Advances in GeoAI for Large-Scale Spatiotemporal Data: Techniques and Real-World Use Cases

The fusion of Artificial Intelligence (AI) with geospatial technologies, GeoAI has transformed how we analyze complex spatiotemporal data. With the growing availability of high-resolution satellite imagery, sensor networks, and geotagged data, scalable GeoAI techniques are increasingly vital across sectors such as urban planning, environmental monitoring, disaster response, and public health. This paper provides a concise overview of recent advances in GeoAI for large-scale spatiotemporal data analytics. It highlights key techniques, addresses major challenges, and presents real-world use cases demonstrating the practical value of GeoAI in tackling global problems.