Geospatial Artificial Intelligence (GeoAI)

About this programme

In an era where we have access to vast amounts of geospatial data acquired from sources like satellites, UAVs, smartphones, IoT sensors, and more, the synergy of Artificial Intelligence (AI) with Geography/GIScience has led to the emergence of Geospatial Artificial Intelligence (GeoAI). GeoAI harnesses the power of AI models to analyze this wealth of geospatial data, enabling us to study both natural phenomena and human-related activities. This course offers a comprehensive study of AI models and algorithms and their practical applications in geospatial problem-solving. The course adopts a dual focus, combining theoretical insights with hands-on, real-world applications. Its primary goal is to equip students with advanced AI techniques tailored for geospatial analysis, fostering the ability to diagnose and address complex challenges in the field. Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information. Please note: all information from the Course syllabus is available on this page in an accessible format. This course provides a logical progression from the fundamentals of AI in geospatial analysis to practical skills in data preparation, traditional machine learning and deep learning models, and a deep understanding of model limitations in geospatial contexts. Application examples will be given on how GeoAI can be used to support urban and environmental planning decisions. The course is organized in six modules: