In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

This resource contains data inputs and a Jupyter Notebook that is used to introduce Hydrologic Analysis using Terrain Analysis Using Digital Elevation Models (TauDEM) and Python. TauDEM is a free and open-source set of Digital Elevation Model (DEM) tools developed at Utah State University for the extraction and analysis of hydrologic information from topography. This resource is part of a HydroLearn Physical Hydrology learning module available at https://edx.hydrolearn.org/courses/course-v1:Utah_State_University+CEE6400+2019_Fall/about

In this activity, the student learns how to (1) derive hydrologically useful information from Digital Elevation Models (DEMs); (2) describe the sequence of steps involved in mapping stream networks, catchments, and watersheds; and (3) compute an approximate water balance for a watershed-based on publicly available data.

Please note that this exercise is designed for the Logan River watershed, which drains to USGS streamflow gauge 10109000 located just east of Logan, Utah. However, this Jupyter Notebook and the analysis can readily be applied to other locations of interest. If running the terrain analysis for other study sites, you need to prepare a DEM TIF file, an outlet shapefile for the area of interest, and the average annual streamflow and precipitation data. - There are several sources to obtain DEM data. In the U.S., the DEM data (with different spatial resolutions) can be obtained from the National Elevation Dataset available from the national map (http://viewer.nationalmap.gov/viewer/). Another DEM data source is the Shuttle Radar Topography Mission (https://www2.jpl.nasa.gov/srtm/), an international research effort that obtained digital elevation models on a near-global scale (search for Digital Elevation at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-products-overview?qt-science_center_objects=0#qt-science_center_objects). - If not already available, you can generate the outlet shapefile by applying basic terrain analysis steps in geospatial information system models such as ArcGIS or QGIS. - You also need to obtain average annual streamflow and precipitation data for the watershed of interest to assess the annual water balance and calculate the runoff ratio in this exercise. In the U.S., the streamflow data can be obtained from the USGS NWIS website (https://waterdata.usgs.gov/nwis) and the precipitation from PRISM (https://prism.oregonstate.edu/normals/). Note that using other datasets may require preprocessing steps to make data ready to use for this exercise.

This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

LANDISVIEW is a tool, developed at the Knowledge Engineering Laboratory at Texas A&M University, to visualize and animate 8-bit/16-bit ERDAS GIS format (e.g., LANDIS and LANDIS-II output maps). It can also convert 8-bit/16-bit ERDAS GIS format into ASCII and batch files. LANDISVIEW provides two major functions: 1) File Viewer: Files can be viewed sequentially and an output can be generated as a movie file or as an image file. 2) File converter: It will convert the loaded files for compatibility with 3rd party software, such as Fragstats, a widely used spatial analysis tool. Some available features of LANDISVIEW include: 1) Display cell coordinates and values. 2) Apply user-defined color palette to visualize files. 3) Save maps as pictures and animations as video files (*.avi). 4) Convert ERDAS files into ASCII grids for compatibility with Fragstats. (Source: http://kelab.tamu.edu/)

The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

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Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics 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.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector, gover

Bolton & Menk, an engineering planning and consulting firm from the Midwestern United States has released a series of illustrated children’s books as a way of helping young people discover several different professions that typically do not get as much attention as other more traditional ones do.Topics of the award winning book series include landscape architecture, civil engineering, water resource engineering, urban planning and now Geographic Information Systems (GIS). The books are available free online in digital format, and easily accessed via a laptop, smart phone or tablet.The book Lindsey the GIS Specialist – A GIS Mapping Story Tyler Danielson, covers some the basics of what geographic information is and the type of work that a GIS Specialist does. It explains what the acronym GIS means, the different types of geospatial data, how we collect data, and what some of the maps a GIS Specialist creates would be used for.Click here to check out the GIS Specialist – A GIS Mapping Story e-book

This web map references the live tiled map service from the OpenStreetMap project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information such as free satellite imagery, and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: http://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in Esri products under a Creative Commons Attribution-ShareAlike license.Tip: This service is one of the basemaps used in the ArcGIS.com map viewer and ArcGIS Explorer Online. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10.

