AI-Enhanced Geospatial Modelling for Climate-Resilient Landscapes

Climate change, rapid urbanization, and environmental degradation are placing increasing pressure on land and water systems. Addressing these challenges requires innovative tools capable of analysing large environmental datasets and predicting future landscape changes.

This project proposes the integration of artificial intelligence (AI), Geographic Information Systems (GIS), and remote sensing to develop advanced geospatial models for assessing climate-related risks and environmental dynamics. Machine learning techniques will be used to analyse Earth observation data and environmental variables to detect patterns in land-use change, ecosystem services distribution, and water resource availability.

The research will develop spatial decision-support tools that enable policymakers and environmental planners to identify climate vulnerability hotspots and design effective adaptation strategies. The project will also explore the role of nature-based solutions and sustainable land management practices in enhancing climate resilience.

By combining geospatial science with AI-driven environmental modelling, the project aims to contribute to innovative approaches for sustainable landscape governance and climate adaptation. The outcomes will support evidence-based environmental policy and planning in both developing and developed regions, strengthening international research collaboration and knowledge exchange.