowledge in a range of applications, including mineral and energy exploration, natural hazard mitigation, and groundwater management.

  10. GIS Market Analysis North America, Europe, APAC, South America, Middle East...

    • technavio.com
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    GIS Market Analysis North America, Europe, APAC, South America, Middle East and Africa - US, China, Germany, UK, Canada, Brazil, Japan, France, South Korea, UAE - Size and Forecast 2025-2029 [Dataset]. https://www.technavio.com/report/gis-market-industry-analysis
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    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    United Arab Emirates, South Korea, China, Japan, Brazil, Canada, Germany, United States, United Kingdom, Europe, Global
    Description

    Snapshot img

    GIS Market Size 2025-2029

    The GIS market size is forecast to increase by USD 24.07 billion at a CAGR of 20.3% between 2024 and 2029.

    The Global Geographic Information System (GIS) market is experiencing significant growth due to the integration of Building Information Modeling (BIM) software and GIS, enabling more accurate and efficient construction projects. The increasing adoption of GIS solutions in precision farming for soil and water management is another key trend, with farmers utilizing sensors, GPS, and satellite data to optimize fertilizer usage and crop yields. However, challenges persist, such as the lack of proper planning leading to implementation failures of GIS solutions. In the realm of smart cities, GIS plays a crucial role in managing data from various sources, including LIDAR, computer-aided design, and digital twin technologies. Additionally, public safety and insurance industries are leveraging GIS for server-based data analysis, while smartphones and antennas facilitate real-time data collection. Amidst this digital transformation, ensuring data security and privacy becomes paramount, making it a critical consideration for market participants.
    

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

    Request Free Sample

    The Global Geographic Information System (GIS) market encompasses a range of software solutions and hardware components used to capture, manage, analyze, and visualize geospatial data. Key industries driving market growth include transportation, smart city planning, green buildings, architecture and construction, utilities, oil and gas, agriculture, and urbanization. GIS technology plays a pivotal role in various applications such as 4D GIS software for infrastructure project management, augmented reality platforms for enhanced visualization, and LIDAR and GNSS/GPS antenna for accurate location data collection. Cloud technology is transforming the GIS landscape by enabling real-time data access and collaboration. The transportation sector is leveraging GIS for route optimization, asset management, and predictive maintenance.
    Urbanization and population growth are fueling the demand for GIS in city planning and disaster management. Additionally, GIS is increasingly being adopted in sectors like agriculture for precision farming and soil mapping, and in the construction industry for Building Information Modeling (BIM). The market is also witnessing the emergence of innovative applications in areas such as video games and natural disasters risk assessment. Mobile devices are further expanding the reach of GIS, making it accessible to a wider audience. Overall, the market is poised for significant growth, driven by the increasing need for data-driven decision-making and the integration of geospatial technology into various industries.
    

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

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

    Product
    
      Software
      Data
      Services
    
    
    Type
    
      Telematics and navigation
      Mapping
      Surveying
      Location-based services
    
    
    Device
    
      Desktop
      Mobile
    
    
    Geography
    
      North America
    
        Canada
        US
    
    
      Europe
    
        Germany
        UK
        France
    
    
      APAC
    
        China
        Japan
        South Korea
    
    
      South America
    
        Brazil
    
    
      Middle East and Africa
    

    By Product Insights

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

    The market encompasses desktop, mobile, cloud, and server software solutions, catering to various industries. Open-source software with limited features poses a challenge due to the prevalence of counterfeit products. Yet, the market witnesses an emerging trend toward cloud-based GIS software adoption. However, standardization and interoperability concerns hinder widespread adoption. Geospatial technology is utilized extensively in sectors such as Transportation, Utilities, Oil and Gas, Agriculture, and Urbanization, driven by population growth, urban planning, and sustainable development. Key applications include smart city planning, green buildings, BIM, 4D GIS software, augmented reality platforms, GIS collectors, LIDAR, and GNSS/GPS antennas. Cloud technology, mobile devices, and satellite imaging are critical enablers.

    Get a glance at the GIS Industry report of share of various segments Request Free Sample

    The software segment was valued at USD 5.06 billion in 2019 and showed a gradual increase during the forecast period.

    Regional Analysis

    North America is estimated to contribute 38% to the growth of the global market during the forecast period.
    

    Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during th

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

    • technavio.com
    Updated Jun 15, 2024
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    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 States, United Kingdom
    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

  12. A Geospatial Decision Support System Toolkit, Phase I

    • data.nasa.gov
    application/rdfxml +5
    Updated Jun 26, 2018
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    (2018). A Geospatial Decision Support System Toolkit, Phase I [Dataset]. https://data.nasa.gov/dataset/A-Geospatial-Decision-Support-System-Toolkit-Phase/3yts-xj4e
    Explore at:
    application/rssxml, csv, tsv, application/rdfxml, xml, jsonAvailable download formats
    Dataset updated
    Jun 26, 2018
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    We propose to design a working prototype Geospatial Decision Support Toolkit (GeoKit) that will enable scientists, agencies, and stakeholders to configure and deploy their own web based applications containing maps, forms, algorithms, and a rich set of functionality related to visualization, analysis, querying, and publication of geospatial data and information. GeoKit will focus on development of a suite of tools that will operate on data, to create rule-based applications for risk analysis, risk mitigation, operations management, and science research support. GeoKit will enhance the the use of data from NASA and other sources, provide a tool for non-software developers to create a website with custom functions and tools that operate on geospatial data, and provide a framework for development of new tools to support risk assessment, risk management, and operational analysis of spatially- explicit data from NASA platforms, climate reanalyses, and user-defined sources, as well as allow real-time publication of results in standard geobrowser compatible formats.

  13. GIS In Utility Industry Market Analysis North America, Europe, APAC, Middle...

    • technavio.com
    Updated Dec 31, 2024
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    Technavio (2024). GIS In Utility Industry Market Analysis North America, Europe, APAC, Middle East and Africa, South America - US, China, Canada, Japan, Germany, Russia, India, Brazil, France, UAE - Size and Forecast 2025-2029 [Dataset]. https://www.technavio.com/report/gis-market-in-the-utility-industry-analysis
    Explore at:
    Dataset updated
    Dec 31, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    France, Canada, Germany, United States, Global
    Description

    Snapshot img

    What is the GIS In Utility Industry Market Size?

    The GIS market in the utility industry size is forecast to increase by USD 3.55 billion at a CAGR of 19.8% between 2023 and 2028. Market expansion hinges on various factors, such as the rising adoption of Geographic Information System (GIS) solutions in the utility sector, the convergence of GIS with Building Information Modeling, and the fusion of Augmented Reality with GIS technology. These elements collectively drive market growth, reflecting advancements in spatial data analytics and technological convergence. The increased adoption of GIS solutions in the utility industry underscores the importance of geospatial data in optimizing infrastructure management. Simultaneously, the integration of GIS with BIM signifies the synergy between spatial and building information for enhanced project planning and management. Additionally, the integration of AR with GIS technology highlights the potential for interactive and interactive visualization experiences in spatial data analysis. Thus, the interplay of these factors delineates the landscape for the anticipated expansion of the market catering to GIS and related technologies.

    What will be the size of Market during the forecast period?

    Request Free GIS In Utility Industry Market Sample

    Market Segmentation

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

    Product
    
      Software
      Data
      Services
    
    
    Deployment
    
      On-premises
      Cloud
    
    
    Geography
    
      North America
    
        Canada
        US
    
    
      Europe
    
        Germany
        France
    
    
      APAC
    
        China
        India
        Japan
    
    
      Middle East and Africa
    
    
    
      South America
    
        Brazil
    

    Which is the largest segment driving market growth?

    The software segment is estimated to witness significant growth during the forecast period. In the utility industry, the spatial context of geographic information systems (GIS) plays a pivotal role in site selection, land acquisition, planning, designing, visualizing, building, and project management. Utilities, including electricity, gas, water, and telecommunications providers, leverage GIS software to efficiently manage their assets and infrastructure. This technology enables the collection, management, analysis, and visualization of geospatial data, derived from satellite imaging, aerial photography, remote sensors, and artificial intelligence. Geospatial AI, sensor technology, and digital reality solutions are integral components of GIS, enhancing capabilities for smart city planning, urban planning, water management, mapping systems, grid modernization, transportation, and green buildings.

