The world in which we live requires a lot of study and analysis based on its geography. Numerous energy, transportation, and public sector organizations depend on the geographical data to serve their business objectives and enhance efficiency. However, a significant revolution is underway, expanding the use of geographic data in a way that promises to disrupt entire industries. Sometimes called geospatial AI, geospatial analytics, or GEOINT (geospatial intelligence), the intersection of geospatial data and artificial intelligence is becoming critical to enterprises and governments ranging from weather centers, national labs, defense agencies, healthcare, agriculture, insurance, transportation, and many more.

Behind the rise of geospatial AI are three trends: increased availability of geospatial data from satellites and remote sensing, the advancement of artificial intelligence (particularly machine and deep learning), and the availability of massive computational power. And these trends are driving the new-age innovation across businesses today.

For the businesses and their leaders charged with improving operational efficiency or creating breakthrough results, the geospatial data revolution offers a tantalizing promise: almost unlimited opportunity when coupled with imagination. It's hard to think of any business now that can't use geospatial data and AI.

The volume of data that geospatial imagery and sensors generate is too extensive for humans alone to process; therefore, the importance of scalable computing, Machine Learning and AI for the geospatial analytics industry is immense. It is essential not only in processing and interrogating vast amounts of data but also in generating impactful insights.

Zooming out and looking at the larger geospatial analytics industry, these same digitalization tools are helping turn data into insights for customers in widely disparate industries. These tools allow businesses to leverage data to transform industries and make better decisions. Companies are realizing the power of imagery when paired with AI and starting to leverage geospatial technologies at an unprecedented rate.

Business Use Cases

Geospatial AI serves with great opportunities and applications in health and healthcare, as location plays a key role in both population and individual health. Several disciplines within the domains of public health, precision medicine, and IoT (Internet of Things)-powered 'smart healthy cities and regions' are benefiting from GeoAI, e.g., environmental health, epidemiology, genetics and epigenetics, social and behavioral sciences, and infectious diseases, to name but a few.

Moreover, geo-tagged big data collated from rich sources, such as social media streams, satellite imagery (remote sensing), IoT sensors in smart cities (e.g., monitoring air, light, and sound pollution), and personal sensing (via connected ambient and wearable sensors), can be reasoned with using geospatial AI to answer many important research and practice questions in more comprehensive ways.

Geospatial AI technologies can capture and model the environment, linking the places where people live, work, travel, and spend their time on environmental, social, and other types of location-specific exposures, to explore the technological potential role(s) in influencing human health. Such technologies can also generate new hypotheses, predict disease occurrence, and help plan and monitor the deployment of effective health promotion and disease prevention and control programs within smart healthy cities. Besides these population-level geospatial AI applications, there are further opportunities for integration of GeoAI and location-based information intelligence into precision medicine via well-tailored mHealth (mobile health) interventions targeting individual patients.