Rapid susceptibility mapping of earthquake-triggered slope geohazards in Lushan County by combining remote sensing with the AHP model developed for the Wenchuan earthquake

摘要

A rapid-response mapping model can be used to study the susceptibility of areas of interest to geohazards (which are commonly regarded as among the most damaging natural hazards), assuming that the model is stable (i.e., that it is generally applicable to any such area). Applying a predefined predictive geohazard-susceptibility model to an area with geoenvironmental conditions similar to those of the area for which it was originally formulated is an effective method of testing the stability of the model. In this paper, the analytic hierarchy process (AHP)-based model developed for the Wenchuan earthquake was used to study susceptibility to earthquake-triggered slope geohazards in Lushan County. Upon integrating the results of a literature review, site investigation, and remote sensing interpretation, seven main factors that influence earthquake-triggered slope geohazards were identified, including peak ground acceleration, distance from a stream, distance from a highway, slope gradient, slope position, normalized difference vegetation index, and micro-landform. In order to reduce the subjectivity of the expert evaluation method usually applied in the AHP, these factors were ranked by relative importance using regression analysis. The weight of each factor was then calculated by the AHP. The susceptibility mapping model was obtained on the ArcGIS platform, utilizing map overlaying. Finally, the results were re-classified to obtain a map of slope geohazard susceptibility. The accuracy of the AHP model was evaluated using both qualitative and quantitative methods. In the qualitative method, the modeled distribution of susceptibility was compared with the actually distribution of geohazards in the study area (identified through remote sensing interpretation), and the areas with high and very high geohazard susceptibilities in the model were found to match well with the actual locations of slope geohazards. In the quantitative method, statistical data showed that over 66% of the geohazards were located in areas of high or very high susceptibility according to the model, while only about 16% were located in areas of very low or low susceptibility, and the density of slope geohazards was about 125 times greater in the areas with very high susceptibility than in the areas with very low susceptibility. Also, the AUC value of the ROC curve for the model suggested that it has high predictive power (a predictive accuracy of 84.8%). In conclusion, it was possible to make accurate predictions about the slope geohazards in earthquake-prone areas located in mountainous regions based on geospatial data, and a high correlation between the susceptibility map generated by the AHP-based model and the true distribution of slope geohazards was observed. Therefore, the AHP-based model used here could be applied to map the slope geohazard susceptibility in other mountainous regions which may be prone to slope geohazards during earthquakes.