Advancements and innovation of technologies like AI, Cloud, Big Data and more have transformed the way businesses are done in the last few years. This continuous development has also led to a digital technology environment, expediting the global reach and contribution of the geospatial industry.

The industry involves collecting, storing, processing, assimilating, managing, mapping, assessing and distributing data connected to a specific location across the globe. Geospatial technologies include Geographic Information System (GIS)/Spatial Analytics, Global Navigation Satellite System (GNSS) and Positioning, Earth Observation, and Scanning.

As technological advancements continue to grow, the world will see a convergence of geospatial technologies with artificial intelligence along with its subsets, machine learning and deep learning. Though these cutting-edge technologies are still in its nascent stage, it is significant for industry players to start comprehending the impact of these solutions in the future.

Here we have accumulated some emerging technologies that will have an impact on and influence the geospatial industry in upcoming years.

Artificial Intelligence

AI has fundamentally altered the businesses' work operations, and analysis support, providing heightened intelligence opportunities for entities across sectors. Its subset, machine learning encompasses building statistical models based on sample data to make estimations or decisions without being explicitly programmed to do the task. The technology is largely leveraged by geospatial companies that enable systems to derive insights and make effective decisions from structured and unstructured datasets with least human intervention.

Moreover, the GIS systems carry a huge amount of information classified by geographical locations that make excellent training datasets for AI systems. And this connection to AI is requisite in the context of recent advances in computer vision and image recognition. Integrating AI with other emerging technologies like the internet of things (IoT) will also bring enormous new opportunities for the geospatial sector.

Cloud Computing

The evolution of cloud infrastructure has provided the advances in Big Data Analytics for geospatial technologies as GIS systems contain a wealth of information from geographical locations. These advances provide geospatial data a flexible, on-demand computing platform to combine observation systems, parameter extracting algorithms, phenomena simulations, analytical visualization and decision support. This further facilitates with social impact and user feedback that are the significant elements of the geospatial sciences.

Advanced computing networks such as CyberGIS and cloud computing services like cloud GIS are offering governments and others with conduits where they can more easily and quickly access and contribute to growing repositories of geospatial data, tools, and services.

Big Data

Big Data in this sector refers to datasets that exceeds the capacity of current systems. The traditional geospatial data that contains remotely sensed data was structured and analyzed in data analytics systems like GIS. However, with the emergence in faster and broader wireless and web networks, modern data with useful geospatial content like photos, social media chats, video, voice and messages now constitute almost 80 percent of the total data. In its unstructured form, it cannot be utilized in conventional analytic systems like GIS and the amount of data generated by these platforms far exceed the data storage capacity available.

Thus, Big Data here comes with improved innovation, sustainability which converts the sheer volume into billions in savings.

The geospatial industry comprises individuals, private companies, non‐profit organizations, academic and research institutions, and government entities that research, develop, manufacture, and deploy geospatial technology.