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GIS In Utility Industry Market Size 2025-2029

The gis in utility industry market size is forecast to increase by USD 3.55 billion, at a CAGR of 19.8% between 2024 and 2029.

The utility industry's growing adoption of Geographic Information Systems (GIS) is driven by the increasing need for efficient and effective infrastructure management. GIS solutions enable utility companies to visualize, analyze, and manage their assets and networks more effectively, leading to improved operational efficiency and customer service. A notable trend in this market is the expanding application of GIS for water management, as utilities seek to optimize water distribution and reduce non-revenue water losses. However, the utility GIS market faces challenges from open-source GIS software, which can offer cost-effective alternatives to proprietary solutions. These open-source options may limit the functionality and support available to users, necessitating careful consideration when choosing a GIS solution. To capitalize on market opportunities and navigate these challenges, utility companies must assess their specific needs and evaluate the trade-offs between cost, functionality, and support when selecting a GIS provider. Effective strategic planning and operational execution will be crucial for success in this dynamic market.

What will be the Size of the GIS In Utility Industry Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe Global Utilities Industry Market for Geographic Information Systems (GIS) continues to evolve, driven by the increasing demand for advanced data management and analysis solutions. GIS services play a crucial role in utility infrastructure management, enabling asset management, data integration, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage management, and spatial analysis. These applications are not static but rather continuously unfolding, with new patterns emerging in areas such as energy efficiency, smart grid technologies, renewable energy integration, network optimization, and transmission lines. Spatial statistics, data privacy, geospatial databases, and remote sensing are integral components of this evolving landscape, ensuring the effective management of utility infrastructure. Moreover, the adoption of mobile GIS, infrastructure planning, customer service, asset lifecycle management, metering systems, regulatory compliance, GIS data management, route planning, environmental impact assessment, mapping software, GIS consulting, GIS training, smart metering, workforce management, location intelligence, aerial imagery, construction management, data visualization, operations and maintenance, GIS implementation, and IoT sensors is transforming the industry. The integration of these technologies and services facilitates efficient utility infrastructure management, enhancing network performance, improving customer service, and ensuring regulatory compliance. The ongoing evolution of the utilities industry market for GIS reflects the dynamic nature of the sector, with continuous innovation and adaptation to meet the changing needs of utility providers and consumers.

How is this GIS In Utility Industry Industry segmented?

The gis in utility industry industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductSoftwareDataServicesDeploymentOn-premisesCloudGeographyNorth AmericaUSCanadaEuropeFranceGermanyRussiaMiddle East and AfricaUAEAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW).

By Product Insights

The software segment is estimated to witness significant growth during the forecast period.In the utility industry, Geographic Information Systems (GIS) play a pivotal role in optimizing operations and managing infrastructure. Utilities, including electricity, gas, water, and telecommunications providers, utilize GIS software for asset management, infrastructure planning, network performance monitoring, and informed decision-making. The GIS software segment in the utility industry encompasses various solutions, starting with fundamental GIS software that manages and analyzes geographical data. Additionally, utility companies leverage specialized software for field data collection, energy efficiency, smart grid technologies, distribution grid design, renewable energy integration, network optimization, transmission lines, spatial statistics, data privacy, geospatial databases, GIS services, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage ma

800+ GIS Engineers with 25+ years of experience in geospatial, We provide following as Advance Geospatial Services:

Analytics (AI) Change detection Feature extraction Road assets inventory Utility assets inventory Map data production Geodatabase generation Map data Processing /Classifications
Contour Map Generation Analytics (AI) Change Detection Feature Extraction Imagery Data Processing Ortho mosaic Ortho rectification Digital Ortho Mapping Ortho photo Generation Analytics (Geo AI) Change Detection Map Production Web application development Software testing Data migration Platform development

AI-Assisted Data Mapping Pipeline AI models trained on millions of images are used to predict traffic signs, road markings , lanes for better and faster data processing

Our Value Differentiator

Experience & Expertise -More than Two decade in Map making business with 800+ GIS expertise -Building world class products with our expertise service division & skilled project management -International Brand “Mappls” in California USA, focused on “Advance -Geospatial Services & Autonomous drive Solutions”