Geographic Information System (GIS) Software Market Outlook

According to our latest research, the global Geographic Information System (GIS) Software market size reached USD 11.6 billion in 2024, reflecting a robust demand for spatial data analytics and location-based services across various industries. The market is experiencing a significant growth trajectory, driven by a CAGR of 12.4% from 2025 to 2033. By the end of 2033, the GIS Software market is forecasted to attain a value of USD 33.5 billion. This remarkable expansion is primarily attributed to the integration of advanced technologies such as artificial intelligence, IoT, and cloud computing, which are enhancing the capabilities and accessibility of GIS platforms.

One of the major growth factors propelling the GIS Software market is the increasing adoption of location-based services across urban planning, transportation, and utilities management. Governments and private organizations are leveraging GIS solutions to optimize infrastructure development, streamline resource allocation, and improve emergency response times. The proliferation of smart city initiatives worldwide has further fueled the demand for GIS tools, as urban planners and municipal authorities require accurate spatial data for effective decision-making. Additionally, the evolution of 3D GIS and real-time mapping technologies is enabling more sophisticated modeling and simulation, expanding the scope of GIS applications beyond traditional mapping to include predictive analytics and scenario planning.

Another significant driver for the GIS Software market is the rapid digitization of industries such as agriculture, mining, and oil & gas. Precision agriculture, for example, relies heavily on GIS platforms to monitor crop health, manage irrigation, and enhance yield forecasting. Similarly, the mining sector uses GIS for exploration, environmental impact assessment, and asset management. The integration of remote sensing data with GIS software is providing stakeholders with actionable insights, leading to higher efficiency and reduced operational risks. Furthermore, the growing emphasis on environmental sustainability and regulatory compliance is prompting organizations to invest in advanced GIS solutions for monitoring land use, tracking deforestation, and managing natural resources.

The evolution of 3D GIS is revolutionizing the way spatial data is visualized and analyzed, offering a more immersive and detailed perspective of geographic information. This technology allows for the creation of three-dimensional models that provide a realistic representation of urban landscapes, infrastructure, and natural environments. By integrating 3D GIS with real-time data feeds, organizations can enhance their spatial analysis capabilities, enabling more accurate simulations and predictions. This advancement is particularly beneficial for urban planners and architects who require detailed visualizations to assess the impact of new developments and infrastructure projects. Moreover, 3D GIS is facilitating better communication and collaboration among stakeholders by providing a common platform for visualizing complex spatial data.

The expanding use of cloud-based GIS solutions is also a key factor driving market growth. Cloud deployment offers scalability, cost-effectiveness, and remote accessibility, making GIS tools more accessible to small and medium enterprises as well as large organizations. The cloud model supports real-time data sharing and collaboration, which is particularly valuable for disaster management and emergency response teams. As organizations increasingly prioritize digital transformation, the demand for cloud-native GIS platforms is expected to rise, supported by advancements in data security, interoperability, and integration with other enterprise systems.

Regionally, North America remains the largest market for GIS Software, accounting for a significant share of global revenues. This leadership is underpinned by substantial investments in smart infrastructure, advanced transportation systems, and environmental monitoring programs. The Asia Pacific region, however, is witnessing the fastest growth, driven by rapid urbanization, government-led digital initiatives, and the expansion of the utility and agriculture sectors. Europe continues to demonstrate steady adoption, particularly in environmental manage

Snapshot img

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.

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

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 geographi

An attempt to collect, format, analyse and disseminate surveyed marine biological data deriving from the Eastern Mediterranean and Black Sea region is currently under development at the Hellenic Center for Marine Research (HCMR, Greece). The effort has been supported by the MedOBIS project (Mediterranean Ocean Biogeographic Information System) and has been carried out in cooperation with the Aristotelian University of Thessaloniki (Greece), the National Institute of Oceanography (Israel) and the Institute of Biology of the Southern Seas (Ukraine).

    The aim is to develop a taxon-based biogeography database and online data server with a link to survey and provide satellite environmental data. Currently, the primary features of the MedOBIS application are its offline GIS data formatting capabilities and its online Java and JavaScript enabling data server with taxon-based search, mapping and data downloading capabilities. In its completion, the MedOBIS online marine biological data system (http://www.iobis.org/OBISWEB/ObisDynPage1.jsp?content=meta/42.html) will be a single source of biological and environmental data (raw and analysed) as well as an online GIS tool for access of historical and current data by marine researchers. It will function as the Eastern Mediterranean and Black Sea node of EurOBIS (the European node of the International OBIS initiative, part of the Census of Marine Life).

