Integrated Remote Monitoring of Coastal Geohazards

Coastal geohazards are a major issue in many regions of the world, and certain coastlines, such as soft-cliff environments can be particularly prone to erosion and instability. Effective monitoring is fundamental to improved understanding of the behaviour of such processes. However, traditional monitoring techniques are generally limited in their spatial and temporal resolution, while contemporary approaches tend to be unsuitable in isolation, due to the often complex coastal morphology. To overcome such issues, this research adopts an integrated remote monitoring approach, concentrating on the synergistic fusion of multi-modal datasets. Airborne laser scanning enables rapid, continuous acquisition of large spatial extents, and the possibility for early detection of geohazard activity. In complement, terrestrial laser scanning then allows for more practical monitoring of these pockets of interest, at higher spatial and temporal frequencies. This research focuses on the effective reconciliation of these disparate datasets, and considers issues including resolution, vegetation effects, control requirements, and suitable scan and flightline overlaps. While rapid static GPS has been used to rigorously control temporary terrestrial scan stations in foreshore areas, the in-flight GPS-IMU system enables direct geo-referencing of airborne datasets. Furthermore, robust least squares based surface matching software has been developed as an additional dataset registration tool. This is particularly suited to the refinement of poorly-controlled datasets, and those which may be contaminated by large differences due to vegetation effects or terrain change. An episodic monitoring campaign was carried out, with test areas located on the east coast of England. Results have indicated the suitability of the robust matching approach for successful registration and change detection, and highlighted the value of the integrated monitoring strategy for practical and flexible multi-resolution monitoring.