Value Added Services -Production environment with continuous improvement culture -Key metrics driven production processes to align customer’s goals and deliverables -Transparency & visibility to all stakeholder -Technology adaptation by culture

Flexibility -Customer driven resource management processes -Flexible resource management processes to ramp-up & ramp-down within short span of time -Robust training processes to address scope and specification changes -Priority driven project execution and management -Flexible IT environment inline with critical requirements of projects

Quality First -Delivering high quality & cost effective services -Business continuity process in place to address situation like Covid-19/ natural disasters -Secure & certified infrastructure with highly skilled resources and management -Dedicated SME team to ensure project quality, specification & deliverables

Geographic Information System (GIS) Software Market Outlook

The global Geographic Information System (GIS) software market size is projected to grow from USD 9.1 billion in 2023 to USD 18.5 billion by 2032, reflecting a compound annual growth rate (CAGR) of 8.5% over the forecast period. This growth is driven by the increasing application of GIS software across various sectors such as agriculture, construction, transportation, and utilities, along with the rising demand for location-based services and advanced mapping solutions.

One of the primary growth factors for the GIS software market is the widespread adoption of spatial data by various industries to enhance operational efficiency. In agriculture, for instance, GIS software plays a crucial role in precision farming by aiding in crop monitoring, soil analysis, and resource management, thereby optimizing yield and reducing costs. In the construction sector, GIS software is utilized for site selection, design and planning, and infrastructure management, making project execution more efficient and cost-effective.

Additionally, the integration of GIS with emerging technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) is significantly enhancing the capabilities of GIS software. AI-driven data analytics and IoT-enabled sensors provide real-time data, which, when combined with spatial data, results in more accurate and actionable insights. This integration is particularly beneficial in fields like smart city planning, disaster management, and environmental monitoring, further propelling the market growth.

Another significant factor contributing to the market expansion is the increasing government initiatives and investments aimed at improving geospatial infrastructure. Governments worldwide are recognizing the importance of GIS in policy-making, urban planning, and public safety, leading to substantial investments in GIS technologies. For example, the U.S. governmentÂ’s Geospatial Data Act emphasizes the development of a cohesive national geospatial policy, which in turn is expected to create more opportunities for GIS software providers.

Geographic Information System Analytics is becoming increasingly pivotal in transforming raw geospatial data into actionable insights. By employing sophisticated analytical tools, GIS Analytics allows organizations to visualize complex spatial relationships and patterns, enhancing decision-making processes across various sectors. For instance, in urban planning, GIS Analytics can identify optimal locations for new infrastructure projects by analyzing population density, traffic patterns, and environmental constraints. Similarly, in the utility sector, it aids in asset management by predicting maintenance needs and optimizing resource allocation. The ability to integrate GIS Analytics with other data sources, such as demographic and economic data, further amplifies its utility, making it an indispensable tool for strategic planning and operational efficiency.

Regionally, North America holds the largest share of the GIS software market, driven by technological advancements and high adoption rates across various sectors. Europe follows closely, with significant growth attributed to the increasing use of GIS in environmental monitoring and urban planning. The Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, fueled by rapid urbanization, infrastructure development, and government initiatives in countries like China and India.

Component Analysis

The GIS software market is segmented into software and services, each playing a vital role in meeting the diverse needs of end-users. The software segment encompasses various types of GIS software, including desktop GIS, web GIS, and mobile GIS. Desktop GIS remains the most widely used, offering comprehensive tools for spatial analysis, data management, and visualization. Web GIS, on the other hand, is gaining traction due to its accessibility and ease of use, allowing users to access GIS capabilities through a web browser without the need for extensive software installations.

