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Abstract : The search for the most appropriate GIS data model to integrate, manipulate and analyse spatio-temporal data raises several research questions about the conceptualisation of geographic spaces. Although there is now a general consensus that many environmental phenomena require field and object conceptualisations to provide a comprehensive GIS representation, there is still a need for better integration of these dual representations of space within a formal spatio-temporal database. The research presented in this paper introduces a hybrid and formal dual data model for the representation of spatio-temporal data. The whole approach has been fully implemented in PostgreSQL and its spatial extension PostGIS, where the SQL language is extended by a series of data type constructions and manipulation functions to support hybrid queries. The potential of the approach is illustrated by an application to underwater geomorphological dynamics oriented towards the monitoring of the evolution of seabed changes. A series of performance and scalability experiments are also reported to demonstrate the computational performance of the model.Data Description : The data set used in our research is a set of bathymetric surveys recorded over three years from 2009 to 2011 as Digital Terrain Models (DTM) with 2m grid spacing. The first survey was carried out in February 2009 by the French hydrographic office, the second one was recorded on August-September 2010 and the third in July 2011, both by the “Institut Universitaire Européen de la Mer”.
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The global GIS Data Management market size is projected to grow from USD 12.5 billion in 2023 to USD 25.6 billion by 2032, exhibiting a CAGR of 8.4% during the forecast period. This impressive growth is driven by the increasing adoption of geographic information systems (GIS) across various sectors such as urban planning, disaster management, and agriculture. The rising need for effective data management systems to handle the vast amounts of spatial data generated daily also significantly contributes to the market's expansion.
One of the primary growth factors for the GIS Data Management market is the burgeoning demand for spatial data analytics. Businesses and governments are increasingly leveraging GIS data to make informed decisions and strategize operational efficiencies. With the rapid urbanization and industrialization worldwide, there's an unprecedented need to manage and analyze geographic data to plan infrastructure, monitor environmental changes, and optimize resource allocation. Consequently, the integration of GIS with advanced technologies like artificial intelligence and machine learning is becoming more prominent, further fueling market growth.
Another significant factor propelling the market is the advancement in GIS technology itself. The development of sophisticated software and hardware solutions for GIS data management is making it easier for organizations to capture, store, analyze, and visualize geographic data. Innovations such as 3D GIS, real-time data processing, and cloud-based GIS solutions are transforming the landscape of geographic data management. These advancements are not only enhancing the capabilities of GIS systems but also making them more accessible to a broader range of users, from small enterprises to large governmental agencies.
The growing implementation of GIS in disaster management and emergency response activities is also a critical factor driving market growth. GIS systems play a crucial role in disaster preparedness, response, and recovery by providing accurate and timely geographic data. This data helps in assessing risks, coordinating response activities, and planning resource deployment. With the increasing frequency and intensity of natural disasters, the reliance on GIS data management systems is expected to grow, resulting in higher demand for GIS solutions across the globe.
Geospatial Solutions are becoming increasingly integral to the GIS Data Management landscape, offering enhanced capabilities for spatial data analysis and visualization. These solutions provide a comprehensive framework for integrating various data sources, enabling users to gain deeper insights into geographic patterns and trends. As organizations strive to optimize their operations and decision-making processes, the demand for robust geospatial solutions is on the rise. These solutions not only facilitate the efficient management of spatial data but also support advanced analytics and real-time data processing. By leveraging geospatial solutions, businesses and governments can improve their strategic planning, resource allocation, and environmental monitoring efforts, thereby driving the overall growth of the GIS Data Management market.
Regionally, North America holds a significant share of the GIS Data Management market, driven by high technology adoption rates and substantial investments in GIS technologies by government and private sectors. However, Asia Pacific is anticipated to witness the highest growth rate during the forecast period. The rapid urbanization, economic development, and increasing adoption of advanced technologies in countries like China and India are major contributors to this growth. Governments in this region are also focusing on smart city projects and infrastructure development, which further boosts the demand for GIS data management solutions.
The GIS Data Management market is segmented by component into software, hardware, and services. The software segment is the largest and fastest-growing segment, driven by the continuous advancements in GIS software capabilities. GIS software applications enable users to analyze spatial data, create maps, and manage geographic information efficiently. The integration of GIS software with other enterprise systems and the development of user-friendly interfaces are key factors propelling the growth of this segment. Furthermore, the rise of mobile GIS applications, which allow field data collectio
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TwitterAs of June 2024, almost a ******* percent of the licenses for spatial database management systems (DBMSs) were open-source licenses. Over the years, open source DBMSs have become more and more popular. As of the evaluated period, open source DBMSs have become as popular as commercial ones.
