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摘要:
以往的滑坡易发性评价多以全体滑坡为研究对象，忽视了滑坡类型的区别。各评价指标对不同类型滑坡的影响程度不同，也导致指标权重无法精确地反映其对滑坡的影响。为更准确地对滑坡灾害进行空间预测，针对西宁市滑坡特征及发育机理，将全区滑坡分为土质滑坡和岩质滑坡；在野外实际调查的基础上，结合相关性分析，选取坡度、坡向、剖面曲率、平面曲率、工程地质岩组，以及滑坡点距断层、水系、道路的距离远近等8项因素作为滑坡易发性评价指标，并通过滑坡点分布密度和滑坡点相对分布密度，分析各评价指标分别对土质滑坡和岩质滑坡的影响；利用信息量模型，计算各评价指标对两类滑坡的信息量值，利用人工神经网络模型，赋予各评价指标对两类滑坡的权重；最后基于GIS平台利用加权信息量模型对研究区进行易发性评价。通过统计方法和ROC曲线法分别计算滑坡易发性评价成功率，结果表明：评价成功率可达到82.61%和82.30%，与未经滑坡分类的成功率比较，分别提高了10.9%和5.2%；同时，经过滑坡分类后，湟水河两岸地质条件较差的地区转变为滑坡高易发区。
Abstract:In the past, all landslides were mostly taken as the research object in the susceptibility evaluation, but the difference in types of landslides was ignored, leading to the fact that the index weight did not accurately reflect its impact on landslides. In order to accurately predict the landslide disaster, predecessors have put forward a variety of evaluation models: expert scoring, logical regression, neural network, and so on. Those studies have promoted the transformation of landslide susceptibility mapping from qualitative to quantitative. On the basis of previous studies, this paper analyses the feature and mechanism of landslides in the city of Xining, and puts forward landslide susceptibility mapping based on landslide classification. Through field investigation, landslides in the whole area are divided into soil landslides and rock landslides. Based on GIS platform, the geological data are extracted as raster data. Finally, the weighted information value is used to evaluate the vulnerability of the study area. Statistic methods and ROC curve are used to calculate the success rate. The results show that after landslide is classified the success rates are 82.61% and 82.30%, increasing respectively by 10.9% and 5.2%. Areas with poor geological conditions on both sides of the Huangshui River are transformed into highly susceptible areas. It is confirmed that landslide susceptibility mapping based on landslide classification is an effective means for landslide susceptibility mapping.
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