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Yang, J., 2018. Landslide damage from extreme rainstorm geological accumulation layers within plain river basins. In: Ashraf, M.A. and Chowdhury, A.J.K. (eds.), Coastal Ecosystem Responses to Human and Climatic Changes throughout Asia. To provide the basis of an early warning and detection for landslide disasters and to provide decision support for local governments in disaster prevention and mitigation, this research studied landslide damage assessment from the geological accumulation layer in a plain river basin under conditions of an extreme rainstorm. Based on an analysis of the relationship between landslide geology and rainfall and a damage model of landslides under conditions of extreme rainfall, the landslide damage assessment described in this article used the SINMAP model. The layer of geological accumulation in the Wenchuan–Diexi River section in the upper reaches of the Minjiang River was the study area. Spatial distribution characteristics and the main factors inducing a landslide disaster were studied, and a danger-evaluation model for landslides in that region was established for landslide assessment research and for applying that research. Based on the SINMAP model, the effects of different extreme rainstorm events on the stability of regional slopes were analyzed. The results of a stability evaluation for landslides show that the area has an unstable zone of 4339.8 km2, which accounts for 64.49% of the total area. The unstable area in this evaluation was basically consistent with the distribution of an existing landslide, which shows that the model can adequately evaluate slope stability and landslide potential from the layer of geological accumulation in this area. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to establish a data-driven approach and assess its potential for shallow landslide susceptibility mapping of the Shennongjia Forestry District, China. For the data processing, Fisher segmenting was used for the classification of topographical factors (gradient, relief amplitude, plan curvature, and normalized difference vegetation index) and the improved Otsu method was used to determine the buffer length thresholds of the locational factors (proximity to roads, rivers and faults). The computations show that these two objective methods help to avoid the uncertainty caused by the subjective judgments and the obtained thresholds are more consistent with actual conditions. Considering the different data types, the locational and topographical factors were evaluated by fuzzy comprehensive evaluation while the geological factors were evaluated by frequency index, and then the three separate evaluations were combined using radar chart analysis. The validation result shows that the susceptibility map based on a data-driven approach has a high accuracy of prediction and this approach will be salutary for risk mitigation and land-use management in mountainous regions. [ABSTRACT FROM AUTHOR]

Fifty-five descending images from the ENVISAT satellite were processed using the small baseline subset (SBAS) method to derive the spatial and temporal ground deformation of the Bailong River Basin between 2003 and 2010. The basin is one of the most severely landslide- and debris flow-affected areas of China. As a result, 104 sites with high deformation areas were identified. Interferometric Synthetic Aperture Radar (InSAR) analysis was combined with landslide inventory data and field surveys, and anomalous areas were classified into three main types: landslide; debris; and subsidence. Displacement rates up to 35 mm/yr were evaluated away from the sensor along a line-of-sight (LOS) direction. The results gained should allow a more accurate prediction and monitoring of landslides, debris, and subsidence; further, they demonstrate the capability of the SBAS method to analyze any displacement effect and identify dangerous and uninhabitable areas in the basin. The small baseline subset method can thus contribute to the prediction and prevention of geohazards in the area. [ABSTRACT FROM AUTHOR]