DISPLACEMENT OF THE KHETRAPAL LANDSLIDES CHAMOLI IN THE HIMALAYAN REGION USING UAV AND TLS

Abstract

Landslides are a significant source of concern in the Himalayan region and other hilly regions of India, particularly during the wet seasons. At the same time, this is the case in the Chamoli region, which is the focus of this research. Although this is the case, there is still a deficiency in the amount of comprehensive study and a sufficient database on landslides in these regions. With respect to landslip inventory, susceptibility mapping, and risk assessment, the purpose of this study is to present a comprehensive review of the existing advances, gaps, and future directions in the Indian context. When there is a lack of data, the major objective is to make use of geospatial platforms in order to construct a landslip inventory map that covers a number of different time periods. An evaluation of the landslip susceptibility map will be carried out with the use of the weights of evidence (UA). A total of 293 landslip polygons were manually digitised during the first stage, which took place between 2011 and 2013. With the assistance of Google Earth® and the Indian earth observation visualisation technology known as BHUVAN, this was made within the realm of possibility. On the other hand, fourteen factors that were shown to be responsible for landslides were chosen based on the findings of the earlier analysis. For example, There are a variety of components that fall under this category, including geology, geomorphology, soil type and depth, slope angle and aspect, relative relief, distance to lineaments, streams, roads, land use/cover, altitude zones, faults and thrusts, and more. As part of the process of developing a map of landslip susceptibility, both the UAV and the TLS technique were used.. This was accomplished by giving weights to each category of characteristics that were responsible for the landslip. The final landslip susceptibility map was then broken down into five distinct categories: very low, very high, medium, and low. the highest category was extremely low. After that, the IDRISI SELVA 17.0 programme was used in order to carry out a validation check on the landslip susceptibility map. This includes comparing the map to a selection of landslides that were chosen at random.