    Get a glance at the market share of various regions. Download the PDF Sample

    The software segment was valued at USD 541.50 million in 2018. Moreover, the geospatial industry continues to evolve, with startups and software solutions driving innovation in hardware, smart city planning, land use management, smart infrastructure planning, and smart utilities. GIS solutions facilitate 4D visualization, enabling stakeholders to overcome geospatial data barriers and make informed decisions. The utility industry's reliance on GIS extends to building information modeling, augmented reality, and smart urban planning, ultimately contributing to the growth of the geospatial technology market.

    Which region is leading the market?

    For more insights on the market share of various regions, Request Free Sample

    North America is estimated to contribute 37% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

    How do company ranking index and market positioning come to your aid?

    Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.

    AABSyS IT Pvt. Ltd. - The company offers GIS solutions such as remote sensing and computer aided design and drafting solutions for electric and gas utility.

    Technavio provides the ranking index for the top 20 companies along with insights on the market positioning of:

    AABSyS IT Pvt. Ltd.
    Autodesk Inc.
    Avineon Inc.
    Bentley Systems Inc.
    Blue Marble Geographics
    Cadcorp Ltd.
    Caliper Corp.
    Environmental Systems Research Institute Inc.
    General Electric Co.
    Hexagon AB
    Mapbox Inc.
    Maxar Technologies Inc.
    Mobile GIS Services Ltd.
    NV5 Global Inc.
    Orbital Insight Inc.
    Pitney Bowes Inc.
    Schneider Electric SE
    SuperMap Software Co. Ltd.
    Trimble Inc.
    VertiGIS Ltd.
    

    Explore our company rankings and market positioning. Request Free Sample

    How can Technavio assist you in ma

  14. d

    Global Mobile Location Data | Over 1 Billion Devices Globally

    • datarade.ai
    .json, .csv
    Updated Jul 29, 2024
    + more versions
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    Sovereign Intelligence (2024). Global Mobile Location Data | Over 1 Billion Devices Globally [Dataset]. https://datarade.ai/data-products/sovereign-intelligence-global-mobile-location-data-over-1-sovereign-intelligence
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Jul 29, 2024
    Dataset authored and provided by
    Sovereign Intelligence
    Area covered
    Saint Pierre and Miquelon, Italy, Barbados, Papua New Guinea, Ukraine, Algeria, Réunion, Saint Barthélemy, Greece, Honduras
    Description

    Aurora:GeoStudio® is a cutting-edge platform that offers robust mobile location data services, providing detailed geographical information about devices’ whereabouts, linked to specific time identifiers. Mobile location data is crucial for a variety of applications, including targeted advertising, traffic analysis, urban planning, and location-based services.

    Core Features:

      1.    Current and Historical Data:
      •    Aurora:GeoStudio® delivers both current and historical mobile location data, allowing users to analyze current movement patterns as well as trends over time. This dual approach enables comprehensive analysis of device trajectories, population movements, and location-specific behaviors.
      2.    High Precision and Accuracy:
      •    The platform ensures high precision and accuracy in mobile location data, providing granular details about device locations. This precise data is essential for applications requiring exact positioning, such as traffic management, navigation services, and emergency response.
      3.    Temporal Context:
      •    Each data point is linked to a specific time identifier, adding a temporal dimension to the geographical information. This feature allows users to track changes and trends over time, understand peak activity periods, and analyze time-dependent patterns, such as rush hour traffic or seasonal visitor fluctuations.
      4.    Data Integration and Visualization:
      •    Aurora:GeoStudio® integrates mobile location data with customizable maps and overlay options, enhancing the visualization of movement patterns and spatial relationships. Users can visualize data on various map types, including Google, Esri, Open, and Stamen variants, and overlay additional data layers, such as traffic density, WiFi usage, and weather conditions, to gain deeper insights.
    

