Research Interests

Current project: Landslide monitoring and early warning with SAR and GNSS

Supervisors: Prof. Zhenhong Li; Prof. Stefano Utili; Dr Nigel Penna.

Project overview:

In order to mitigate the impact of landslide disasters, it is necessary to detect potential landslide risk areas, monitor landslide bodies in real time and develop a set of adaptive landslide early warning systems.

In our project, an improved landslide detection method combining various time series SAR techniques will be developed, which can trace both the fast-creep and slow-creep landslides. Landslide failure triggers will be analysed according to historical events, field investigation and slope dynamic simulation. With clear failure triggers we could determine the type and density of surveying sensors in the monitoring network.

To predict the landslide failure accurately and timely, failure pre-cursors will be estimated through landslide modelling. Moreover, a continuous, real-time and multi-source monitoring network will provide dynamic encrypted observations and support the refinement of the landslide model in a small scale. From the landslide risk detection, slope modelling to landslide monitoring and re-modelling, we expect to construct a more systematic and adaptive landslide early warning system.