It is vital to monitor the post-seismic landslides economically and effectively in high-mountain regions for the long term. The landslide creep could cause a subtle change of the overlying vegetation after the earthquake, which will lead to the change of vegetation spectral characteristics in optical remote sensing data. The optical remote sensing technique can be used to monitor the landslide creep areas with dense vegetation in a large range at a low cost because it is easy to obtain multi-temporal, multiple-scale, and multi-spectral information. We identified and extracted the vegetation change area before the 2018 Baige landslide by the high-resolution optical remote sensing data. Firstly, the image fusion method was used to improve the accuracy of change detection. Then, vegetation coverage before the landslide was calculated. The vegetation change was identified, and qualitative and quantitative methods were used to analyze the spatio-temporal changes of vegetation coverage. Our results indicate that the creep distance of the landslide is about 50 m and the vegetation in the back scarp area and the main sliding area display a significant downward trend with time closing to the landslide comparing with that in the reference area. The vegetation change in the remote sensing image has an excellent spatio-temporal correlation with the landslide creep. This study provides a possible way and perspective for monitoring post-seismic landslide disasters.
Detecting the Vegetation Change Related to the Creep of 2018 Baige Landslide in Jinsha River, SE Tibet Using SPOT Data