    INTRODUCTION

    The international and interdisciplinary nature of the biological degradation issue as well as the technological advances of the Internet capabilities allowed the development of a considerable number of interrelated online databases. The free dissemination of valuable historical and current biological, environmental and genetic information has contributed to the establishment of an interdisciplinary platform targeted towards information integration at regional and also at global scales and to the development of information-based management schemes about our common interest.

    The spatial component of these data has led to the integration of the information by means of the Geographic Information System (GIS) technology. The latter is widely used as the natural framework for spatial data handling (Wright & Bartlett 1999, Valavanis 2002). GIS serves as the basic technological infrastructure for several online marine biodiversity databases available on the Internet today. Developments like OBIS (Ocean Biogeographic Information System, "http://www.iobis.org/"), OBIS-SEAMAP (Spatial Ecological Analysis of Megavertebrate Populations, "http://seamap.env.duke.edu/") and FIGIS (FAO Fisheries Global Information System, http://www.fao.org/fishery/figis) facilitate the study of anthropogenic impacts on threatened species, enhance our ability to test biogeographic and biodiversity models, support modelling efforts to predict distribution changes in response to environmental change and develop a strong potential for the public outreach component. In addition, such online database systems provide a broader view of marine biodiversity problems and allow the development of management practices that are based on synthetic analysis of interdisciplinary data (Schalk 1998, Decker & O'Dor 2002, Tsontos & Kiefer 2002).

    Towards this end, a development of a new online marine biological information system is presented here in its initial phase. MedOBIS (Mediterranean Ocean Biogeographic Information System) intends to assemble, formulate and disseminate marine biological data for the Eastern Mediterranean and Black Sea regions focusing on the assurance and longevity of historical surveyed data, the assembly of current and new information and the dissemination of raw and integrated biological and environmental data and future products through the Internet.

    MedOBIS DESCRIPTION

    MedOBIS current development consists of four main phases (Fig. 1). The data assembly phase is based on the free contribution of biological data from various national and international scientific surveys in the region. The data formatting phase is based on a GIS (ESRI, 1994), under which the geographic location of data stations is used to convert station data and their attributes to GIS shapefiles. The data analysis phase is based on data integration through GIS and spatial analyses (e.g. species distribution maps, species-environment relations, etc). Finally, the dissemination phase is based on ALOV Map, a free portable Java application for publication of vector and raster maps to the Internet and interactive viewing on web browsers. It supports navigation and search capabilities and allows working with multiple layers, thematic maps, hyperlinked features and attributed data.

    During the on-going data assembly phase, a total number of 776 stations with surveyed benthic biological data was employed. These data include mainly benthic species abundance (for nearly 3000 benthic organisms), benthic substrate types and several environmental parameters. Currently, 100 stations have been assembled for the Ionian Sea, 570 stations for the Aegean Sea and 106 stations for the Black Sea. The temporal resolution of these data extends for the period 1937-2000 while most data cover the period 1986-1996. Additionally, monthly satellite images of sea surface temperature (SST) and chlorophyll (Chl-a) were assembled for the period 1998-2003. Satellite data were obtained from the Advanced Very High Resolution Radiometer (AVHRR SST) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS Chl-a). 

    During the data formatting phase, all assembled surveyed stations were converted to a GIS shapefile (Fig. 2). This GIS information layer includes the geographic coordinates of the stations as well as stations' identification number. Station data attributes were organised in an MS Access Database while satellite data were embedded in a GIS database as GIS regular grids. The MedOBIS data analysis phase is still at the initial stage. Several off line analytical published efforts (e.g. Arvanitidis et al. 2002, Valavanis et al. 2004a,b,c) will be included in the MedOBIS development, which mainly focus on species distribution maps, mapping of productive oceanic processes and species-environment interactions. 

