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The human brain doesn’t work in rows and columns Our brains often organize information based on time and place. But for many organizations, information is still confined to rows and columns.
This makes reporting fast and easy—but not necessarily more insightful.
Geospatial analytics adds timing and location to traditional types of data and this additional context allows for a more complete picture of events , creating maps that show changes over time and exactly where those changes are taking place. Insights that might have been lost in a massive spreadsheet are revealed in easy-to-recognize visual patterns and images. Maps make it easier for the eye to recognize patterns that were previously buried in spreadsheets, such as distance, proximity, contiguity, and affiliation.
Geospatial analytics uses data from all kinds of technology — GPS, location sensors, social media, mobile devices, satellite imagery Today’s technologies—GPS, mobile devices, location sensors, social media, satellite imagery and more—allow organizations to collect time and place (“geo-referenced”) data about practically any event. Geospatial analysis uses this data to — to build data visualizations for understanding phenomena and finding trends in complex relationships between people and places.
The visualizations can include maps, graphs, statistics, and cartograms, making complex relationships understandable. Representations like these can reveal historical shifts, as well as that underway today. They can even point to those that are likely to occur in the future. This can make predictions easier and more accurate.
Location-based analysis can help decision-makers understand why solutions that work in one place often fail in another. It can also help them understand the locational aspects that influence broader trends and may have future consequences.
Geospatial analytics companies are able to instantly process huge amounts of geographic and geometric data. This gives users the ability to interact with billions of mapped points while looking at real-time geospatial visualizations. Users can explore data across time and space to instantly see how something has changed from days to years
Geospatial big data analytics breaks data out of the endless rows and columns of a traditional spreadsheet and organizes it visually by time and space. It is easier for the human brain to absorb information this way. Geospatial data analytics lets the eye recognize patterns like distance, proximity, contiguity and affiliation that are hidden in massive datasets. The visualization of spatial data also makes it easier to see how things are changing over time and where the change is most pronounced.
Benefits of geospatial analytics include:
- Engaging insights — Seeing data in the context of a visual map makes it easier to understand how events are unfolding and how to react to those events.
- Better foresight — Seeing how spatial conditions are changing in real time can help an organization better prepare for change and determine future action.
- Targeted solutions — Seeing location-based data helps organizations understand why some locations and countries, such as the United States, are more successful for business than others.
Geospatial Imagery Analytics
Geospatial imagery analytics provides video and image data of the earth – also referred to as earth analytics. Companies in many sectors use the data to determine future risk and contingency plans.
Geospatial imagery analytics uses data collected from satellite images. The geo-referenced images are then presented as raster and vector images. Raster images are individual pixels of color, also known as bitmaps. Vector images are graphics comprised of mathematical formulas and can be infinitely scaled.
Geospatial imagery analytics is most often used for examining climate conditions, urban planning and disaster response management.
There are five markets in geospatial imagery analytics:
- Imaging — segmented into video and image.
- Technology — segmented into GPS, GIS analysis, remote sensing (RS) and unmanned aerial vehicles (UAVS).
- Analysis — segmented into surface analysis, network analysis and geovisualization.
- Application — segmented into agriculture, defense / security, energy analytics / energy business intelligence, engineering / construction, environment-monitoring, government data analytics, healthcare, insurance, mining/manufacturing, natural resources.
- Geography — segmented into Asia-Pacific, Europe, North America and Rest of the World (RoW). RoW includes Africa, Middle East and South America.
Geospatial imagery analytics companies are building their own satellites to gather the best data. The geospatial imagery analytics market is expected to have a revenue of $9 billion by 2026, driven by demands from the mining/manufacturing and engineering/construction industries.
Applications
Nearly 80 percent of enterprises possess location data, according to CIO. They benefit from geospatial analytics for business intelligence by being able to locate customers on a map. With address or zip code data, businesses can see where competitors are in relation to customers and decide where to locate a store. In retail, customers who download an app on a mobile phone can be tracked in the store and receive offers in real time.
Geospatial analytics benefits transportation and manufacturing sectors when it comes to logistics and supply chain management. Enterprises can visualize the most efficient routing scenarios and business processes.
Government and energy organizations that depend on geographic boundaries benefit from geospatial analytics by knowing instantly and accurately where municipal lines are drawn and the location of underground pipes, power poles and their relation to populated areas.
