Recent advances in both unmanned aerial vehicles (UAVs) and computer vision techniques offer the potential to change the monitoring of active surface processes and their associated hazards.
The low cost and simplicity of UAVs allow rapid and repeat deployment in areas that are either inaccessible for field work or lacking sufficient resolution from satellite data. The digital terrain models (DTMs) and orthorectified images generated from UAVs also have the potential to be of improved quality, meaning that new insights can be gained.
This project will develop a proof-of-concept study, split into technology and science components, that will, respectively (1) devise best-practice techniques for the use of UAVs to monitor active surface processes, (2) provide new insight into understanding the dynamics of several active landslides. Of particular importance in the technology component will be the comparison of image versus point cloud techniques for quantifying change. The main scientific outputs will be focused on the dynamics of failure at different landslides and quantifying the rate of movement for hazard assessment.