    Applications:

      1.    Targeted Advertising:
      •    By analyzing mobile location data, businesses can deliver highly targeted advertisements to users based on their geographic locations and movement patterns. This enables more effective marketing strategies, tailored to the specific behaviors and preferences of potential customers.
      2.    Traffic Analysis:
      •    Urban planners and traffic management authorities can use mobile location data to analyze traffic flows, identify congestion hotspots, and optimize transportation networks. This data-driven approach supports the development of efficient traffic management solutions and infrastructure improvements.
      3.    Urban Planning:
      •    Mobile location data provides valuable insights into population movements, helping urban planners design better cities. By understanding how people move and interact with urban spaces, planners can optimize public transportation routes, allocate resources more effectively, and create more livable environments.
      4.    Location-Based Services:
      •    Aurora:GeoStudio® supports the development of location-based services, such as navigation apps, ride-sharing platforms, and location-based social networks. Precise mobile location data ensures these services operate efficiently, providing users with accurate and reliable information.
    

    Aurora:GeoStudio® stands out as a powerful tool for leveraging mobile location data, providing detailed geographical information linked to time identifiers. Its capabilities in delivering precise, real-time, and historical data, combined with advanced visualization and integration options, make it an invaluable resource for targeted advertising, traffic analysis, urban planning, and location-based services. By harnessing the power of mobile location data, Aurora:GeoStudio® enables users to make more informed decisions, optimize operations, and develop innovative solutions tailored to geographical and temporal insights.

  15. w

    Global Location Intelligence Business Intelligence Market Research Report:...

    • wiseguyreports.com
    Updated Jan 1, 2025
    + more versions
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    wWiseguy Research Consultants Pvt Ltd (2025). Global Location Intelligence Business Intelligence Market Research Report: By Application (Geospatial Analytics, Data Visualization, Risk Management, Supply Chain Management, Customer Analytics), By Deployment Type (On-Premises, Cloud-Based, Hybrid), By End Use (Retail, Healthcare, Telecommunications, Transportation, Government), By Component (Software, Services, Hardware) and By Regional (North America, Europe, South America, Asia Pacific, Middle East and Africa) - Forecast to 2032. [Dataset]. https://www.wiseguyreports.com/de/reports/location-intelligence-business-lntelligence-market
    Explore at:
    Dataset updated
    Jan 1, 2025
    Dataset authored and provided by
    wWiseguy Research Consultants Pvt Ltd
    License

    https://www.wiseguyreports.com/pages/privacy-policyhttps://www.wiseguyreports.com/pages/privacy-policy

    Area covered
    Global
    Description
    BASE YEAR2024
    HISTORICAL DATA2019 - 2024
    REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
    MARKET SIZE 202313.77(USD Billion)
    MARKET SIZE 202415.23(USD Billion)
    MARKET SIZE 203234.1(USD Billion)
    SEGMENTS COVEREDApplication, Deployment Type, End Use, Component, Regional
    COUNTRIES COVEREDNorth America, Europe, APAC, South America, MEA
    KEY MARKET DYNAMICSIncreasing demand for data analytics, Rising adoption of cloud-based solutions, Growing emphasis on spatial data visualization, Expanding use of AI and machine learning, Enhanced focus on real-time insights
    MARKET FORECAST UNITSUSD Billion
    KEY COMPANIES PROFILEDQlik, Microsoft, IBM, Google, Hexagon, MicroStrategy, TIBCO Software, Oracle, Teradata, Palantir Technologies, Alteryx, SAP, Tableau, Esri, SAS
    MARKET FORECAST PERIOD2025 - 2032
    KEY MARKET OPPORTUNITIESAdvanced analytics integration, Real-time data visualization, Cloud-based solutions growth, Enhanced mobile applications, AI-driven decision making
    COMPOUND ANNUAL GROWTH RATE (CAGR) 10.6% (2025 - 2032)
  16. BICCN molecular pipelines.

