GEOAI: Transforming Geographical Studies Through Artificial Intelligence

Geospatial Artificial Intelligence (GeoAI) represents the integration of artificial intelligence with geographic information science to extract meaningful knowledge from spatial big data. With the growing availability of satellite imagery, GPS data, UAV observations, and sensor networks, traditional analytical methods are increasingly inadequate. GeoAI enables automated spatial pattern recognition, prediction, and decision-making using machine learning and deep learning techniques. This paper reviews the conceptual framework of GeoAI, its methodologies, major applications in geographical studies, challenges, and future research directions. The study highlights how GeoAI enhances land use classification, urban growth modeling, environmental monitoring, disaster management, and socio-economic analysis. Artificial Intelligence (AI) has enhanced geographical research through improved spatial analysis, pattern detection, and predictive modeling. This paper reviews AI applications in geography including land cover classification, spatial prediction, and environmental forecasting and demonstrates results with figures and tables. Challenges and future directions are also discussed