首页> 外文期刊>Bulletin of engineering geology and the environment >Statistical analyses of landslide size and spatial distribution triggered by 1990 Rudbar-Manjil (Mw 7.3) earthquake, northern Iran: revised inventory, and controlling factors
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Statistical analyses of landslide size and spatial distribution triggered by 1990 Rudbar-Manjil (Mw 7.3) earthquake, northern Iran: revised inventory, and controlling factors

机译:1990年Rudbar-Manjil(MW 7.3)地震,伊朗北部地震突出的滑坡尺寸和空间分布统计分析:修订了库存,控制因素

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This study is a revised inventory of landslides triggered by the Rudbar-Manjil earthquake (Mw = 7.3), 1990, obtained through the study of Komak Panah and Hafezi Moghadas (1993), interpretations of the stereoscopic aerial photos, and field data. We mapped the 223 coherent landslides with a total area of 11.3 km(2) and a calculated volume of 3.8 x 10(8) m(3) using a digital elevation model (DEM, 12.5 m) within the geographical information system (GIS) software. The correlation between landslide occurrence (size and distribution) and the controlling factors was analyzed using the bivariate model and the linear automated modeling (LINEAR) procedure in the SPSS software. Both LINEAR models of landslide volume (LV, m(3)) and landslide area (LA, m(2)) indicate the distance from the fault surface rupture is the most influencing factor on size prediction of coseismic landslides. The LA is more dependent on seismic factors, whereas the LV is on the lithology and topographic factors. The result of principal component analysis (PCA) model, using the GIS, showed that most landslides occurred in the red band (including 95% of the variance of controlling factors). Thus, the selected factors to investigate the landslide occurrence are valid and the PCA can be used to identify regions prone to coseismic landslides. The curves of landslide number density (LND, landslides/km(2)), landslide area percentage (LAP, landslide area/total area%), LA, and LV have a multimodal distribution (several patterns of response) by the topographic and seismic factors. It is recommended that other models be applied to better investigate the local effects of factors on the coseismic landslides.
机译:本研究是由Rudbar-Manjil地震(MW = 7.3),1990年触发的山体滑坡库存,通过研究Komak Panah和Hafezi Moghadas(1993),对立体天线照片和现场数据进行解释。我们使用地理信息系统(GIS)内的总面积为11.3 km(2)和3.8 x 10(8)米(3)的计算量的223个相干山体积,以及3.8 x 10(8)米(3)的计算量(GIS)软件。使用SPSS软件中的双抗体模型和线性自动建模(Linear)程序分析了滑坡发生(尺寸和分布)和控制因子之间的相关性。滑坡体积(LV,M(3))和滑坡区域(LA,M(2))的两种线性模型表明距离故障面破裂的距离是电影山山脉阳台山体积大小预测最大的因素。 LA更依赖地震因素,而LV是对岩性和地形因素的影响。使用GIS主成分分析(PCA)模型的结果显示,大多数山体滑坡发生在红色频段(包括控制因子的95%的差异)。因此,调查滑坡发生的所选因素是有效的,并且PCA可用于识别容易发电池滑坡的地区。滑坡数密度(LND,LANDSLIDES / KM(2)),滑坡面积百分比(LAP,LACKLIDE区域/总面积%),LA和LV的曲线通过地形和地震具有多模级分布(几种响应模式)因素。建议应用其他型号,以更好地调查因素对电影山脉的局部影响。

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