基于信息量、逻辑回归及其耦合模型的滑坡易发性评估研究:以青海沙塘川流域为例

滑坡易发性定量评估是预测滑坡发生空间概率的重要手段,基于统计分析原理的评估方法目前在国内外应用最为广泛,且不同评估方法的对比研究逐渐成为热点。以青海沙塘川流域黄土梁峁区为例,剖析了信息量模型和逻辑回归模型在滑坡易发性评估中的优越性和局限性,并探索提出基于二者的耦合模型。考虑坡度、坡向、起伏度、岩性、与干流距离、与支流距离和植被指数等7个影响因素,对比分析了基于信息量、逻辑回归及二者耦合模型的滑坡易发性评估的技术流程及结果。3种模型的成功率分别为:耦合模型成功率(78. 9%)>信息量模型成功率(71. 8%)>逻辑回归模型成功率(70. 8%)。在沙塘川流域黄土滑坡的易发性评估中,信息量和逻辑回归模型的表现基本相当,但信息量-逻辑回归耦合模型的成功率明显提升。该研究结果可为黄土高原区滑坡易发性定量评估提供借鉴。

Landslide Susceptibility Assessment Based on Information Value Model,Logistic Regression Model and Their Integrated Model:A Case in Shatang River Basin,Qinghai Province

Quantitative landslide susceptibility assessment is important to predict the spatial probability of landslides. The assessment method based on statistical analysis principle is in present commonly adopted worldwide, and comparison of different assessment methods has become a research hot spot. The loess region of the Shatang River Basin in Qinghai Province was the focus of this study. Strengths and limitations of the information value and logistic regression models in landslide susceptibility assessment were analyzed and an integrated model was proposed. Seven influence factors including the slope, aspect, relief and lithology, distance from main/branch drainage, and the normalized difference vegetation index (NDVI) were analyzed and compared with the landslide susceptibility assessment results based on the three models. The results suggest that the successful rate decreases from the integrated model (78.9%), through the information value model (71.8%) to the logistic regression model (70.8%), which indicates that the performance of the latter two models are similar in the loess landslide susceptibility assessment in the Shatang River Basin, and the successful rate of the new method is obviously higher. This study provides a reference for the quantitative landslide susceptibility assessment in the loess plateaus.