Mobile GIS is another crucial aspect of the software segment, providing field-based solutions for data collection, asset management, and real-time decision making. With the increasing use of smartphones and tablets, mobile GIS applications are becoming indispensable for sectors such as utilities, transportation, and

Python Scripting for ArcGIS Pro stars with the fundamentals of Python programming and then dives into how to write useful Python scripts that work with spatial data in ArcGIS Pro. Leam how to execute geoprocessing tools, describe, create and update data, as well as execute a number of specialized tasks. See how to write simple, Custom scripts that will automate your ArcGIS Pro workflows.Some of the key topics you Will learn include:Python fundamentalsSetting up a Python editorAutomating geoprocessing tasksExploring and manipulating spatal and tabular dataWorking With geometriesMap scriptingDebugging ard error handlingHelpful "points to remember," key terms, and review questions are included at the end of each chapter to reinforce your understanding of Python. Corresponding data and exercises are available online.Whether want to learn python or already have some experience, Python Scripting for ArcGlS Pro is comprehensive, hands-on book for learning versatility of Python coding as an approach to solving problems and increasing your productivity in ArcGlS Pro. Follow the step-by-step instruction and common workflow guidance for automating tasks and scripting with Python.Don't forget to also check out Esri Press's other Python title:Advanced Python Scripting for ArcGIS ProAUDIENCEProfessional and scholarly. College/higher education. General/trade.AUTHOR BIOPaul A Zandbergen is an associate professor of geography at the University of New Mexico in Albuquerque. His areas of expertise include geographic information science; spatial and statistical analysis techniques using GIS; error and uncertainty in spatial data; GIS applications in criminology, economics, health, and spatial ecology; terrain analysis and modeling; and community-based mapping using GIS and GPS.Pub Date: Print 7/7/2020 Digital: 7/7/2020ISBN: Print 9781589484993 Digital: 9781589485006 Price: Print: $79.99 USD Digital: $79.99 USD Pages: 420 Trim: 8 x 10 in.Table of ContentsPrefaceAcknowledgmentsChapter 1. Introducing Py%onChapter 2. Working with Python editorsChapter 3. Geoprocessing in ArcGIS ProChapter 4. Leaming Python language fundamentalsChapter 5. Geoprocessing using PythonChapter 6. Exploring spatial dataChapter 7. Debugging and error handlingChapter 8. Manipulating spatial and tabular dataChapter 9. Working with geometriesChapter 10. Working with rastersChapter 11. Map scriptingIndexPython Scripting and Advanced Python Scripting for ArcGIS Pro | Official Trailer | 2020-07-12 | 01:04Paul Zandbergen | Interview with Esri Press | 2020-07-10 | 25:37 | Link.

Can your desktop computer crunch the large GIS datasets that are becoming increasingly common across the geosciences? Do you have access to, or the know how to, take advantage of advanced high performance computing (HPC) capability? Web based cyberinfrastructure takes work off your desk or laptop computer and onto infrastructure or "cloud" based data and processing servers. This talk will describe the HydroShare collaborative environment and web based services being developed to support the sharing and processing of hydrologic data and models. HydroShare supports the storage and sharing of a broad class of hydrologic data including time series, geographic features and rasters, multidimensional space-time data and structured collections of data representing river geometry. Web service tools and a python client library provide researchers with access to high performance computing resources without requiring them to become HPC experts. This reduces the time and effort spent in finding and organizing the data required to prepare the inputs for hydrologic models and facilitates the management of online data and execution of models on HPC systems. This talk will illustrate web and client based use of data services that support the delineation of watersheds to define a modeling domain, then extract terrain and land use information to automatically configure the inputs required for hydrologic models. These services support the Terrain Analysis Using Digital Elevation Model (TauDEM) tools for watershed delineation and generation of hydrology-based terrain information such as wetness index and stream networks. These services also support the derivation of inputs for the Utah Energy Balance snowmelt model used to address questions such as how climate, land cover and land use change may affect snowmelt inputs to runoff generation. These cases serve as examples for how this approach can be extended to other models to enhance the use of web and data services in the geosciences.