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According to our latest research, the global spatial database market size reached USD 2.94 billion in 2024, driven by the exponential growth in geospatial data generation and the increasing adoption of location-based services across industries. The market is projected to grow at a robust CAGR of 12.1% from 2025 to 2033, reaching a forecasted value of USD 8.23 billion by 2033. This impressive growth trajectory is primarily fueled by advancements in spatial analytics, the proliferation of IoT devices, and the rising demand for real-time geographic information systems (GIS) in both public and private sectors.
One of the primary growth factors for the spatial database market is the surging demand for advanced geospatial analytics in urban planning and smart city initiatives. As cities across the globe embrace digital transformation, there is an increasing need for sophisticated spatial databases capable of handling complex, multi-dimensional datasets. These databases enable city planners and government agencies to analyze spatial relationships, optimize resource allocation, and improve decision-making processes. The integration of spatial databases with AI and machine learning algorithms further enhances their analytical capabilities, allowing for predictive modeling and real-time visualization of urban dynamics. This has accelerated the adoption of spatial database solutions in both developed and emerging economies, positioning the market for sustained growth over the next decade.
Another significant driver is the rapid expansion of IoT and connected devices, which generate vast volumes of location-based data requiring efficient management and analysis. Industries such as transportation, logistics, and utilities are leveraging spatial databases to track assets, optimize routes, and monitor infrastructure in real time. The ability to process and analyze geospatial data streams from sensors, vehicles, and mobile devices is critical for operational efficiency and risk mitigation. Moreover, the increasing use of spatial databases in environmental monitoring—such as tracking climate change, natural disasters, and resource management—underscores their importance in supporting sustainability initiatives. This trend is further amplified by the growing emphasis on data-driven decision-making across sectors, fueling the demand for scalable and high-performance spatial database solutions.
The adoption of cloud-based spatial database solutions is another pivotal factor contributing to market growth. Cloud deployment offers unparalleled scalability, flexibility, and cost-effectiveness, enabling organizations of all sizes to access and manage spatial data without significant upfront investments in infrastructure. The shift towards cloud-native architectures also facilitates seamless integration with other enterprise applications and data sources, enhancing interoperability and data sharing. This has led to a surge in demand for spatial database-as-a-service (DBaaS) offerings, particularly among small and medium enterprises (SMEs) and organizations with distributed operations. The ongoing advancements in cloud security and data privacy are further encouraging the migration of critical geospatial workloads to the cloud, accelerating the overall expansion of the spatial database market.
From a regional perspective, North America continues to dominate the spatial database market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The region's leadership is attributed to the presence of major technology players, a mature IT infrastructure, and significant investments in smart city and defense projects. However, Asia Pacific is emerging as the fastest-growing market, driven by rapid urbanization, government-led digitalization initiatives, and the increasing adoption of advanced GIS technologies in countries such as China, India, and Japan. The region's robust economic growth and expanding industrial base are expected to create substantial opportunities for spatial database vendors, making it a key focus area for future market expansion.
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The data, codes and queries to accompany the paper "Multipurpose temporal GIS model for cadastral data management". Full details of the designs and use of queries are explained in the paper
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Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.
Our self-hosted GIS data cover administrative and postal divisions with up to 6 precision levels: a zip code layer and up to 5 administrative levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.
The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.
Use cases for the Global Boundaries Database (GIS data, Geospatial data)
In-depth spatial analysis
Clustering
Geofencing
Reverse Geocoding
Reporting and Business Intelligence (BI)
Product Features
Coherence and precision at every level
Edge-matched polygons
High-precision shapes for spatial analysis
Fast-loading polygons for reporting and BI
Multi-language support
For additional insights, you can combine the GIS data with:
Population data: Historical and future trends
UNLOCODE and IATA codes
Time zones and Daylight Saving Time (DST)
Data export methodology
Our geospatial data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson
All GIS data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Why companies choose our map data
Precision at every level
Coverage of difficult geographies
No gaps, nor overlaps
Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.
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PaleoRiada is the first national geographic database that compiles data on palaeoflood records published in scientific journals, book chapters, conference presentations, and publicly accessible scientific-technical reports. This database has been implemented through a Database Management System (Microsoft Access).
Funding:
Grants 2022-2023 and 2023-2026, signed between the Spanish General Directorate for Water (DGA-MITERD) and the Spanish Research Council (CSIC-MCIU), which include actions 20223TE003 and 20233TE012 (Tarquín project in IGME-CSIC).