Here are two examples of companies using geospatial analytics to benefit from real-time situational awareness and decision-making:
- Skyhook — The mobile positioning and location provider uses geospatial analytics to run up to 10 billion transactions daily and map billions of data points in real time.
- Simulmedia — Uses geospatial analytics to process more than 300 million viewing events per day from 20 different sources to show national advertisers the effectiveness of ad campaigns.
Telecommunications — Quickly visualize call detail records and network logs so network operations centers can fix issues before customers notice. Since network signal strength fluctuates by location over time, geospatial analytics helps telecommunications companies understand where anomalies occur and then resolve them.
Military — Logistics for military operations that provide a true view of situational awareness. Geospatial predictive analytics helps the military optimize placement of resources while using predictive analytics to assess infrastructure, anticipate maintenance needs and meet deadlines.
Weather — Rapid response to extreme weather by visualizing blizzards, wildfires and hurricanes fast enough for effective evacuation alerts. Geospatial data analytics also helps airlines with routing and gives insurance companies a better way to assess property risk.
Urban Planning/Development — Determine how growing populations affect energy, transportation and housing resources. Geospatial big data analytics helps planners visualize large datasets at the speed and scale. It also allows for compiling and cross-filtering data from many sources to see how crime, public health, education and housing/real estate outcomes vary by location.
Natural Resource Exploration — Improve efficiencies in exploration and field operations for oil and gas industries. Geospatial analytics helps inform every phase of upstream exploration and production from mapping to drilling. Geologists and project managers can use the visualized data to make decisions that reduce costs, minimize risks and improve output.
Market
The global geospatial analytics market size was USD 56.88 billion in 2020 rose to USD 63.61 billion in 2021 Geospatial Analytics Market is projected to grow from USD 67.4 billion in 2022 to USD 119.9 billion by 2027, at a CAGR of 12.2% during the forecast period. The global market size is inclusive of several geospatial solutions such as thematic mapping and spatial analysis, geocoding and revere geocoding, data integration& ETL tools, among others.
Geospatial analytics market currently represents nearly 40% of the overall geographic information system (GIS) market.
Drivers
Rising use of AI and ML in geospatial analytics, increasing number of government projects are some key factors driving market revenue growth. The key factors impacting the growth of the global geospatial analytics market include upsurge in demand for AI-based GIS solutions, an increase in demand for geospatial analytics in smart cities development, rapid urbanization and urban planning. In addition, use of satellite monitoring to control the spread of COVID-19 positively impacts the growth of the market.
There has been a remarkable enhancement in artificial intelligence (AI) and machine learning (ML) abilities over the last few years to analyze GIS data. Artificial Intelligence and machine learning when integrated with geospatial data, offer improved insights to organization
AI GIS (artificial intelligence geographic information system) is a combination of artificial intelligence technology and several GIS procedures, like spatial data analysis algorithms. AI GIS is becoming the main focus of geoscience research and applications in recent times. Thus, growing utilization of artificial intelligence and machine learning in GIS solutions is driving the market.
Governments all around the world are investing in the development of a space borne and airborne surveillance system to improve national, regional, and global emergency response capabilities as well as to promote human health, security, and well-being. The rising number of AI-based GIS solutions, advancements in Big Data analytics, the rise of smart cities and urbanization, and integration of IoT sensors across industries are all propelling the market. Additionally, product launches and strategic initiatives by key players are expected to contribute to the geospatial analytics market growth. As per FMI, the geospatial analytics market is driven by factors such as technological advancements in machine learning and artificial intelligence, and big data technologies for analyzing geospatial data.
Widespread Applicability and Advancements in Location-Based Technology (LBT) to Drive Market Growth in Long-Term
Location-based services are widely utilized in a variety of verticals, including retail, mining,
transportation, construction, and urban planning. Businesses and agencies are widely
using location-based services integrated with Geographical Information System (GIS)
technology to for a variety of applications, including geospatial modelling, route
optimization, asset tracking, and others to offer better consumer-focused services.
Facility managers, for example, utilize GIS technology to support a variety of business processes
and information systems for tasks, such as building condition assessment, space utilization
optimization, and route mapping. GIS and Global Positioning System (GPS) technologies
are growing beyond their conventional uses to include a slew of consumer-focused,
location-based applications. According to a survey conducted by Information and Communications Technology for Development (ICT4D), Catholic Relief Services (CRS) and Devex, geospatial and mapping technology will be one of the top 5 technologies and 78%
respondents believe that the technology would have progressive effect on global digital
transformation.