    • plos.figshare.com
    xls
    Updated Jun 30, 2023
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    Michael Hawrylycz; Maryann E. Martone; Giorgio A. Ascoli; Jan G. Bjaalie; Hong-Wei Dong; Satrajit S. Ghosh; Jesse Gillis; Ronna Hertzano; David R. Haynor; Patrick R. Hof; Yongsoo Kim; Ed Lein; Yufeng Liu; Jeremy A. Miller; Partha P. Mitra; Eran Mukamel; Lydia Ng; David Osumi-Sutherland; Hanchuan Peng; Patrick L. Ray; Raymond Sanchez; Aviv Regev; Alex Ropelewski; Richard H. Scheuermann; Shawn Zheng Kai Tan; Carol L. Thompson; Timothy Tickle; Hagen Tilgner; Merina Varghese; Brock Wester; Owen White; Hongkui Zeng; Brian Aevermann; David Allemang; Seth Ament; Thomas L. Athey; Cody Baker; Katherine S. Baker; Pamela M. Baker; Anita Bandrowski; Samik Banerjee; Prajal Bishwakarma; Ambrose Carr; Min Chen; Roni Choudhury; Jonah Cool; Heather Creasy; Florence D’Orazi; Kylee Degatano; Benjamin Dichter; Song-Lin Ding; Tim Dolbeare; Joseph R. Ecker; Rongxin Fang; Jean-Christophe Fillion-Robin; Timothy P. Fliss; James Gee; Tom Gillespie; Nathan Gouwens; Guo-Qiang Zhang; Yaroslav O. Halchenko; Nomi L. Harris; Brian R. Herb; Houri Hintiryan; Gregory Hood; Sam Horvath; Bingxing Huo; Dorota Jarecka; Shengdian Jiang; Farzaneh Khajouei; Elizabeth A. Kiernan; Huseyin Kir; Lauren Kruse; Changkyu Lee; Boudewijn Lelieveldt; Yang Li; Hanqing Liu; Lijuan Liu; Anup Markuhar; James Mathews; Kaylee L. Mathews; Chris Mezias; Michael I. Miller; Tyler Mollenkopf; Shoaib Mufti; Christopher J. Mungall; Joshua Orvis; Maja A. Puchades; Lei Qu; Joseph P. Receveur; Bing Ren; Nathan Sjoquist; Brian Staats; Daniel Tward; Cindy T. J. van Velthoven; Quanxin Wang; Fangming Xie; Hua Xu; Zizhen Yao; Zhixi Yun; Yun Renee Zhang; W. Jim Zheng; Brian Zingg (2023). BICCN molecular pipelines. [Dataset]. http://doi.org/10.1371/journal.pbio.3002133.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 30, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Michael Hawrylycz; Maryann E. Martone; Giorgio A. Ascoli; Jan G. Bjaalie; Hong-Wei Dong; Satrajit S. Ghosh; Jesse Gillis; Ronna Hertzano; David R. Haynor; Patrick R. Hof; Yongsoo Kim; Ed Lein; Yufeng Liu; Jeremy A. Miller; Partha P. Mitra; Eran Mukamel; Lydia Ng; David Osumi-Sutherland; Hanchuan Peng; Patrick L. Ray; Raymond Sanchez; Aviv Regev; Alex Ropelewski; Richard H. Scheuermann; Shawn Zheng Kai Tan; Carol L. Thompson; Timothy Tickle; Hagen Tilgner; Merina Varghese; Brock Wester; Owen White; Hongkui Zeng; Brian Aevermann; David Allemang; Seth Ament; Thomas L. Athey; Cody Baker; Katherine S. Baker; Pamela M. Baker; Anita Bandrowski; Samik Banerjee; Prajal Bishwakarma; Ambrose Carr; Min Chen; Roni Choudhury; Jonah Cool; Heather Creasy; Florence D’Orazi; Kylee Degatano; Benjamin Dichter; Song-Lin Ding; Tim Dolbeare; Joseph R. Ecker; Rongxin Fang; Jean-Christophe Fillion-Robin; Timothy P. Fliss; James Gee; Tom Gillespie; Nathan Gouwens; Guo-Qiang Zhang; Yaroslav O. Halchenko; Nomi L. Harris; Brian R. Herb; Houri Hintiryan; Gregory Hood; Sam Horvath; Bingxing Huo; Dorota Jarecka; Shengdian Jiang; Farzaneh Khajouei; Elizabeth A. Kiernan; Huseyin Kir; Lauren Kruse; Changkyu Lee; Boudewijn Lelieveldt; Yang Li; Hanqing Liu; Lijuan Liu; Anup Markuhar; James Mathews; Kaylee L. Mathews; Chris Mezias; Michael I. Miller; Tyler Mollenkopf; Shoaib Mufti; Christopher J. Mungall; Joshua Orvis; Maja A. Puchades; Lei Qu; Joseph P. Receveur; Bing Ren; Nathan Sjoquist; Brian Staats; Daniel Tward; Cindy T. J. van Velthoven; Quanxin Wang; Fangming Xie; Hua Xu; Zizhen Yao; Zhixi Yun; Yun Renee Zhang; W. Jim Zheng; Brian Zingg
    License

