CSIRO PhD Grant hosted at Flinders University - Radar applications for ground deformation and land erosion mapping in Au...

We are seeking an outstanding candidate for a PhD scholarship for a CSIRO-funded Project entitled: Radar applications for ground deformation and land erosion mapping in Australia. The PhD project aims at exploring the value-added of satellite-based Earth observation data for understanding ground level changes due to land erosion, coastal erosion, landslides, and groundwater extraction. The project focuses on deformation data produced via the Interferometric Aperture Radar technique but might take advantage of a wide range of field, airborne and spaceborne auxiliary data to validate the measurements obtained by radar imagery processing.

Production and interpretation of ground level change data is crucial to observe land erosion processes, assess stability of surficial soil layers, map soil properties, map compaction in clayey aquifers etc. In Australia, such data help protect key environmental assets such as the Great Barrier Reef or to assure the sustainability of essential water resources. It is also important for the protection of coastal settlements and large development projects (e.g., transport infrastructure, nuclear waste disposal facilities). Currently, in Australia, techniques used for ground level change monitoring mostly rely on multi-temporal LiDAR-data, which are cost-intensive to obtain over large areas and are unable to monitor ground level changes at fine temporal scales (e.g., for one specific rain event). While interferometric radar ground level change mapping (InSAR) has been used throughout the World, its uptake in Australia is still limited to this date. This project proposes to test the method over several areas where interest has been identified in past and current CSIRO projects and where ground level changes can be measured via auxiliary methods. The project will use existing data from these projects to assess the value-added and the limits of methods based on radar imagery.