Furthermore, the growing usage of cloud-based GIS platforms is expected to enhance market growth in the coming years. Complexity associated with storing and administration
of location-based data has enforced companies to prefer cloud-based geographic
information systems to achieve cost savings, improved productivity, and effective data management practices.
High cost of geospatial analytics and regulatory issues and lack of comprehensive government policies toward geospatial analytics are expected to further affect the market growth. Moreover, the adopting cloud-based GIS and increase in application of AR and VR technologies in geographic information system are expected to have a significant impact on the market growth during the forecast period. However, each of these factors is projected to have a definite impact on the growth of the geospatial analytics market.
Advancements in Geospatial Big Data Analytics Influence Demand?
Geoanalytics or geospatial big data analytics is a developing technology in which big data technology takes out insights, meaning, and patterns from complicated geospatial datasets. The advancement of big data technology will augment the adoption of sensor technology and the Internet of Things (IoT).
More businesses are moving towards geoanalytics technology to collect details from their day-to-day operations. Geoanalytics scales the investigation of big data by disclosing hidden patterns. For example, geoanalytics can investigate everything from the crime patterns to the spread of diseases.
The IoT in GIS is referred to the enhanced connectivity between physical devices over the internet with a spatial component. IoT in GIS enhances accuracy, efficiency, and economic advantages as it permits these objects to gather and exchange details with each other.
Esri offers GIS products such as ArcGIS platform that offers real- time GIS capabilities. Real-time dashboards offer actionable views into the daily functions of organizations, empowering stake holders and decision makers with the latest details they require to drive future and current strategies and ideas. Thus, advancements in geospatial big data analytics and usage of IoT are contributing to the growth in the market.
Increase in demand for GIS software in smart cities development and urban planning
Smart cities are data-driven and dependent on sharing real-time awareness. Collecting data from thousands of IoT sensors and analyzing it by an enterprise GIS creates visualization of the data on a map for immediate actionable insights. These insights can be used to track the delivery of city services and highlight areas where local council services need improvement. Location-based analysis of IoT data has further been used by local government to develop smarter parks, improve safety, and drive innovation. While developing smart cities projects, GIS solutions are implemented to create generalized location-enabled platform for use cases analysis in smart cities environments. These include automated natural hazard monitor web GIS with SMS warning, climate monitoring, urban design, intelligent transportation systems, and disaster management SDI. GIS software for smart city helps in site selection & land acquisition, planning, designing & visualization, construction & project management, and operations & reporting. Specialists apply GIS in urban planning for analysis, modeling, and visualization. By processing geospatial data from satellite imaging, aerial photography, and remote sensors, users gain a detailed perspective on land and infrastructure. These benefits of GIS are driving the growth of the geospatial analytics market.
Geospatial Analytics Solutions Helped Governments and Healthcare Agencies to Manage Drug Delivery and Emergency Response Management
The outbreak of COVID-19 had a minor impact on the global market with some players
witnessing reduced solution and product demand. During the pandemic, the expansion of
transportation and logistics, manufacturing, and retail sectors was hampered by stringent
lockdown rules and the suspension of import-export activities by several governments.
Verticals, including healthcare and life sciences, energy, and utilities, on the other hand, are
rapidly embracing geospatial and location-based platforms and services. While geospatial data and technology are assisting governments throughout the world in answering important COVID-19 issues, each nation faces its own set of challenges that affect response efforts.
Location intelligence and geospatial technologies are helping healthcare companies and governments in medical supply and drug delivery, vaccine distribution, and analysis of rising cases particular to locations. For instance, ArcGIS Solutions developed by Esri in December 2020 is helping businesses and healthcare communities to manage vaccine distribution plans and monitor key vaccine distribution metrics.
The long-term growth of the global market would be driven by increased adoption of GIS
and geolocation technologies across healthcare, retail, and military verticals. Maps and GIS give significant insights to aid businesses in responding to the crisis, maintaining operational continuity, and assisting in the reopening process. GIS, analytics, and Big Data are some of the technologies that are expected to gain exponential growth over the upcoming years. The GIS-based comparison study is assisting in the understanding and analysis of COVID-19’s source and pattern.
Segment Review
The geospatial analytics market is segmented into component, deployment model, solution, type, technology, industry vertical, and region.
In terms of component, the market is fragmented into solution and services.
