A comprehensive remote sensing identification model for ancient landslides in the Dadu river basin on the eastern margin of tibet plateau

[摘要] The identification of ancient landslides has become a challenging task due to the long-term reconstruction and sediment cover, which obscure the original geomorphic characteristics of these landslides. To address this issue, a comprehensive remote sensing identification model, known as GTVI, is developed using the Object Based Image Analysis (OBIA) based on multi-source and high-resolution remote sensing data in the Dadu River Basin. The study reveals significant differences in texture, hue, shape, and adjacency topology between ancient landslides and reactivated landslides. The gray level co-occurrence matrix entropy (GLCM), terrain roughness index (TRI) and vegetation index (NDVI) effectively capture the information related to ancient landslides. The feasibility of the GTVI (GLCM and Terrain roughness and Vegetation index) model is confirmed through field investigations and remote sensing image analysis of typical landslides, demonstrating its high accuracy. This research provides a valuable method and technical reference for the rapid identification of ancient landslides in plateau canyon areas.

[发布日期] 2023-10-16

[关键词] OBIA method;multi-scale segmentation;feature optimization;ancient landslide;remote sensing identification model