Community of Madrid (Predoctoral research grant PIPF-2022/ECO-24879)
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TwitterThe geographic data are built from the Technical Information Management System (TIMS). TIMS consists of two separate databases: an attribute database and a spatial database. The attribute information for offshore activities is stored in the TIMS database. The spatial database is a combination of the ARC/INFO and FINDER databases and contains all the coordinates and topology information for geographic features. The attribute and spatial databases are interconnected through the use of common data elements in both databases, thereby creating the spatial datasets. The data in the mapping files are made up of straight-line segments. If an arc existed in the original data, it has been replaced with a series of straight lines that approximate the arc. The Gulf of America OCS Region stores all its mapping data in longitude and latitude format. All coordinates are in NAD 27. Data can be obtained in three types of digital formats: INTERACTIVE MAP: The ArcGIS web maps are an interactive display of geographic information, containing a basemap, a set of data layers (many of which include interactive pop-up windows with information about the data), an extent, navigation tools to pan and zoom, and additional tools for geospatial analysis. SHP: A Shapefile is a digital vector (non-topological) storage format for storing geometric location and associated attribute information. Shapefiles can support point, line, and area features with attributes held in a dBASE format file. GEODATABASE: An ArcGIS geodatabase is a collection of geographic datasets of various types held in a common file system folder, a Microsoft Access database, or a multiuser relational DBMS (such as Oracle, Microsoft SQL Server, PostgreSQL, Informix, or IBM DB2). The geodatabase is the native data structure for ArcGIS and is the primary data format used for editing and data management.
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According to our latest research, the global managed PostGIS services market size reached USD 1.12 billion in 2024, reflecting robust demand across various industries for spatial database management solutions. The market is witnessing a strong growth trajectory, registering a CAGR of 13.4% from 2025 to 2033. By the end of 2033, the managed PostGIS services market is forecasted to achieve a valuation of USD 3.57 billion. This growth is primarily driven by the increasing adoption of geospatial data analytics, the proliferation of location-based services, and a rising emphasis on digital transformation across multiple sectors.
One of the foremost growth factors for the managed PostGIS services market is the surging demand for advanced geospatial analytics and spatial database management. Organizations across industries such as IT & telecom, government, BFSI, and healthcare are increasingly leveraging spatial data to drive business intelligence, optimize operations, and enhance customer engagement. The integration of PostGIS with PostgreSQL offers robust spatial and geographic object support, making it an attractive choice for enterprises seeking scalable and cost-effective solutions. Furthermore, as businesses continue to generate massive volumes of location-based data from IoT devices and mobile applications, the need for managed services that provide seamless database hosting, administration, and security is more pronounced than ever. This trend is expected to fuel sustained market growth over the forecast period.
Another significant driver is the shift towards cloud-based deployment models, which offer flexibility, scalability, and cost efficiencies. Managed PostGIS services delivered via the cloud enable organizations to reduce their IT overhead, streamline database management, and ensure high availability and disaster recovery. Cloud-based solutions also facilitate rapid deployment and integration with other cloud-native applications, supporting the growing trend of digital transformation. Moreover, the rise of hybrid work environments and remote operations has further accelerated the adoption of cloud-managed spatial databases, enabling organizations to manage and analyze geospatial data from anywhere, thereby enhancing operational agility and decision-making capabilities.
The managed PostGIS services market is also benefiting from the increasing focus on data security and regulatory compliance. With the proliferation of sensitive geospatial data, organizations are under pressure to ensure robust security protocols and adherence to data protection regulations. Managed service providers are responding by offering advanced security and compliance solutions, including encryption, access control, and automated backup and recovery. These services not only help organizations mitigate risks but also enable them to focus on their core business objectives without the burden of managing complex database environments. As regulatory requirements continue to evolve, the demand for managed PostGIS services that offer comprehensive security and compliance features is expected to rise.
From a regional perspective, North America currently dominates the managed PostGIS services market, driven by the presence of leading technology companies, high adoption of cloud-based solutions, and a strong focus on innovation. Europe and the Asia Pacific region are also witnessing significant growth, supported by increasing investments in smart city projects, digital infrastructure, and the expansion of the IT & telecom sector. Emerging markets in Latin America and the Middle East & Africa are gradually embracing managed PostGIS services as organizations in these regions recognize the value of spatial data analytics for business growth and operational efficiency. Overall, the global managed PostGIS services market is poised for substantial expansion, with diverse regional dynamics shaping its trajectory.
