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首页> 外文期刊>Journal of African Earth Sciences >Landslide susceptibility zonation mapping using statistical index and landslide susceptibility analysis methods: A case study from Gindeberet district, Oromia Regional State, Central Ethiopia
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Landslide susceptibility zonation mapping using statistical index and landslide susceptibility analysis methods: A case study from Gindeberet district, Oromia Regional State, Central Ethiopia

机译：利用统计指标和滑坡敏感性分析分析方法的滑坡敏感性分析方法 - 以埃塞俄比亚中部地区德罗米亚地区州林德伯雷特区为例

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The present study was carried out in Gindeberet district, central Ethiopia and covers a total of 128 km(2). The geology of the area is comprised of sandstone, mudstone, limestone and basalt. The general objective was to evaluate the factors influencing the landslide initiation and to prepare a landslide susceptibility zonation map. One hundred thirty landslides were identified through field investigation and Google Earth image interpretation. Statistical Index Model (SIM) and Landslide Susceptibility Analysis (LSA) were used for the preparation of landslide susceptibility map. Lithology, slope steepness, aspect, land use/land cover, and distance from drainage are the causative factors selected, whereas rainfall and human activities are considered as the triggering factors. The relations of landslides and causative factors were determined in terms of weighted value (W-ij). From the lithology limestone, mudstone and weathered basalt have strong relationship with the landslides. Moreover, the result shows that weighted values (W-ij) are high for N and W orientation class of slope aspect; greater than 45. slope steepness; agricultural land and moderately vegetated land use/land cover class and 0 100 m and 100 200 m distance from drainage class. Landslide susceptibility zonation (LSZ) map was prepared and classified into very low, low, high, and very high susceptible zones. For LSZ map prepared by SIM model out of 130 landslides inventory data, 2 (1.54%) of the landslides fall in very low susceptible zone, 11 (8.46%) in low susceptible zone, 12 (9.23%) in moderate susceptible zone, 16 (12.31%) falls in high susceptible zone and 89 (68.46%) in very high susceptible zone, whereas LSZ map prepared by LSA model shows that out of 130 landslides inventory data, 11 (8.5%) of the landslides fall in very low susceptible zone, 12 (9.2%) in low susceptible zone, 15 (11.5%) in moderate susceptible zone, 25 (19.3%) in high susceptible zone and 67 (51.5%) in very high susceptible zone. The percent of existing landslide determined from LSZ maps prepared by SIM and LSA falls in high and very high susceptible zones were 81% and 71% respectively. The result of verification shows that areal distributions and occurrences of landslides were relatively comparable in both methods.
机译：本研究在埃塞俄比亚中部吉丁区进行，共占总128公里（2）。该地区的地质由砂岩，泥岩，石灰石和玄武岩组成。一般目标是评估影响滑坡启动的因素，并制备山床滑坡易感区映射。通过现场调查和谷歌地球图像解释确定了一百三十个山体滑坡。统计指标模型（SIM）和滑坡易感性分析（LSA）用于制备滑坡易感性图。岩性，边坡陡坡，方面，土地使用/陆地覆盖以及排水的距离是所选择的致病因素，而降雨和人类活动被视为触发因素。在加权值（W-IJ）方面确定了山体滑坡和致病因子的关系。从石灰石，泥岩和风化的玄武岩与滑坡有很强的关系。此外，结果表明加权值（W-IJ）对于斜率方面的N和W方向等级高;大于45.坡度陡峭;农业用地和适度植被的土地使用/陆地覆盖级和0 100 M和100 200米距离排水等级。山体滑坡易感性分区（LSZ）地图被制备并分为非常低，低，高，高易感区域。对于SIM模型中的LSZ地图，其中130个LANDSLIDES库存数据，2（1.54％）的山体滑坡下降在极低的易感区，11（8.46％），在低易感区，12（9.23％）中适中易感区，16 （12.31％）在高易感区和89（68.46％）中落在非常高的易感区中，而LSA模型准备的LSZ地图显示，在130个山体滑坡库存数据中，11（8.5％）的滑坡下降非常低易感区域，12（9.2％）在低易感区，15（11.5％）中适中易感区，25（19.3％）高易感区，67（51.5％）在非常高的易感区。由SIM和LSA制备的LSZ地图中确定的现有滑坡百分比分别为81％和71％。验证结果表明，两种方法中，山体滑坡的出现和发生相对相比。

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