首页> 外文期刊>International Journal of Erosion Control Engineering >Comparative Study of Land Use Change and Landslide Susceptibility Using Frequency Ratio, Certainty Factor, and Logistic Regression in Upper Area of Ujung-Loe Watersheds South Sulawesi Indonesia
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Comparative Study of Land Use Change and Landslide Susceptibility Using Frequency Ratio, Certainty Factor, and Logistic Regression in Upper Area of Ujung-Loe Watersheds South Sulawesi Indonesia

机译:印度尼西亚南苏拉威西Ujung-Loe流域上游地区利用频率比,确定性因子和Logistic回归进行土地利用变化和滑坡敏感性比较研究

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The purpose of this study is to develop and apply land use change (LUC) as a novel causative factor to produce landslide susceptibility map (LSM) by using frequency ratio (FR), certainty factor (CF), and logistic regression (LR) models in a geographic information system environment. In the study area, Upper Area of Ujung-loe Watersheds area South Sulawesi Indonesia, landslides were derived from aerial photography from time series data image of Google Earth Pro~(TM )during 2012-2016 and field survey. LSM were built by using FR, CF, and LR with eleven causative factors. The results indicated that LUC affects landslide susceptibility in the study area according to FR and CF method. It can be inferred from the results of FR and CF, LUC has the highest value on both at LUC from primary forest to open area and paddy field, it was observed that the change vegetation type to another landscape destabilize slopes. However, in logistic regression method, LUC has on 5~(th )place from eleven causative factor, according to likelihood ratio test with chi-square value 85.065 after Slope, distance to river, distance to faults and aspect. Validation of landslide susceptibility was carried out by calculating the area under the curve (AUC) of receiver operating characteristic curve (ROC). Firstly, LR shows the highest accuracy in both success and predictive rate (85.6%). Secondly, the frequency of landslides in high to a very high class of susceptibility was calculated, which indicates the level of accuracy of the method. CF returns the highest accuracy of 85.28%.
机译:这项研究的目的是通过使用频率比(FR),确定性因子(CF)和逻辑回归(LR)模型来开发和应用土地利用变化(LUC)作为一种新的致病因子来生成滑坡敏感性图(LSM)在地理信息系统环境中。在研究区域印度尼西亚苏拉威西省的Ujung-loe流域上游区域,从Google Earth Pro〜(TM)在2012-2016年的时间序列数据图像中进行的航拍和实地调查得出了滑坡。 LSM是通过使用FR,CF和LR建立的,具有11个成因。结果表明,根据FR和CF方法,LUC影响研究区的滑坡敏感性。从FR和CF的结果可以推断,LUC在从原始森林到开阔地带和稻田的LUC上都具有最高的价值,观察到植被类型向另一种景观的变化会破坏斜坡。然而,在逻辑回归方法中,根据坡度,距河的距离,距断层的距离和坡向后的卡方值85.065,根据似然比检验,LUC在十一个致病因素上位于第五位。通过计算接收器工作特性曲线(ROC)的曲线下面积(AUC)进行滑坡敏感性分析。首先,LR在成功率和预测率上均显示出最高的准确性(85.6%)。其次,计算了高至极高敏感性等级的滑坡发生频率,这表明了该方法的准确性。 CF返回的准确度最高,为85.28%。

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