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Mapping Landslide Prediction through a GIS-Based Model: A Case Study in a Catchment in Southern Italy

机译:通过基于GIS的模型映射滑坡预测:意大利南部集水区的案例研究

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摘要

Shallow landslides are an increasing concern in Italy and worldwide because of the frequent association with vegetation management. As vegetation cover plays a fundamental role in slope stability, we developed a GIS-based model to evaluate the influence of plant roots on slope safety, and also included a landslide susceptibility map. The GIS-based model, 4SLIDE, is a physically based predictor for shallow landslides that combines geological, topographical, and hydrogeological data. The 4SLIDE combines the infinite slope model, TOPMODEL (for the estimation of the saturated water level), and a vegetation root strength model, which facilitates prediction of locations that are more susceptible for shallow landslides as a function of forest cover. The aim is to define the spatial distribution of Factor of Safety (FS) in steep-forested areas. The GIS-based model 4SLIDE was tested in a forest mountain watershed located in the Sila Greca (Cosenza, Calabria, South Italy) where almost 93% of the area is covered by forest. The sensitive ROC analysis (Receiver Operating Characteristic) indicates that the model has good predictive capability in identifying the areas sensitive to shallow landslides. The localization of areas at risk of landslides plays an important role in land management activities because landslides are among the most costly and dangerous hazards.
机译:由于与植被管理经常联系,浅层滑坡是意大利和全球的越来越多的问题。随着植被覆盖在坡度稳定性中起着基本作用,我们开发了一种基于GIS的模型,以评估植物根部对坡度安全性的影响,还包括滑坡敏感性图。基于GIS的模型4SLIDE是一种物理基于基于地质,地形和水文地质数据的浅层滑坡的预测因子。 4Slide结合了无限斜率模型,TopModel(用于估计饱和水位),以及植被根强度模型,这有利于预测对浅层滑坡更容易受到森林覆盖的函数的影响。目的是在陡峭的地区定义安全(FS)因子的空间分布。基于GIS的模型4SLIDE在位于Sila Greca(Cosenza,Calabria,南意大利)的森林山流域中进行了测试,其中近93%的地区被森林覆盖。敏感的ROC分析(接收器操作特性)表示该模型具有良好的预测能力,可识别对浅层滑坡敏感的区域。山体滑坡风险的区域化在土地管理活动中起着重要作用,因为山体滑坡是最昂贵和危险的危险之一。

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