GIS-based statistical analysis for assessing shallow-landslide susceptibility along the highway in Calabria (southern Italy)

被引:7
|
作者
Conforti, Massimo [1 ]
Rago, Valeria [2 ]
Muto, Francesco [2 ]
Versace, Pasquale [3 ]
机构
[1] CNR, Ist Sistemi Agr & Forestali Mediterraneo ISAFOM, Arcavacata Di Rende, Italy
[2] Univ Calabria, Dipartimento Biol Ecol & Sci Terra DiBEST, Arcavacata Di Rende, Italy
[3] Univ Calabria, Dipartimento Ingn Informat Modellist Elettron & S, Arcavacata Di Rende, Italy
来源
RENDICONTI ONLINE SOCIETA GEOLOGICA ITALIANA | 2016年 / 39卷
关键词
Shallow-landslides; Weight of evidence method; Susceptibility map; Southern Italy;
D O I
10.3301/ROL.2015.184
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
In this work a GIS-based statistical analysis was used to evaluate shallow-landslide susceptibility along a section of highway "A3, Salerno-Reggio Calabria", between Cosenza Sud and Altilia (northern Calabria, Italy). The study applies the weight of evidence (WofE) method, which is useful in determining landslide susceptibility in large areas with complex geological and geomorphological settings. The statistical analysis is based on past shallow -landslides, geological, pedological and topographic factors, which represent the most relevant landslide predisposing factors. The quality of the proposed model, particularly the fitting performance, was assessed; the landslide database was divided into a training set to obtain the model and a testing set to estimate the model quality. The susceptibility map was classified into five susceptibility classes: very low, low, moderate, high, and very high. About 34% of the study area falls in high to very high susceptible classes and most of the landslides mapped (86%) occur in the same classes. The validation results showed satisfactory agreement between the susceptibility map and the landslides locations; over 83% of the landslides of the testing set are correctly classified falling in high and very high susceptibility areas. Also, the prediction rate curve had shown an area under curve (AUC) value of 80.2% which demonstrates the robustness and good reliability of the landslide susceptibility model. According to these results, we conclude that the map produced by the WofE model is reliable and the methodology applied in the study produced high performance, and satisfactory results, which may be useful for land planning policy.
引用
收藏
页码:155 / 158
页数:4
相关论文
共 50 条
  • [1] Statistical analysis for assessing shallow-landslide susceptibility in South Tyrol (south-eastern Alps, Italy)
    Piacentini, Daniela
    Troiani, Francesco
    Soldati, Mauro
    Notarnicola, Claudia
    Savelli, Daniele
    Schneiderbauer, Stefan
    Strada, Claudia
    GEOMORPHOLOGY, 2012, 151 : 196 - 206
  • [2] Shallow-landslide susceptibility in the Costa Viola mountain ridge (southern Calabria, Italy) with considerations on the role of causal factors
    Giulio G. R. Iovine
    Roberto Greco
    Stefano L. Gariano
    Annamaria D. Pellegrino
    Oreste G. Terranova
    Natural Hazards, 2014, 73 : 111 - 136
  • [3] Shallow-landslide susceptibility in the Costa Viola mountain ridge (southern Calabria, Italy) with considerations on the role of causal factors
    Iovine, Giulio G. R.
    Greco, Roberto
    Gariano, Stefano L.
    Pellegrino, Annamaria D.
    Terranova, Oreste G.
    NATURAL HAZARDS, 2014, 73 (01) : 111 - 136
  • [4] Landslide susceptibility assessment in the Ferro Torrent basin (Calabria, south Italy) using a GIS-based Conditional Analysis method
    Rago, Valeria
    Conforti, Massimo
    Muto, Francesco
    Critelli, Salvatore
    RENDICONTI ONLINE SOCIETA GEOLOGICA ITALIANA, 2013, 24 : 257 - 259
  • [5] A new GIS-based multivariate statistical analysis for landslide susceptibility zoning
    Bovolenta, R.
    Federici, B.
    Marzocchi, R.
    Berardi, R.
    LANDSLIDES AND ENGINEERED SLOPES: EXPERIENCE, THEORY AND PRACTICE, VOLS 1-3, 2016, : 511 - 516
  • [6] Modeling Shallow Landslide Susceptibility and Assessment of the Relative Importance of Predisposing Factors, through a GIS-Based Statistical Analysis
    Conforti, Massimo
    Ietto, Fabio
    GEOSCIENCES, 2021, 11 (08)
  • [7] Application and validation of bivariate GIS-based landslide susceptibility assessment for the Vitravo river catchment (Calabria, south Italy)
    Conforti, Massimo
    Robustelli, Gaetano
    Muto, Francesco
    Critelli, Salvatore
    NATURAL HAZARDS, 2012, 61 (01) : 127 - 141
  • [8] Application and validation of bivariate GIS-based landslide susceptibility assessment for the Vitravo river catchment (Calabria, south Italy)
    Massimo Conforti
    Gaetano Robustelli
    Francesco Muto
    Salvatore Critelli
    Natural Hazards, 2012, 61 : 127 - 141
  • [9] GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy
    Mancini, F.
    Ceppi, C.
    Ritrovato, G.
    NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2010, 10 (09) : 1851 - 1864
  • [10] The evaluation and the sensitivity analysis of GIS-based landslide susceptibility models
    Chang, H
    Kim, NK
    GEOSCIENCES JOURNAL, 2004, 8 (04) : 415 - 423