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首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >A spatiotemporal probabilistic modelling of storm-induced shallow landsliding using aerial photographs and logistic regression
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A spatiotemporal probabilistic modelling of storm-induced shallow landsliding using aerial photographs and logistic regression

机译：航空摄影和逻辑回归的风暴诱发浅层滑坡时空概率模拟

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摘要

Landslides constitute one of the major natural hazards that could cause significant losses of life and property. Mapping or delineating areas prone to landsliding is therefore essential for land-use activities and management decision making in hilly or mountainous regions. A landslide hazard map can be constructed by a qualitative combination of maps of site conditions, including geology, topography and geomorphology, by statistical methods through correlating landslide occurrence with geologic and geomorphic factors, or by using safety factors from stability analysis. A landslide hazard map should provide information on both the spatial and temporal probabilities of landsliding in a certain area. However, most previous studies have focused on susceptibility mapping, rather than on hazard mapping in a spatiotemporal context. This study aims at developing a predictive model, based on both quasi-static and dynamic variables, to determine the probability of landsliding in terms of space and time. The study area selected is about 13 km~2 in North Lantau, Hong Kong. The source areas of the landslides caused by the rainstorms of 18 July 1992 and 4-5 November 1993 were interpreted from multi-temporal aerial photographs. Landslide data, lithology, digital elevation model data, land cover, and rainfall data were digitized into a geographic information system database. A logistic regression model was developed using lithology, slope gradient, slope aspect, elevation, slope shape, land cover, and rolling 24 h rainfall as independent variables, since the dependent variable could be expressed in a dichotomous way. This model achieved an overall accuracy of 87.2%, with 89.5% of landslide grid cells correctly classified and found to be performing satisfactorily. The model was then applied to rainfalls of a variety of periods of return, to predict the probability of landsliding on natural slopes in space and time. It is observed that the modelling techniques described here are useful for predicting the spatiotemporal probability of landsliding and can be used by land-use planners to develop effective management strategies.
机译：滑坡是可能造成重大生命和财产损失的主要自然灾害之一。因此，在丘陵或山区，绘制或划定易于滑坡的区域对于土地使用活动和管理决策至关重要。可以通过定性组合现场条件图（包括地质，地形和地貌），通过将滑坡发生与地质和地貌因素相关联的统计方法，或通过使用稳定性分析中的安全系数，来构造滑坡灾害图。滑坡灾害图应提供有关某个地区滑坡的时空概率的信息。但是，以前的大多数研究都集中在磁化率图上，而不是时空背景下的危害图上。这项研究旨在基于准静态和动态变量开发一种预测模型，以确定在时空上发生滑坡的可能性。在香港北大屿山选定的研究区域约为13 km〜2。 1992年7月18日和1993年11月4-5日的暴风雨造成的滑坡源区是从多时相航空照片中得到解释的。将滑坡数据，岩性，数字高程模型数据，土地覆盖和降雨数据数字化到地理信息系统数据库中。建立了逻辑回归模型，使用岩性，坡度，坡度，高程，斜坡形状，土地覆盖和滚动的24小时降雨作为自变量，因为可以用二分法表示因变量。该模型的总体精度为87.2％，正确分类的滑坡网格单元中有89.5％的性能令人满意。然后将该模型应用于各种回报期的降雨，以预测时空在自然斜坡上滑坡的可能性。可以看出，此处描述的建模技术可用于预测滑坡的时空概率，并且土地使用规划人员可以使用其开发有效的管理策略。

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