Chuang Song

• Email: c.song4@ncl.ac.uk

Supervisors

• Professor Zhenhong Li
• Professor Stefano Utili
• Dr Nigel Penna

Project description

Traditional landslide monitoring techniques with geotechnical sensors can provide measurements inside the landslide body. But careful selection of the proper monitoring equipment and location is needed. In general, this is not a straightforward choice for newly detected landslides.

The project aims to detect potential landslide areas at a large spatial scale. It will monitor landslide bodies in near real time with various remote sensing techniques.

I will develop a set of Synthetic Aperture Radar (SAR) processing flow. This will include interferometric SAR time series and SAR offset tracking methods. It will trace landslides with different types of deforming modes. This can enhance the efficiency and accuracy of landslide risk detection.

I will also combine observations from satellite/ground-based SAR, GNSS and geotechnical sensors. This will strengthen the complementarity of landslide monitoring networks. It will also build a landslide 3D deformation field.