GeoAI represents a powerful convergence of Geographic Information Systems (GIS), remote sensing, and artificial intelligence, including machine learning and deep learning. This integration is increasingly transforming how we analyze, model, and manage complex urban systems.

 

The proposed course is structured to provide both strong theoretical foundations and hands-on practical exposure. It introduces students to geospatial data handling, spatial analysis, and AI-based modeling techniques. Importantly, it goes beyond traditional GIS by enabling predictive modeling, pattern recognition, and automated spatial decision-making.

 

The course is organized into key modules covering:

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• Fundamentals of GeoAI and geospatial data systems

• Machine learning applications in spatial analysis

• Deep learning for remote sensing and image classification

• Object detection and change detection for urban and environmental monitoring

• Real-world applications such as smart mobility, climate risk mapping, and disaster assessment

• Advanced topics including big data analytics and spatio-temporal modelling

 

A distinctive strength of this elective is its practice-oriented approach, where students will work with tools such as Python, QGIS, Google Earth Engine, and KNIME and complete an end-to-end project solving a real-world urban or environmental problem.

 

The importance of this course lies in three key aspects:

 

First, it addresses the growing demand for data-driven planning, where planners are expected to work with large-scale spatial datasets and advanced analytical tools. Second, it enhances employability and research capability, equipping students with skills that are highly relevant for smart cities, climate resilience, infrastructure planning, and policy analytics. Third, it positions our department at the forefront of innovation in planning education, integrating AI into urban planning pedagogy—something that is increasingly becoming a global academic standard.

In conclusion, the GeoAI elective is not merely an addition to the curriculum but a strategic step toward future-ready urban planning education, bridging technology and planning practice.