Research Presentation by Roquia Salam - UCL 14th Annual IRDR Conference

Explainable AI-driven Digital Twin-Enabling Technologies for Developing Rainfall-Induced Landslides Forecasting Systems in Bangladesh
All over the world, rainfall-induced landslides are recurrent and catastrophic disasters, with long-lasting impacts on people's lives, livelihoods, critical infrastructure, and sustainable development. Several landslides forecasting systems (LFS) are operational in different parts of the world that help to minimise overall loss and damage. Developing these LFS requires extensive data from various sources, such as meteorological, hydrological, geological, lithological and sensor data. However, many data sparse and rainfall-induced landslides-affected areas in the world lack an LFS because of the necessary data input to develop LFS, leaving people, their property, and the environment at high risk of landslide disasters.
Supervisors: Dr Bayes Ahmed and Prof Peter Sammonds
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