Characterization and Geomorphic Change Detection of Landslides Using UAV Multi-Temporal Imagery in the Himalayas, Pakistan

Abstract

Multi-temporal unmanned aerial vehicle (UAV) imagery and topographic data were used to characterize and evaluate the geomorphic changes of two active landslides (Nara and Nokot) in Pakistan. Ortho-mosaic images and field-based investigations were utilized to assess the geomorphological changes, including the Topographic Wetness Index, slope, and displacement. Volumetric changes in specific areas of the landslides were measured using the Geomorphic Change Detection (GCD) tool. The depletion zone of the Nara landslide was characterized by failures of the main scarps, resulting in landslides causing erosional displacements exceeding 201.6 m. In contrast, for the Nokot landslide, the erosional displacement ranged from −201.05 m to −64.98 m. The transition zone of the slide experienced many slow earth flows that re-mobilized displaced material from the middle portion of the landslide, ultimately reaching the accumulation zone. Volumetric analysis of the Nara landslide indicated overall erosion of landslide material with a volume of approximately 4,565,274.96 m3, while the accumulated and surface-raising material volume was approximately 185,544.53 m3. Similarly, for the Nokot landslide, the overall erosion of landslide material was estimated to be 6,486,121.30 m3, with an accumulated volume and surface-raising material of 117.98 m3. This study has demonstrated the efficacy of the GCD tool as a robust and repeatable method for mapping and monitoring landslide dynamics with UAVs over a relatively long time series.

Keywords

• unmanned aerial vehicle (UAV)
• GCD
• surface movement
• point cloud
• orthomosaic
• DSM