Abstract
Soil changes, including landslides and erosion, are some of the most prominent post-fire effects in Mediterranean ecosystems. Landslide detection and monitoring play an essential role in mitigation measures. We tested two different methodologies in five burned sites with different characteristics in Central Greece. We compared Unmanned Aerial Vehicles (UAV)-derived high-resolution Digital Surface Models and point clouds with terrestrial Light Detection and Ranging (LiDAR)-derived point clouds to reveal new cracks and monitor scarps of pre-existing landslides. New cracks and scarps were revealed at two sites after the wildfire, measuring up to 27 m in length and up to 25 ± 5 cm in depth. Pre-existing scarps in both Kechries sites appeared to be active, with additional vertical displacements ranging from 5–15 ± 5 cm. In addition, the pre-existing landslide in Magoula expanded by 8%. Due to vegetation regrowth, no changes could be detected in the Agios Stefanos pre-existing landslide. This high-spatial-resolution mapping of slope deformations can be used as landslide precursor, assisting prevention measures. Considering the lack of vegetation after wildfires, UAV photogrammetry has great potential for tracing such early landslide indicators and is more efficient for accurately recording soil changes.
Highlights
The comparison of both Digital Surface Models (DSM) revealed slight changes in the topography, which are interpreted as small soil movements, possible early landslide indicators and soil erosion
Since the behaviour of a landslide can be monitored by examining the cracks at the landslide site [82], we focused on developing DSM and point clouds of high resolution and accuracy, both absolute and relative
We demonstrated that Unmanned Aerial Vehicles (UAV)-derived and t-Light Detection And Ranging (LiDAR) datasets are effective in areas that experienced severe wildfires no longer than 7 months before the flight campaign, or up to 2–3 months after the rainy season
Summary
[6] p.7 indicated a direct correlation between rainfall-induced mass movement events and their average frequency of occurrence after forest fires, since they alter vegetation and soil properties, making the burned area susceptible to rapid geomorphological changes [3,8]. It is common for these areas to have steep topography, rendering traditional techniques inappropriate and even hazardous for operators [16,17,18]. For this purpose, new tools such as Light Detection And Ranging (LiDAR) [19] and Unmanned Aerial Vehicles (UAV) have been deployed [20,21], for detection but monitoring purposes as well
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