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

    Description

    Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

  17. G

    Geographic Information Systems Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Feb 20, 2025
    + more versions
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    AMA Research & Media LLP (2025). Geographic Information Systems Report [Dataset]. https://www.archivemarketresearch.com/reports/geographic-information-systems-49573
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Feb 20, 2025
    Dataset provided by
    AMA Research & Media LLP
    License

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

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

    Market Analysis for Geographic Information Systems (GIS) The global Geographic Information Systems (GIS) market is projected to reach a value of USD 2890.3 million by 2033, expanding at a CAGR of 5.3% during the forecast period (2025-2033). This growth is driven by increasing adoption of GIS in various industries, such as utilities, transportation, government, and defense. Additionally, the rising demand for real-time data visualization, spatial analysis, and decision-making is fueling the market expansion. The GIS market is segmented based on type (hardware, software, service) and application (public, private). Public sector applications, such as urban planning, land management, and emergency response, are expected to witness significant growth. Private sector applications, including asset management, supply chain optimization, and environmental conservation, are also gaining traction. Key players in the market include Pasco, Ubisense Group, Beijing SuperMap Software, Hexagon, and Schneider Electric. The market is highly competitive, with established players and emerging startups vying for market share. North America and Europe are the largest markets for GIS, with Asia Pacific expected to exhibit the highest growth potential in the coming years.

  18. Photogrammetry Software Market Analysis North America, Europe, APAC, South...

    • technavio.com
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    Photogrammetry Software Market Analysis North America, Europe, APAC, South America, Middle East and Africa - US, China, Germany, Canada, UK - Size and Forecast Report 2024-2028 [Dataset]. https://www.technavio.com/report/photogrammetry-software-market-industry-analysis
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    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global, United Kingdom, Europe, Canada, Germany, United States
    Description

    Snapshot img

    Photogrammetry Software Market Size 2024-2028

    The photogrammetry software market size is forecast to increase by USD 1.16 billion at a CAGR of 14.3% between 2023 and 2028.

    The market is experiencing significant growth due to the increasing adoption of 3D mapping and modeling in various industries, particularly in building and construction. This technology enables the creation of geo-referenced maps and orthomosaic images from drone images, which are essential for 3D visualizations and 3D reconstruction. Additionally, the use of 3D scanning and computer visualization in applications such as 3D modeling and 3D printing of models for drones and quadcopters is driving market growth. However, challenges persist, including the inadequate infrastructure in developing and underdeveloped countries, which hampers the market's expansion. Key software solutions in this market include VisualSFM and OpenMVG, which offer advanced features for processing Images and Video to generate 3D models.
    

    What will be the Size of the Market During the Forecast Period?

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    Photogrammetry software has emerged as a critical tool in various industries, particularly in defense and security, engineering, architecture, and surveyor sectors. This software utilizes advanced imaging technologies, such as high-resolution cameras, Lidar, and drones, to capture data in the form of a series of photographs. These images are then processed using artificial intelligence (AI) and machine learning algorithms to generate 3D models in real time. Data collection technologies have significantly evolved in recent years, with the integration of AI and machine learning enabling faster and more accurate processing of large datasets.

    Moreover, the AI-driven photogrammetry software uses pixels and reference points from the images to create 3D meshes, which are essential for various applications, including emergency management and object recognition in space. The market is segmented into cloud-based Software as a Service (SaaS) and on-premises commercial/proprietary software. The SaaS model offers benefits such as cost savings, flexibility, and scalability, while on-premises software provides greater control and security. The use of AI-driven photogrammetry software is not limited to specific industries. It is widely adopted by surveyors, architects, engineers, and contractors to streamline their workflows and improve accuracy. For instance, Autodesk REMake, an AI-driven photogrammetry software, enables users to create 3D models from images, which can be used for various applications, including architectural design and construction planning.