    The MedOBIS dissemination phase ("http://www.medobis.org/") is based on ALOV Map ("http://www.alov.org/"), a joint project of ALOV Software and the Archaeological Computing Laboratory, University of Sydney, Australia. ALOV Map is a Java-based application for publication of GIS data on the Internet and interactive viewing on web browsers. ALOV Map is designed to display geographical information stored in shapefiles or in any SQL database or even in an XML (Extensible Markup Language) document serving as a database. MedOBIS uses ALOV Map's full capabilities and runs in a client-server mode (Fig. 3). ALOV Map is connected to an MS Access database via a servlet container. This architecture was needed to connect the biological data with the spatial data and facilitate search options, such as, which species are found at which stations. Additionally, a JavaScript code is invoked, which searches the data, pops up a window with the results and then shows the relevant stations on the map.

    To provide a taxon-based search capability to the MedOBIS development, the sampling data as well as the relevant spatial data are stored in the database, so taxonomic data can be linked with the geographical data by SQL (Structured Query Language) queries. To reference each species to its location on the map, the database queries are stored and added to the applet as individual layers. A search function written in JavaScript searches the attribute data of that layer, displays the results in a separate window and marks the matching stations on the map (Fig. 4). Finally, selecting several stations by drawing a zooming rectangle on the map provides a list with predefined themes from which the user may select more information (Fig. 5). 

    CURRENT LIMITATIONS AND FUTURE PLANS

    A disadvantage of embedding information from the database as a layer is the relatively long download time due to the current MedOBIS-ALOV Map client-server architecture. An appropriate solution would be a direct search on the server side, which will allow partial data downloading to the client side. This work will be embedded in the MedOBIS application in the future (client-side architecture), when the size of assembled data becomes relatively 'heavy' for the current client-server architecture. This is an on-going process, since the MedOBIS initiative has been endorsed by the "Excellence of the Institute of Marine Biology of Crete (IMBC) in Marine Biodiversity", a Hellenic National Project that has been evaluated and approved by European experts. As more data will be assembled in time-series databases, an additional future work will include the development of MedOBIS data analysis phase, which is planned to include GIS modelling/mapping of species-environment interactions.

    Size reference: 2953 species; 776 stations

    [Source: The information provided in the summary was extracted from the MarBEF Data System at "http://www.marbef.org/data/eurobisproviders.php"]

In this asynchronous session, you will use some of the free GIS tools from the Teach With GIS website, created and maintained by the Esri UK education team. All of these tools are free to use and accessible as websites from laptops, tablets and mobile devices. We recommend that you view them on a laptop or tablet if possible, to give you plenty of screen space to see every detail. They do not require any logins or subscriptions. We want you to experience using modern, online GIS tools from the perspective of a student before you begin to create your own tools, maps, and lessons. We have chosen a range of tools that let you experience GIS as a tool to examine physical and human geography, and to compare and contrast over space and time.

THE EARTH SCIENCE GEOINQUIRY COLLECTION

http://www.esri.com/geoinquiries

To support Esri’s involvement in the White House ConnectED Initiative, GeoInquiry instructional materials using ArcGIS Online for Earth Science education are now freely available.

The Earth Science GeoInquiry collection contains 15 free, web-mapping activities that correspond and extend map-based concepts in leading middle school Earth science textbooks. The activities use a standard inquiry-based instructional model, require only 15 minutes for a teacher to deliver, and are device agnostic. The activities harmonize with the Next Generation Science Standards. Activity topics include:

Teachers, GeoMentors, and administrators can learn more at http://www.esri.com/geoinquiries