The service type segment in the managed PostGIS services market is broadly cat
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TwitterExpands the use of internal data for creating Geographic Information System (GIS) maps. SSA's Database Systems division developed a map users guide for GIS data object publishing and was made available in an internal Sharepoint site for access throughout the agency. The guide acts as the reference for publishers of GIS objects across the life-cycle in our single, central geodatabase implementation.
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TwitterThe China Administrative Regions GIS Data: 1:1M, County Level, 1 July 1990 consists of geographic boundary data for the administrative regions of China as of 1 July 1990. The data includes the geographical location, area, administrative division code, and county and island name. The data are at a scale of one to one million (1:1M) at the national, provincial, and county level. This data set is produced in collaboration with the Center for International Earth Science Information Network (CIESIN), Chinese Academy of Surveying and Mapping (CASM), and the University of Washington as part of the China in Time and Space (CITAS) project.
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Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and outdoor recreation access across the nation. This data release (PAD-US 4.1 Vector Analysis and Summary Statistics) presents results from statistical summaries of the PAD-US 4.1 protection status (by GAP Status Code) and public access status for various land unit boundaries. Summary statistics are also available to explore and download from the PAD-US Statistics Dashboard ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-statistics ). The vector GIS analysis file, source data used to summarize statistics for areas of interest to stakeholders (National, State, Department of the Interior Region, Congressional District, County, EcoRegions I-IV, Urban Areas, Landscape Conservation Cooperative), and complete Summary ...
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TwitterNOTE: A more current version of the Protected Areas Database of the United States (PAD-US) is available: PAD-US 2.0 https://doi.org/10.5066/P955KPLE. The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .
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TwitterGADM is a spatial database of the location of the world's administrative areas (or adminstrative boundaries) for use in GIS and similar software. Administrative areas in this database are countries and lower level subdivisions such as provinces, departments, bibhag, bundeslander, daerah istimewa, fivondronana, krong, landsvæðun, opština, sous-préfectures, counties, and thana. GADM describes where these administrative areas are (the "spatial features"), and for each area it provides some attributes, such as the name and variant names.
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Discover the booming cadastral mapping market! This comprehensive analysis reveals an 8% CAGR, reaching $27.38 billion by 2033, driven by technological advancements and increasing government initiatives. Learn about key players, regional trends, and future growth opportunities in land administration.
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Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from workshops that were conducted on February 19-21 and October 6-7, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.
Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.
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Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.
Our self-hosted geospatial data cover administrative and postal divisions with up to 5 precision levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.
The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.
Use cases for the Global Administrative Boundaries Database (Geospatial data, Map data)
In-depth spatial analysis
Clustering
Geofencing
Reverse Geocoding
Reporting and Business Intelligence (BI)
Product Features
Coherence and precision at every level
Edge-matched polygons
High-precision shapes for spatial analysis
Fast-loading polygons for reporting and BI
Multi-language support
For additional insights, you can combine the map data with:
Population data: Historical and future trends
UNLOCODE and IATA codes
Time zones and Daylight Saving Time (DST)
Data export methodology
Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson
All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Why companies choose our map data
Precision at every level
Coverage of difficult geographies
No gaps, nor overlaps
Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.
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North America Geographic Information System Market Size 2025-2029
The geographic information system market size in North America is forecast to increase by USD 11.4 billion at a CAGR of 23.7% between 2024 and 2029.
The market is experiencing significant growth due to the increasing adoption of advanced technologies such as artificial intelligence, satellite imagery, and sensors in various industries. In fleet management, GIS software is being used to optimize routes and improve operational efficiency. In the context of smart cities, GIS solutions are being utilized for content delivery, public safety, and building information modeling. The demand for miniaturization of technologies is also driving the market, allowing for the integration of GIS into smaller devices and applications. However, data security concerns remain a challenge, as the collection and storage of sensitive information requires robust security measures. The insurance industry is also leveraging GIS for telematics and risk assessment, while the construction sector uses GIS for server-based project management and planning. Overall, the GIS market is poised for continued growth as these trends and applications continue to evolve.
What will be the Size of the market During the Forecast Period?
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The Geographic Information System (GIS) market encompasses a range of technologies and applications that enable the collection, management, analysis, and visualization of spatial data. Key industries driving market growth include transportation, infrastructure planning, urban planning, and environmental monitoring. Remote sensing technologies, such as satellite imaging and aerial photography, play a significant role in data collection. Artificial intelligence and the Internet of Things (IoT) are increasingly integrated into GIS solutions for real-time location data processing and operational efficiency.
