Satellite monitoring of settlement-induced building deformations

Applications are invited for a 3-years Whorrod PhD Studentship on the use of Interferometric Synthetic Aperture Radar (InSAR) monitoring to assess the vulnerability of buildings and infrastructure. The project will be run in collaboration with the University of Cambridge and the NASA Jet Propulsion Laboratory, Caltech.

Modern cities are increasingly constructing underground as a solution to the lack of housing and infrastructure space. The excavation of metro and rail tunnels, stations and service space involve a certain amount of ground movements, which can cause damage to adjacent structures. Structural monitoring is therefore a large investment component of every underground construction project in urban areas.

While traditional monitoring requires in-situ installation and a preliminary evaluation of vulnerable structures, very recent advances in Interferometric Synthetic Aperture Radar (InSAR) techniques enable remote monitoring over extensive areas, providing quasi-real time and highly dense measurements with millimetre accuracy.

To exploit this vast improvement in data acquisition the project will use InSAR data as input to improved procedure for the assessment of settlement-induced damage to structures and infrastructure, and the early detection of damage indicators. Current and historical data will be used to improve current damage assessment techniques and to develop an automatic system for the evaluation of early failure signs.

The research involves the analysis and processing of satellite-based displacement measurements, computational and analytical modelling, collaborative work, preparation of journal papers and result dissemination to diverse audience.

Temporary research stays at partner institutions (University of Cambridge and California Institute of Technology) may be possible.

Applicants for the studentship should have a First Class (or a high 2:1) degree in a relevant discipline such as Engineering or Computer Science. The successful candidate should have strong analytical skills, interest in and aptitude for numerical modelling, the ability to work independently and in a team, and high level of proficiency in spoken and written English.

Applications will be considered as they are received, and a selection may be made before the application deadline.