Landslide susceptibility assessment using the certainty factor and analytic hierarchy process

A new approach combining the certainty factor(CF) and analytic hierarchy process(AHP) methods was proposed to assess landslide susceptibility in the Ziyang district, which is situated in the Qin-Ba Mountain region, China. Landslide inventory data were collected based on field investigations and remote sensing interpretations. A total of 791 landslides were identified. A total of 633 landslides were randomly selected from this data setas the training set, and the remaining landslides were used for validation as the test set. Nine factors, including the slope angle, slope aspect, slope curvature, lithology, distance to faults, distance to streams, precipitation, road network intensity degree and land use were chosen as the landslide causal factors for further susceptibility assessment. The weight of each factor and its subclass were calculated by AHP and CF methods. Landslide susceptibility was compared between the bivariate statistical method and the proposed CF-AHP method. The results indicate that the distance to streams, distance to faults and lithology are the most dominant causal factors associated with landslides. The susceptibility zonation was categorized into five classes of landslide susceptibility, i.e., very high, high, moderate, low and very low level. Lastly, the relative operating characteristics(ROC) curve was used to validate the accuracy of the new approach, and the result showed a satisfactory prediction rate of 78.3%, compared to 69.2% obtained with the landslide susceptibility index method. The results indicate that the CF-AHP combined method is more appropriate for assessing the landslide susceptibility in this area.

Susceptibility Assessment of Landslides in Alpine-Canyon Region Using Multiple GIS-Based Models

This study explores a comparative study of three susceptibility assessment models based on remote sensing(RS) and geographic information system(GIS). The Lenggu region(China) was selected as a case study. At first, a landslide inventory map was compiled using data from existing geology reports, satellite imagery, and coupling with field observations. Subsequently, three models were built to map the landslide susceptibility using analytical hierarchy process(AHP), fuzzy logic(FL) and certainty factors(CF). The resulting models were validated and compared using areas under the curve(AUC). The AUC plot estimation results indicated that the three models are promising methods for landslide susceptibility mapping. Among the three methods, CF model has highest prediction accuracy than the other two models. Similarly, the outcome of this study reveals that streams, faults, slope and elevation are the main conditioning factors of landslides. Especially, the erosion of streams plays a key role of the landslide occurrence. These landslide susceptibility maps, to some extent, reflect spatial distribution characteristics of landslides in alpine-canyon region of southwest China, and can be used for land planning and hazard risk assessment.

滑坡易发性评价的层次分析法研究——以贵州省普安县为例

评价方法的合理选择是获取正确滑坡地质灾害易发性评价结果的关键环节。本文以贵州省黔西南州普安县为例,在全面分析区内地层岩性、地形地貌、地质构造和水文地质等条件对滑坡灾害影响的基础上,采用层次分析法建立了具有针对性的滑坡灾害易发性评价指标体系,并开展了实际应用。评价结果在县境内划分出了极高、高、中和低易发区四个区域,对比分析显示评价结果与区内滑坡灾害发育宏观认识与实际分布情况吻合较好,证明了该方法在山区滑坡地质灾害易发性评价中的有效性与实用性。