Presentation at Kansas University GIS Days November 18, 2015

Satellite observations of night-time emitted lights describe a geography of the spatial distribution of resource use. Measurements of nocturnal lights enable the calculation of the total light emitted from each country of the world, and the light emitted per capita. We consider different groups of countries that share a land or maritime border and whose light per capita can be more equally/unequally distributed. A sharp difference in light per capita among neighboring countries reflects marked differences in economic welfare and in the extent of built environments. We demonstrate how this geography of nocturnal lights informs our understanding of the dynamics of conflict at the national and regional scale. We propose an index of regional disparity and test its ability to detect conflict dynamics by relating the index score with the occurrence and intensity of conflicts as classified by the Heidelberg Institute for International Conflict Research’s Conflict Barometer 2012 for the countries of the world. This method can be used to produce a global available temporal sampling of “cold spots” of disparity where conflicts are likely to occur. This will help foresee the identification and monitoring of regions of the world,which are becoming particularly unstable, assisting in the definition and execution of timely and proactive policies.

Hydrologic models are growing in complexity: spatial representations, model coupling, process representations, software structure, etc. New and emerging datasets are growing, supporting even more detailed modeling use cases. This complexity is leading to the reproducibility crisis in hydrologic modeling and analysis. We argue that moving hydrologic modeling to the cloud can help to address this reproducibility crisis. - We create two notebooks: 1. The first notebook demonstrates the process of collecting and manipulating GIS and Time-series data using GRASS GIS, Python and R to create RHESsys Model input. 2. The second notebook demonstrates the process of model compilation, simulation, and visualization.

• The first notebook includes:

  1. Create Project Directory and Download Raw GIS Data from HydroShare
  2. Set GRASS Database and GISBASE Environment
  3. Preprocessing GIS Data for RHESsys Model using GRASS GIS and R script
  4. Preprocess Time series data for RHESsys Model
  5. Construct worldfile and flowtable to RHESSys

• The second notebook includes:

  1. Download and compile RHESsys Execution file
  2. Simulate RHESsys model
  3. Plotting RHESsys output

The Automated Geospatial Watershed Assessment (AGWA) tool is a GIS-based hydrologic modeling tool that uses commonly available GIS data layers to fully parameterize, execute, and spatially visualize results for the RHEM, KINEROS2, KINEROS-OPUS, SWAT2000, and SWAT2005 watershed runoff and erosion models. Accommodating novice to expert GIS users, it is designed to be used by watershed, water resource, land use, and resource managers and scientists investigating the hydrologic impacts of land-cover/land-use change in small watershed to basin-scale studies. AGWA is currently available as AGWA 1.5 for ArcView 3.x, AGWA 2.x for ArcGIS 9.x, and AGWA 3.X for ArcGIS 10.x. Planning and assessment in land and water resource management are evolving from simple, local-scale problems toward complex, spatially explicit regional ones. Such problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extensive data requirements and the difficult task of building input parameter files, however, have long represented an obstacle to the timely and cost-effective use of such complex models by resource managers. The USDA- ARS Southwest Watershed Research Center, in cooperation with the U.S. EPA Office of Research and Development Landscape Ecology Branch, the University of Arizona, and the University of Wyoming, has developed a GIS tool to facilitate this process. A geographic information system (GIS) provides the framework within which spatially-distributed data are collected and used to prepare model input files and evaluate model results. AGWA uses widely available standardized spatial datasets that can be obtained via the internet. The data are used to develop input parameter files for two watershed runoff and erosion models: KINEROS2 and SWAT.

Geoprocessing service Esri ArcGIS Server - Line Of Sight DMP 1G is a public service intended for visibility analysis execution using the dataset Digital Surface Model of the Czech Republic of the 1st generation (DMP 1G). The geoprocessing service enables to find out, which parts of surface along given line leading from observation to target point are visible. When using the service it is necessary to choose the observation location, choose the target location and specify offset above the surface. The result of the analysis is line of sight (line of visibility) with visible and invisible parts leading on the surface. The geoprocessing service LineOfSight_DMP 1G is distinctly faster in contrast with geoprocessing service Visibility_DMP 1G. The service can be used with advantage for visibility analysis for longer distances.

The geoprocessing service is published as asynchronous. The result can be downloaded from server and saved to a local disc as shapefile using URL, which is generated and sent by the geoprocessing service. URL for the result downloaded throught a web client is published in running service record, that is sent from server to the client.

