Study of clay degradation in an earthslide combining OBIA and roughness analysis of UAV-based optical images

Flow-like landslides in clay slopes pose major threats to people and infrastructure, which has led to numerous studies in recent decades. However, the mechanisms leading to the solid-fluid transition in clay are still poorly understood, despite numerous studies on its rheological evolution. The aim of this study is to contribute to quantify the degradation of clay at the surface of the Harmaliere landslide (French Alps) from the analysis of a series of three unmanned aerial vehicle (UAV) acquisitions. Two approaches were combined to process the acquired optical images. First, image classification was performed applying object-based image analysis (OBIA) to the red, green and blue (RGB) and surface roughness layers. Second, deeper analysis of the surface roughness allows to describe the morphology evolution and to interpret the degradation scheme from undegraded clay to degraded clay. The study shows that the applied methodology is appropriate to perform a thorough analysis of the material degradation pattern on the surface of a landslide. The temporal analysis shows an average degradation rate leading to the complete degradation of a block in about 2 years. Meanwhile, a spatial analysis shows that non-degraded clays degrade faster in the lower part of the study area, reactivated 30 years ago, than in the upper part, reactivated only a few years ago. In addition, roughness analyses enabled to highlight the evolution of the morphology during the degradation process of the clay blocks, from angular blocks to mounds.

Automated summary

Flow-like landslides in clay slopes pose major threats to people and infrastructure, but the mechanisms leading to solid-fluid transition in clay are poorly understood. This study uses unmanned aerial vehicle (UAV) acquisitions to quantify the degradation of clay at the surface of a landslide. The study shows that the applied methodology is appropriate to analyze the material degradation pattern and reveals the degradation rate and differences in different areas.