Applications span various sectors, including agriculture, natural resources, construction, and smart cities. GIS is essential for infrastructure analysis, disaster management, and land management. Geospatial technology enables spatial data integration, providing valuable insights for decision-making and optimization. Market size is substantial and growing, fueled by increasing demand for efficient urban planning, improved infrastructure, and environmental sustainability. Geospatial startups continue to emerge, innovating in areas such as telematics, natural disasters, and smart city development.
How is this market segmented and which is the largest segment?
The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Component
Software
Data
Services
Deployment
On-premise
Cloud
Geography
North America
Canada
Mexico
US
By Component Insights
The software segment is estimated to witness significant growth during the forecast period.
The Geographic Information System (GIS) market encompasses desktop, mobile, cloud, and server software for managing and analyzing spatial data. In North America, industry-specific GIS software dominates, with some commercial entities providing open-source alternatives for limited functions like routing and geocoding. Despite this, counterfeit products pose a threat, making open-source software a viable option for smaller applications. Market trends indicate a shift towards cloud-based GIS solutions for enhanced operational efficiency and real-time location data. Spatial data applications span various sectors, including transportation infrastructure planning, urban planning, natural resources management, environmental monitoring, agriculture, and disaster management. Technological innovations, such as artificial intelligence, the Internet of Things (IoT), and satellite imagery, are revolutionizing GIS solutions.
Cloud-based GIS solutions, IoT integration, and augmented reality are emerging trends. Geospatial technology is essential for smart city projects, climate monitoring, intelligent transportation systems, and land management. Industry statistics indicate steady growth, with key players focusing on product innovation, infrastructure optimization, and geospatial utility solutions.
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Market Dynamics
Our North America Geographic Information System Market researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
What are the key market drivers leading to the rise in the adoption of the North America Geographic Information System Market?
Rising applications of geographic
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TwitterUnited States Bureau of Land Management lands within the Rio Grande River Basin. The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .
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Dataset contains training material on using open source Geographic Information Systems (GIS) to improve protected area planning and management from a workshop that was conducted on August 17-21, 2020. Specifically, the dataset contains lectures on GIS fundamentals, QGIS 3.x, and global positioning system (GPS), as well as country-specific datasets and a workbook containing exercises for viewing data, editing/creating datasets, and creating map products in QGIS. Supplemental videos that narrate a step-by-step recap and overview of these processes are found in the Related Content section of this dataset.
Funding for this workshop and material was funded by the Biodiversity and Protected Areas Management (BIOPAMA) programme. The BIOPAMA programme is an initiative of the Organisation of African, Caribbean and Pacific (ACP) Group of States financed by the European Union's 11th European Development Fund. BIOPAMA is jointly implemented by the International Union for Conservation of Nature {IUCN) and the Joint Research Centre of the European Commission (EC-JRC). In the Pacific region, BIOPAMA is implemented by IUCN's Oceania Regional Office (IUCN ORO) in partnership with the Secretariat of the Pacific Regional Environment Programme (SPREP). The overall objective of the BIOPAMA programme is to contribute to improving the long-term conservation and sustainable use of biodiversity and natural resources in the Pacific ACP region in protected areas and surrounding communities through better use and monitoring of information and capacity development on management and governance.
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Abstract : The search for the most appropriate GIS data model to integrate, manipulate and analyse spatio-temporal data raises several research questions about the conceptualisation of geographic spaces. Although there is now a general consensus that many environmental phenomena require field and object conceptualisations to provide a comprehensive GIS representation, there is still a need for better integration of these dual representations of space within a formal spatio-temporal database. The research presented in this paper introduces a hybrid and formal dual data model for the representation of spatio-temporal data. The whole approach has been fully implemented in PostgreSQL and its spatial extension PostGIS, where the SQL language is extended by a series of data type constructions and manipulation functions to support hybrid queries. The potential of the approach is illustrated by an application to underwater geomorphological dynamics oriented towards the monitoring of the evolution of seabed changes. A series of performance and scalability experiments are also reported to demonstrate the computational performance of the model.Data Description : The data set used in our research is a set of bathymetric surveys recorded over three years from 2009 to 2011 as Digital Terrain Models (DTM) with 2m grid spacing. The first survey was carried out in February 2009 by the French hydrographic office, the second one was recorded on August-September 2010 and the third in July 2011, both by the “Institut Universitaire Européen de la Mer”.