In this course, you will learn to work within the free and open-source R environment with a specific focus on working with and analyzing geospatial data. We will cover a wide variety of data and spatial data analytics topics, and you will learn how to code in R along the way. The Introduction module provides more background info about the course and course set up. This course is designed for someone with some prior GIS knowledge. For example, you should know the basics of working with maps, map projections, and vector and raster data. You should be able to perform common spatial analysis tasks and make map layouts. If you do not have a GIS background, we would recommend checking out the West Virginia View GIScience class. We do not assume that you have any prior experience with R or with coding. So, don't worry if you haven't developed these skill sets yet. That is a major goal in this course. Background material will be provided using code examples, videos, and presentations. We have provided assignments to offer hands-on learning opportunities. Data links for the lecture modules are provided within each module while data for the assignments are linked to the assignment buttons below. Please see the sequencing document for our suggested order in which to work through the material. After completing this course you will be able to: prepare, manipulate, query, and generally work with data in R. perform data summarization, comparisons, and statistical tests. create quality graphs, map layouts, and interactive web maps to visualize data and findings. present your research, methods, results, and code as web pages to foster reproducible research. work with spatial data in R. analyze vector and raster geospatial data to answer a question with a spatial component. make spatial models and predictions using regression and machine learning. code in the R language at an intermediate level.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Point Sur to Point Arguello map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Point Sur to Point Arguello map area data layers. Data layers are symbolized as shown on the associated map sheets.

To do more than the very basics of GIS you will need to sign up for a FREE Schools ArcGIS Online subscription. To sign up for a subscription contact gisinschools@eagle.co.nz

The Cumberland County GIS Data Viewer provides the general public with parcel, zoning, hydrology, soils, utilities and topographic data. You can search for a specific address, street name, parcel number (PIN), or by the owner's name.

GIS Online Moisture Sensor Market Outlook

According to our latest research, the global GIS online moisture sensor market size reached USD 1.12 billion in 2024, reflecting robust adoption across key sectors such as agriculture, environmental monitoring, and industrial process control. The market is projected to grow at a CAGR of 8.7% from 2025 to 2033, reaching an estimated value of USD 2.43 billion by 2033. This impressive growth is primarily driven by the increasing demand for precision agriculture, advancements in sensor technologies, and the growing need for real-time environmental data to support sustainable resource management.

One of the primary growth factors fueling the GIS online moisture sensor market is the surging adoption of precision agriculture techniques worldwide. Farmers and agribusinesses are increasingly leveraging advanced moisture sensing technologies integrated with GIS platforms to monitor soil conditions, optimize irrigation schedules, and enhance crop yields. The ability to access real-time moisture data remotely has transformed traditional farming practices, allowing for data-driven decisions that conserve water and reduce operational costs. This trend is further supported by government initiatives and subsidies promoting smart farming solutions, particularly in regions facing water scarcity or climate variability. As a result, the integration of GIS and online moisture sensors has become a cornerstone in the modernization of agricultural operations, driving sustained market expansion.

Another significant driver for the GIS online moisture sensor market is the escalating focus on environmental monitoring and industrial process control. Industries such as construction, mining, and manufacturing are increasingly required to adhere to stringent environmental regulations, necessitating continuous monitoring of moisture levels in soil, air, and materials. GIS-enabled online moisture sensors provide accurate, location-based data that supports compliance, risk management, and process optimization. In addition, the proliferation of smart city initiatives and the expansion of IoT infrastructure have amplified the deployment of these sensors in urban planning, flood prediction, and infrastructure maintenance. The convergence of GIS and online sensor technologies enables seamless data visualization and analysis, making them indispensable tools for both public and private sector stakeholders.

Technological advancements in sensor design and connectivity are also playing a pivotal role in the market's growth trajectory. Innovations such as wireless and cloud-connected moisture sensors, improved accuracy through advanced materials, and miniaturization have broadened the scope of applications. These advancements have resulted in more cost-effective, durable, and easy-to-deploy solutions, fostering adoption across diverse end-user segments. Furthermore, the integration of AI and machine learning algorithms with GIS platforms is enabling predictive analytics and automated decision-making, further enhancing the value proposition of online moisture sensors. As the demand for actionable insights and real-time monitoring continues to rise, the GIS online moisture sensor market is poised for sustained innovation and expansion.

Regionally, North America and Europe are leading the market, driven by early adoption of precision agriculture, robust regulatory frameworks, and substantial investments in R&D. Asia Pacific, however, is emerging as the fastest-growing region, propelled by rapid urbanization, increasing awareness of sustainable agricultural practices, and government support for smart farming initiatives. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as industries in these regions recognize the benefits of GIS-enabled moisture monitoring for resource optimization and environmental management. Overall, the global market is characterized by dynamic regional trends, with each geography contributing uniquely to the market's evolution.

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