    Similarly, the geospatial technology plays a crucial role in the effective implementation of photogrammetry software. Real-time data processing and analysis are essential for various applications, including emergency management and infrastructure monitoring. The integration of AI and machine learning algorithms in photogrammetry software enables faster and more accurate processing of geospatial data, making it an indispensable tool for various industries. In conclusion, the advancement of imaging technologies, AI, and machine learning algorithms has significantly impacted the market. The software's ability to generate 3D models from a series of photographs in real-time makes it an essential tool for various industries, including defense and security, engineering, architecture, and surveyor sectors. The integration of geospatial technology further enhances the software's capabilities, making it an indispensable tool for data-driven decision-making.

    Market Segmentation

    The market 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.

    Application
    
      3D printing
      Drones and robots
      Films and games
      Others
    
    
    Deployment
    
      On-premises
      Cloud
    
    
    Geography
    
      North America
    
        Canada
        US
    
    
      Europe
    
        Germany
        UK
    
    
      APAC
    
        China
    
    
      South America
    
    
    
      Middle East and Africa
    

    By Application Insights

    The 3D printing segment is estimated to witness significant growth during the forecast period. In the realm of advanced imaging technologies, the market is witnessing significant growth. This expansion is driven by various sectors, including Defense and Security, where high-precision 3D models are essential for mission planning and analysis. Artificial Intelligence (AI) and Machine Learning (ML) are also playing a pivotal role in the market's growth, enabling real-time data processing and analysis. Data collection technologies, such as LiDAR and high-resolution cameras, integrated with drones, are revolutionizing the way data is captured and processed. Geospatial technology, a critical component of photogrammetry, is enabling the creation

  19. 3

    3D Visualization System Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Feb 22, 2025
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    Archive Market Research (2025). 3D Visualization System Report [Dataset]. https://www.archivemarketresearch.com/reports/3d-visualization-system-44242
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Archive Market Research
    License

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

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

    The global 3D visualization system market is projected to expand at a CAGR of 10.2% during the forecast period of 2025-2033, reaching a value of XX million by 2033. This growth is primarily attributed to the increasing adoption of 3D visualization technology in various industries, including medical care, buildings, and ports. The healthcare sector is expected to witness significant growth, driven by the rising demand for accurate and detailed anatomical models for surgical planning and patient education. Additionally, the adoption of 3D visualization systems in the construction industry is gaining momentum, as it enables architects and engineers to design and visualize complex structures more efficiently. Key trends shaping the market include the growing integration of artificial intelligence (AI) and virtual reality (VR) with 3D visualization systems. AI-powered visualization tools can automate data analysis and generate more realistic simulations, while VR offers immersive experiences that enhance spatial understanding. Market players are also focusing on developing cloud-based 3D visualization solutions, which provide flexibility, scalability, and cost-effectiveness. Regional markets such as Asia Pacific and North America are expected to contribute significantly to the global growth, driven by the presence of major healthcare and technology hubs.

  20. f

    Description of data organization by data levels, definitions, and...

