GeoAI: Applications, Challenges and Future Prospects in Geography

Abstract

Geography is a subject that mainly relies on field surveys, remote sensing, and Geographical Information Systems (GIS) to interpret and analyze the environmental processes and spatial distributions of natural and social objects. However, these traditional methods have limitations in handling large and complex data sources. The recent developments in artificial intelligence tools with the support of GIS, known as Geographical Artificial Intelligence (GeoAI), offer an opportunity to perform spatial analysis using automation and pattern recognition, and by making predictions as well. In this article, an effort has been made to observe the transition of Geography from conventional GIS, remote sensing, and aerial photography to GeoAI by comparing their processes, advantages, and applications, and demonstrated in urban planning, environmental and disaster management, transportation, and agriculture with Indian and global examples. Besides, issues of data accessibility and generalization, model interpretability, computational requirement, and ethics have also been discussed. The present study concludes that GeoAI could be an excellent source to shift from descriptive to predictive geography to help spatial decision-making and sustainable development.