Hydrologic models are growing in complexity: spatial representations, model coupling, process representations, software structure, etc. New and emerging datasets are growing, supporting even more detailed modeling use cases. This complexity is leading to the reproducibility crisis in hydrologic modeling and analysis. We argue that moving hydrologic modeling to the cloud can help to address this reproducibility crisis. - We create two notebooks: 1. The first notebook demonstrates the process of collecting and manipulating GIS and Time-series data using GRASS GIS, Python and R to create RHESsys Model input. 2. The second notebook demonstrates the process of model compilation, parallel simulation, and visualization.

• The first notebook includes:

  1. Create Project Directory and Download Raw GIS Data from HydroShare
  2. Set GRASS Database and GISBASE Environment
  3. Preprocessing GIS Data for RHESsys Model using GRASS GIS and R script
  4. Preprocess Time series data for RHESsys Model
  5. Construct worldfile and flowtable to RHESSys

• The second notebook includes:

  1. Download and compile RHESsys Execution file
  2. Simulate RHESsys model
  3. Plotting RHESsys output

Geoprocessing service Esri ArcGIS Server - Visibility_DMR 5G is a public service intended for visibility analysis execution using the dataset Digital Terrain Model of the Czech Republic of the 5th generation (DMR 5G). Geoprocessing service enables to find out, which area is visible from chosen observer location to defined distance. When using the service is necessary to choose the observer location, pecify oberver offset above the terrain and define the distance, in which the visibility analysis is demanded. The result of the analysis is visibility field (area) represented by polygons, which delimit visible parts of the terrain. The geoprocessing service is published as asynchronous. The result is passed on client throught Result Map Service Visibility_DMR 5G (MapService). The result can be downloaded from server and saved to a local disc as shapefile using URL, which is generated and sended by the geoprocessing service. URL for the result download throught a web client is published in running service record, that is sent from server to the client.

Geoprocessing service Esri ArcGIS Server - SkyLineGraph_DMR 4G is a public service intended for visibility analysis execution using the dataset Digital Terrain Model of the Czech Republic of the 4th generation (DMR 4G). Geoprocessing service enables to find out, which area is visible from chosen observer location to defined distance. When using the service is necessary to choose the observer location, specify oberver offset above the terrain and define the distance, in which the visibility analysis is demanded. The result of the analysis is visibility field (area) represented by polygons, which delimit visible parts of the terrain. The geoprocessing service is published as asynchronous. The result is passed on client throught Result Map Service Visibility_DMR 4G (MapService). The result can be downloaded from server and saved to a local disc as shapefile using URL, which is generated and sended by the geoprocessing service. URL for the result download throught a web client is published in running service record, that is sent from server to the client.

Geospatial data about Jackson County, Missouri Circuit Court Execution Zones. Export to CAD, GIS, PDF, CSV and access via API.

The RTK (Real-Time Kinematic) Survey Systems market, valued at $783 million in 2025, is poised for robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 5.9% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the increasing adoption of precise positioning technologies across various sectors, including land and resources management, urban planning and construction, and mineral resource exploration, fuels demand. The rising complexity of infrastructure projects and the need for accurate data for efficient planning and execution further contribute to market growth. Technological advancements, such as the development of more accurate and reliable dual-frequency RTK systems, are also significantly impacting the market. Furthermore, the increasing integration of RTK systems with other technologies like GIS (Geographic Information Systems) and drones enhances their functionality and appeal across various applications. Governments' increasing focus on infrastructure development and smart city initiatives in developing economies like those in Asia-Pacific creates significant growth opportunities. However, market growth may be somewhat tempered by certain restraining factors. The high initial investment cost associated with RTK equipment and the requirement for skilled personnel to operate the systems could limit wider adoption, especially among small and medium-sized enterprises (SMEs). Furthermore, the potential impact of economic downturns on infrastructure spending could also temporarily slow market growth. Nonetheless, the long-term outlook for the RTK Survey Systems market remains positive, driven by continuous technological advancements and expanding applications across various industries. The market segmentation by application (Land and Resources Management, Urban Planning and Construction, Roads and Bridges, Mineral Resources, Others) and type (Single-Frequency RTK, Dual-Frequency RTK) provides further insights into market dynamics and allows for tailored strategies to penetrate specific niche markets. Competition amongst established players like Leica (Hexagon), Trimble, and FARO, as well as emerging companies from China, is expected to remain intense, driving innovation and pricing pressures. This in-depth report provides a comprehensive analysis of the global RTK Survey Systems market, projecting a multi-million-unit market by 2033. We delve into market dynamics, competitive landscapes, and future growth trajectories, offering invaluable insights for stakeholders across the industry. The study covers the historical period (2019-2024), base year (2025), and forecast period (2025-2033), leveraging extensive data analysis to deliver actionable intelligence. Keywords: RTK GPS, Real-Time Kinematic, GNSS Surveying, Surveying Equipment, Land Surveying, GIS, Mapping, Positioning Systems, Precision Agriculture.

