Identification and Estimation of Landslide Erosion Rate Based on Particle Swarm Optimization Algorithm

• Published in: Shui tu bao chi xue bao Vol. 39; no. 2; pp. 338 - 347
• Main Authors: GENG Haopeng, XU Ziyi, GUO Yu, ZHANG Jian
• Format: Journal Article
• Language: Chinese
• Published: Editorial Department of Journal of Soil and Water Conservation 01.04.2025
• Subjects: geomorphological evolution; landslide erosion rate; multi-temporal landslide inventory; particle swarm optimization algorithm; the east himalayan syntaxis
• ISSN: 1009-2242
• DOI: 10.13870/j.cnki.stbcxb.2025.02.008

［Objective］ To construct a comprehensive multi-temporal landslide inventory across the Eastern Himalayan Syntaxis and quantify landslide-driven erosion rates, thereby revealing the geomorphological significance of landslide processes in this region. ［Methods］ The Particle Swarm Optimization (PSO) algorithm was employed to detect the change of the Normalized Difference Vegetation Index (NDVI) from remote sensing images, and a multi-temporal landslide inventory for the Eastern Syntaxis from 1987 to 2021 was constructed. The landslide erosion rate was calculated using an empirical landslide area-volume relationship. Additionally, the factors inducing landslide processes by considering climatic and topographic parameters were explored. ［Results］ A total of 1 323 landslides were identified in the study area between 1987 and 2021, with the highest occurrence of 389 landslides recorded between 2017 and 2021. The landslides predominantly occurred on both sides of the river valleys near the Yarlung Tsangpo River's Gre