    • figshare.com
    xlsx
    Updated Jun 30, 2023
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    Michael Hawrylycz; Maryann E. Martone; Giorgio A. Ascoli; Jan G. Bjaalie; Hong-Wei Dong; Satrajit S. Ghosh; Jesse Gillis; Ronna Hertzano; David R. Haynor; Patrick R. Hof; Yongsoo Kim; Ed Lein; Yufeng Liu; Jeremy A. Miller; Partha P. Mitra; Eran Mukamel; Lydia Ng; David Osumi-Sutherland; Hanchuan Peng; Patrick L. Ray; Raymond Sanchez; Aviv Regev; Alex Ropelewski; Richard H. Scheuermann; Shawn Zheng Kai Tan; Carol L. Thompson; Timothy Tickle; Hagen Tilgner; Merina Varghese; Brock Wester; Owen White; Hongkui Zeng; Brian Aevermann; David Allemang; Seth Ament; Thomas L. Athey; Cody Baker; Katherine S. Baker; Pamela M. Baker; Anita Bandrowski; Samik Banerjee; Prajal Bishwakarma; Ambrose Carr; Min Chen; Roni Choudhury; Jonah Cool; Heather Creasy; Florence D’Orazi; Kylee Degatano; Benjamin Dichter; Song-Lin Ding; Tim Dolbeare; Joseph R. Ecker; Rongxin Fang; Jean-Christophe Fillion-Robin; Timothy P. Fliss; James Gee; Tom Gillespie; Nathan Gouwens; Guo-Qiang Zhang; Yaroslav O. Halchenko; Nomi L. Harris; Brian R. Herb; Houri Hintiryan; Gregory Hood; Sam Horvath; Bingxing Huo; Dorota Jarecka; Shengdian Jiang; Farzaneh Khajouei; Elizabeth A. Kiernan; Huseyin Kir; Lauren Kruse; Changkyu Lee; Boudewijn Lelieveldt; Yang Li; Hanqing Liu; Lijuan Liu; Anup Markuhar; James Mathews; Kaylee L. Mathews; Chris Mezias; Michael I. Miller; Tyler Mollenkopf; Shoaib Mufti; Christopher J. Mungall; Joshua Orvis; Maja A. Puchades; Lei Qu; Joseph P. Receveur; Bing Ren; Nathan Sjoquist; Brian Staats; Daniel Tward; Cindy T. J. van Velthoven; Quanxin Wang; Fangming Xie; Hua Xu; Zizhen Yao; Zhixi Yun; Yun Renee Zhang; W. Jim Zheng; Brian Zingg (2023). Description of data organization by data levels, definitions, and classification. [Dataset]. http://doi.org/10.1371/journal.pbio.3002133.s002
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    xlsxAvailable download formats
    Dataset updated
    Jun 30, 2023
    Dataset provided by
    PLOS Biology
    Authors
    Michael Hawrylycz; Maryann E. Martone; Giorgio A. Ascoli; Jan G. Bjaalie; Hong-Wei Dong; Satrajit S. Ghosh; Jesse Gillis; Ronna Hertzano; David R. Haynor; Patrick R. Hof; Yongsoo Kim; Ed Lein; Yufeng Liu; Jeremy A. Miller; Partha P. Mitra; Eran Mukamel; Lydia Ng; David Osumi-Sutherland; Hanchuan Peng; Patrick L. Ray; Raymond Sanchez; Aviv Regev; Alex Ropelewski; Richard H. Scheuermann; Shawn Zheng Kai Tan; Carol L. Thompson; Timothy Tickle; Hagen Tilgner; Merina Varghese; Brock Wester; Owen White; Hongkui Zeng; Brian Aevermann; David Allemang; Seth Ament; Thomas L. Athey; Cody Baker; Katherine S. Baker; Pamela M. Baker; Anita Bandrowski; Samik Banerjee; Prajal Bishwakarma; Ambrose Carr; Min Chen; Roni Choudhury; Jonah Cool; Heather Creasy; Florence D’Orazi; Kylee Degatano; Benjamin Dichter; Song-Lin Ding; Tim Dolbeare; Joseph R. Ecker; Rongxin Fang; Jean-Christophe Fillion-Robin; Timothy P. Fliss; James Gee; Tom Gillespie; Nathan Gouwens; Guo-Qiang Zhang; Yaroslav O. Halchenko; Nomi L. Harris; Brian R. Herb; Houri Hintiryan; Gregory Hood; Sam Horvath; Bingxing Huo; Dorota Jarecka; Shengdian Jiang; Farzaneh Khajouei; Elizabeth A. Kiernan; Huseyin Kir; Lauren Kruse; Changkyu Lee; Boudewijn Lelieveldt; Yang Li; Hanqing Liu; Lijuan Liu; Anup Markuhar; James Mathews; Kaylee L. Mathews; Chris Mezias; Michael I. Miller; Tyler Mollenkopf; Shoaib Mufti; Christopher J. Mungall; Joshua Orvis; Maja A. Puchades; Lei Qu; Joseph P. Receveur; Bing Ren; Nathan Sjoquist; Brian Staats; Daniel Tward; Cindy T. J. van Velthoven; Quanxin Wang; Fangming Xie; Hua Xu; Zizhen Yao; Zhixi Yun; Yun Renee Zhang; W. Jim Zheng; Brian Zingg
    License

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

    Description

    Definition of data levels defined by the BICCN. Columns are detailed definition for each specific modality profiled. (XLSX)

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Chan, Wai Chung Wilson (2023). Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project [Dataset]. http://doi.org/10.5683/SP3/7RVB70

Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project

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Dataset updated
Dec 28, 2023
Dataset provided by
Borealis
Authors
Chan, Wai Chung Wilson
Description

Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.

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