NATURA

The NATURA project transforms landslide risk assessment by integrating physically-based modelling, AI-driven analytics, and socio-economic risk analysis into a unified framework. Unlike conventional models, NATURA explicitly captures feedback loops between hazards and human-induced landscape changes, incorporating CORDEX climate projections and Shared Socioeconomic Pathways (SSPs) to anticipate how urban expansion, economic shifts, and climate change influence landslide susceptibility.

A core innovation is the interdisciplinary approach merging high-resolution satellite imagery (Sentinel-2, PlanetScope, Copernicus DEM) with deep learning architectures (CNNs, transformers) to improve landslide susceptibility mapping, hazard detection, and scenario-based forecasting. The project also evaluates governance structures, economic disparities, and urban policies that disproportionately expose marginalised communities to landslide risks.

Key outputs include high-resolution risk maps, socio-economic vulnerability assessments, and scenario-driven risk projections, supporting global Disaster Risk Reduction (DRR) initiatives and climate adaptation strategies.