Hydrologic models are growing in complexity: spatial representations, model coupling, process representations, software structure, etc. New and emerging datasets are growing, supporting even more detailed modeling use cases. This complexity is leading to the reproducibility crisis in hydrologic modeling and analysis. We argue that moving hydrologic modeling to the cloud can help to address this reproducibility crisis. - We create two notebooks: 1. The first notebook demonstrates the process of collecting and manipulating GIS and Time-series data using GRASS GIS, Python and R to create RHESsys Model input. 2. The second notebook demonstrates the process of model compilation, parallel simulation, and visualization.

• The first notebook includes:

  1. Create Project Directory and Download Raw GIS Data from HydroShare
  2. Set GRASS Database and GISBASE Environment
  3. Preprocessing GIS Data for RHESsys Model using GRASS GIS and R script
  4. Preprocess Time series data for RHESsys Model
  5. Construct worldfile and flowtable to RHESSys

• The second notebook includes:

  1. Download and compile RHESsys Execution file
  2. Simulate RHESsys model
  3. Plotting RHESsys output

3D Mapping Management Software Market Outlook

The global market size of 3D Mapping Management Software was valued at USD 4.2 billion in 2023 and is forecasted to reach USD 12.6 billion by 2032, growing at an impressive CAGR of 13.2% during the forecast period. This remarkable growth can be attributed to increased urbanization, technological advancements, and the rising adoption of 3D visualization in various industries.

The proliferation of smart city projects worldwide is a significant growth driver for the 3D Mapping Management Software market. Governments and urban planners are increasingly leveraging this technology to create accurate and detailed 3D maps for better planning and management of urban spaces. These maps assist in visualizing infrastructure, zoning, and landscape features, thus enabling more efficient and sustainable city planning. The technology's capability to integrate various data sources, such as satellite imagery, LiDAR data, and GIS, enhances its utility and application range, further fueling market growth.

Another major growth factor is the increasing need for disaster management and mitigation solutions. With climate change leading to more frequent and severe natural disasters, the demand for advanced tools to predict, simulate, and manage such events is on the rise. 3D Mapping Management Software offers robust solutions for simulating disaster scenarios, mapping vulnerable areas, and planning emergency responses. The ability to visualize and analyze complex geographical data in three dimensions provides a significant advantage in planning and executing disaster management strategies, thereby driving market demand.

Infrastructure development projects, particularly in emerging economies, are also propelling the 3D Mapping Management Software market. The construction sector is increasingly adopting 3D mapping for project planning, design, and management. These tools enable the creation of accurate and detailed 3D models of construction sites, which help in visualizing the project from different angles, identifying potential issues, and improving overall efficiency. Additionally, asset management within the infrastructure sector benefits greatly from 3D mapping, as it allows for precise tracking and maintenance planning of various assets.

The development and utilization of High-Precision 3D Map technology are becoming increasingly crucial in the realm of urban planning and infrastructure management. These maps provide an unparalleled level of detail and accuracy, which is essential for the meticulous planning and execution of large-scale projects. By offering a comprehensive view of the terrain and existing structures, high-precision 3D maps enable planners and engineers to make informed decisions that enhance the efficiency and sustainability of urban development. This technology is particularly beneficial in the context of smart city initiatives, where the integration of precise mapping data can significantly improve the management of resources and services.