On the basis of solution, it is categorized into geocoding & reverse geocoding, data integration & ETL, reporting & visualization, thematic mapping & spatial analysis, and others. Depending on the collection medium, it is divided into the geographic information system, satellites, unmanned aerial vehicle and others.
Depending on deployment model, it is bifurcated into on-premise and cloud.
Cloud segment to account for higher CAGR during the forecast period
The Geospatial Analytics Market is bifurcated on the basis of cloud and on-premises. The market size of the cloud deployment mode is estimated to be larger and projected to have a higher CAGR during the forecast period. A combination of spatial technologies with cloud computing offers an alternative platform for data, making it affordable and scalable. The deployment type comes with flexible subscription-based pricing models, and access to the services is provided through cloud-deployed network connectivity. A geospatial cloud providing GIS as SaaS offers many analytic and visualization capabilities.
In terms of enterprise size, the market is fragmented into large enterprises and SMEs. By type, it is segregated into surface & field analytics, network & location analytics, geovisualization, and others.
SMEs segment to account for higher CAGR during the forecast period
The SMEs segment is a faster-growing segment in the Geospatial Analytics Market during the forecast period as the demand for geospatial analytics in organizations is increasing. The deployment of geospatial analytics varies according to the needs of different end users. The increasing volume of location-based spatial data in SMEs is one of the major factors driving the growth of the Geospatial Analytics Market.
According to industry vertical, it is classified into mining and manufacturing, government, environmental monitoring, defence and security, engineering and construction, insurance, automotive and others.
Geographical outlook
Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA
Europe region is likely to dominate the geospatial analytics market share by securing a higher share during the forecast period. As per the study, U.K. is estimated to create an absolute $ opportunity of US$ 1.1 Bn by the end of 2032.
Due to the growing geographic information system and innovating AI, advanced technology in the UK is flourishing in the market size in the region. The wide use of GIS is likely to enhance the productivity of the business in recent years. In addition, growing awareness regarding geospatial data fuel the market growth in the region during the forecast period. Moreover, the company’s employees and marketing intelligence are monitoring real-time data to make well-informed decisions for the company in the region.
The geospatial analytics demand in the U.S. is expected to account for around 72.3% of North America market share by 2032. Emergence of modern geospatial cloud is contributing to the growth in the U.S. market.
Geospatial cloud uses web services, along with elastic computing and data storage abilities offered by cloud computing services to permit substantial sharing and integration of distributed georeferenced data.
This modern architecture is simpler to install and use and, hence it also increases adoption and business value. Geospatial cloud is letting current geographic information systems users and new adopters increase their value across their organizations, and it can be utilized by executives and fieldworkers to data scientists and software developers.
Asia Pacific region is also propelling a significant geospatial analytics market share. India is likely to drive the demand for geospatial analytics due to rising GIS technology for the agriculture sector during the forecast period. This technology helps to generate dynamic agriculture and provides information related to crops at different stages. GIS also offers effective products in a good environment by managing and controlling farming easily with this technology in the region.
Market Players
The market is fragmented by the number of key manufacturers present globally during the forecast period. These key players are making marketing strategies to provide high-quality services to end users. Some of their basic tactics are mergers, partnerships, collaborations, and acquisitions, among others. Various start-ups and key companies are deployed modern options and offer scalable and secure services. Moreover, several key market players are innovating Esri ArcGIS technology with AI, with is one of the best combos in the market. It is one of the latest mapping analytics software, which is likely to drive all around the globe. Large enterprises are likely to prefer this technology due to provide better values for the company’s growth.
Major vendors in the Global Geospatial Analytics Market are Esri (US), Precisely (US), Caliper Corporation (US), Blue Marble Geographic (US), Google (US), eSpatial (Ireland), HexagonAB (Switzerland), TomTom (Netherlands), Trimble (US), Maxar Technologies (US), RMSI (India), Maplarge (US), General Electric (US), Bentley Systems (US), Fugro (Netherlands).
Industry developments
In July 2020, GoodData Corporation expanded its geo-mapping capabilities to better meet the needs of organizations seeking location data insights to aid strategic decision-making. Companies can now give the most complete geolocation support for market trend evaluation, asset tracking and monitoring, site selection, and other critical business needs using this new set of analytical visualizations and modeling techniques
References and Resources also include:
https://www.heavy.ai/technical-glossary/geospatial-analytics
https://www.futuremarketinsights.com/reports/geospatial-analytics-market
