Integrating UAV Mapping and Spline-Based Modeling for Landslide Volume Estimation: A Case Study of Landslides in Himachal Pradesh

Landslides are among the most common natural hazards in mountainous regions, with substantial impacts on infrastructure, ecosystems, and communities. The landslide in Kotrupi and near the Prashar Lake, Mandi, Himachal Pradesh, India, has been actively evolving for the past few years, posing significant challenges to the region. This study combines UAV-based remote sensing with a novel computational approach using open-source MATLAB code to analyse the landslide's failure surface and quantify its volume. 

Using high-resolution UAV data, detailed 3D models and Digital Elevation Models (DEMs) of the sites are developed. This method was applied to estimate the landslide failure surface and volume using spline curves and transversal vertical profiles derived from the high-resolution DEMs. The model assumes tangent values of the failure surface, calculates the depth of the probable failure surface at each grid point, and plots it using a 2D grid function. By employing MATLAB code, the process is fully automated, requiring minimal data inputs, such as a DEM and KML file of the contour limits. The model generates a 3D failure surface, enabling rapid and precise volume calculations. 

Preliminary results highlight a significant volume release, offering insights into landslide dynamics and potential downstream hazards. The model's simplicity and adaptability are valuable tools for predicting hazard zones and defining mitigation strategies. By imposing additional constraints based on field measurements, this approach further refines predictions and enhances disaster preparedness. This study underscores the utility of combining UAV technology with advanced computational modelling to address landslide monitoring and risk assessment challenges effectively.