In terms of regional outlook, North America holds a significant share in the 3D Mapping Management Software market. The presence of numerous leading technology companies and widespread adoption of advanced mapping solutions in various sectors drive the market in this region. Additionally, Europe and Asia Pacific are expected to witness substantial growth due to increasing investments in smart city projects, infrastructure development, and disaster management initiatives. The rapid urbanization in Asia Pacific, coupled with government initiatives promoting advanced mapping technologies, makes it a lucrative market for 3D mapping solutions.

Component Analysis

The 3D Mapping Management Software market can be segmented by component into Software and Services. The software segment dominates the market, driven by the increasing adoption of advanced 3D mapping software solutions across various industries. These software solutions offer a range of functionalities, including data integration, visualization, simulation, and analysis. Continuous advancements in software capabilities, such as real-time data processing and AI integration, further enhance their appeal, leading to higher adoption rates.

The services segment, although smaller than the software segment, is witnessing steady growth. This segment includes consulting, implementation, training, and support services. As organizations increasingly adopt 3D mapping softw

The creation of the subsequent building footprint data was executed to capture the existing ground conditions at a specific point in time using Stereo Imagery for the purpose of GIS analysis. GIS is a system of computer software, hardware, and data that allows a user to manipulate, analyze, and present information that is tied to a spatial location. Sauk contracted with the Sanborn Map Company to execute a collection of various buildings types that meet contract requirements.

Hydrologic models are growing in complexity: spatial representations, model coupling, process representations, software structure, etc. New and emerging datasets are growing, supporting even more detailed modeling use cases. This complexity is leading to the reproducibility crisis in hydrologic modeling and analysis. We argue that moving hydrologic modeling to the cloud can help to address this reproducibility crisis. - We create two notebooks: 1. The first notebook demonstrates the process of collecting and manipulating GIS and Time-series data using GRASS GIS, Python and R to create RHESsys Model input. 2. The second notebook demonstrates the process of model compilation, parallel simulation, and visualization.

• The first notebook includes:

  1. Create Project Directory and Download Raw GIS Data from HydroShare
  2. Set GRASS Database and GISBASE Environment
  3. Preprocessing GIS Data for RHESsys Model using GRASS GIS and R script
  4. Preprocess Time series data for RHESsys Model
  5. Construct worldfile and flowtable to RHESSys

• The second notebook includes:

  1. Download and compile RHESsys Execution file
  2. Simulate RHESsys model
  3. Plotting RHESsys output

The aerial photography and creation of the subsequent contour data was executed to capture the existing ground conditions at a specific point in time for the purpose of GIS analysis. VGIN sub-contracted with the Sanborn Map Company to execute a Statewide mapping contract in the years 2009 to 2012. The 4 foot contours were produced as part of the 2011 orthophotography update cycle of the Virginia Geographic Information Network's (VGIN) Virginia Base Mapping Program (VBMP). Contours were provided to jurisdictions who chose to use the upgrade option for contour generation. The contours are provided in File Geodatabase format.

CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) is a large-sample hydrometeorological dataset that provides catchment attributes, forcings and GIS data for 671 small- to medium-sized basins across the CONUS (continental United States). HydroShare hosts a copy of CAMELS and exposes it through different public data access protocols (WMS, WFS and OPeNDAP) for easy visualization and subsetting of the dataset in community modeling research. This notebook demostrates how to set up SUMMA models with CAMELS dataset from HydroShare using various tools integrated in the CyberGIS-Jupyter for Water (CJW) environment and execution of ensemble model runs on a supported High-Performance Computing (HPC) resource (XSEDE Comet or UIUC Virtual Roger) through CyberGIS-Compute Service.

How to run the notebook: 1) Click on the OpenWith button in the upper-right corner; 2) Select "CyberGIS-Jupyter for Water"; 3) Open the notebook and follow instructions;