Using multispectral images and field inclinometer data to analyze topographic changes related to and the reactivation mechanism of a large-scale landslide at Caoling in Taiwan

This study employed a comprehensive methodology, which combines the use of multispectral images and field inclinometer data. The unique approach involves using multispectral images to monitor the topographic and hydrological changes caused by a large-scale landslide at Caoling in Taiwan. The field inclinometer data, collected at regular intervals, were then integrated into a geographic information system. This system was used to estimate the potential sliding volume of the landslide, which was then compared with changes in the digital terrain model data for Caoling. The multispectral images of Caoling were examined to determine the changes in its topographic and hydrological indices after the landslide. The convex slope at Caoling moved in the progressive backward mode with increased groundwater level and slope displacement under rainfall conditions. The potential sliding volume of the landslide was 6.4 x 106 m3. The results of this study indicate that the changes in topographic and hydrological indices after a landslide enable the identification of the local surficial changes caused by the landslide. Changes in the rate of slope movement show a high correlation to the fluctuation of groundwater level. Reactivation of the large-scale landslide is attributable to hillslope, geologic and topographic characteristics, including toe creek incision, surficial erosion, and torrential rainfall brought by typhoons. Moreover, post landslide topographic monitoring through drone images, which provide high-resolution and real-time data, plays a crucial role in identifying a landslide's reactivation mechanism. This, in turn, enables effective disaster mitigation strategies to be implemented.