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

被引:17
作者
Moresi, Federico Valerio [1 ]
Maesano, Mauro [1 ,2 ]
Collalti, Alessio [1 ,2 ]
Sidle, Roy C. [3 ,4 ,5 ]
Matteucci, Giorgio [6 ]
Mugnozza, Giuseppe Scarascia [1 ]
机构
[1] Univ Tuscia, Dept Innovat Biol Agrofood & Forest Syst, I-01100 Viterbo, Italy
[2] Natl Res Council Italy, Inst Agr & Forest Syst Mediterranean, I-00100 Rome, Italy
[3] Univ Cent Asia, Mt Soc Res Inst, Khorog 736000, Tajikistan
[4] Tokyo Univ Agr & Technol, Inst Global Innovat Res, Tokyo 1838538, Japan
[5] Univ Sunshine Coast, Sustainabil Res Ctr, Sippy Downs, Qld 4556, Australia
[6] Inst BioEcon IBE, I-50019 Sesto Fiorentino, FI, Italy
关键词
shallow landslide; root cohesion; infinite slope analysis; integrated modelling; GIS; forest management; TREE ROOTS; CALABRIA; STRENGTH; FLOOD; RISK; SUSCEPTIBILITY; TOPMODEL; SYSTEM; RIVER; SILA;
D O I
10.3390/geosciences10080309
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
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.
引用
收藏
页码:1 / 22
页数:22
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