Spatial Analysis of Wenchuan Earthquake-Damaged Vegetation in the Mountainous Basins and Its Applications

Huaizhen Zhang; Tianhe Chi; Jianrong Fan; Kaiheng Hu; Ling Peng

Spatial Analysis of Wenchuan Earthquake-Damaged Vegetation in the Mountainous Basins and Its Applications

2015

Huaizhen Zhang | Tianhe Chi | Jianrong Fan | Kaiheng Hu | Ling Peng

The 2008 Wenchuan Earthquake induced landslides that destroyed large swaths of mountain vegetation. Presently, the damaged vegetation areas are exhibiting various stages of recovery depending on environments. A spatial analysis of earthquake-damaged and recovered vegetation can provide useful information for understanding landslide processes. The mountainous watersheds of the Minjiang River Upstream, near Yinxiu Town (one of the highest seismic intensity zones during the Wenchuan earthquake) were selected. A DSAL (digital elevation model (DEM), slope, aspect and lithology) spatial zonation method was established to detect natural features of the vegetation survival environments, and damaged and recovered vegetation areas were extracted using the normalized difference vegetation index (NDVI) changes form multi-temporal (2001–2014) Landsat Thematic Mapper/Enhanced Thematic Mapper/Operational Land Imager (TM/ETM/OLI) images. Statistical results show that the vegetation growth was mainly controlled by its survival environments, and vegetation has coupling relations with slope stability. Then, the slope stability model was developed through multivariate analysis of earthquake-damaged vegetation and its controlling factors (i.e., topographic environments and material properties). Application to the Mianyuan River and Subao River basins validated the proposed model, showing that monitoring the vegetation (using the remote sensing images) can be used to assess the slope stability, and model results show what vegetative conditions with its survival environments are susceptible to landslide processes, although the predicted values may be higher than the actual values in the most mountainous basins. Our modeling approach may also be valuable for use in other regions prone to landslide hazards.

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