Artificial intelligence is now opening up new possibilities and posing new challenges for geospatial research. It is evolving very rapidly, driven by theoretical advances, the use of large data sets, a variety of computer hardware, and high-performance computing platforms that support the development, training, and deployment of artificial intelligence models in a short time frame.
In recent years, humanity has witnessed significant progress in geospatial artificial intelligence (GeoAI), representing a deep mutual integration of geospatial research and artificial intelligence, especially machine learning and deep learning techniques, as well as the latest AI technologies in both academia and industry.
The integration of artificial intelligence into geography enables fundamental research that combines big geodata, spatial analysis and methods, and artificial intelligence for a deep understanding of natural and social phenomena in geographical space.
GeoAI’s work aims to find the knowledge that will help humanity become more resilient to natural disasters and achieve more sustainable development. Artificial intelligence is also working on:
protecting vulnerable populations and reducing inequalities in communities;
research on public health and the environment, providing new approaches to improve our understanding of places that can have a positive impact on health;
ecosystem and biodiversity research, improving our understanding of spatial ecological processes and enabling us to make good decisions related to environmental protection and resource management;
spatial data infrastructure, enabling us to develop methods for prioritizing disaster mapping, enriching geospatial resource metadata, and building knowledge graphs from historical maps.
GeoAI actively leverages science and data sets to create smarter, more relevant geographic information, and to address a multitude of day-to-day challenges and future work.