Assessing landslide vulnerability using bivariate statistical analysis and the frequency ratio model. Case study: Transylvanian Plain (Romania)

被引:14
|
作者
Rosian, Gheorghe [1 ]
Csaba, Horvath [2 ]
Kinga-OIga, Reti [1 ]
Botan, Cristian-Nicolae [2 ]
Gavrila, Ionela Georgiana [2 ]
机构
[1] Univ Babes Bolyai, Fac Environm Sci & Engn, Cluj Napoca, Romania
[2] Univ Babes Bolyai, Fac Geog, Cluj Napoca, Romania
来源
ZEITSCHRIFT FUR GEOMORPHOLOGIE | 2016年 / 60卷 / 04期
关键词
statistical index; frequency ratio; GIS; landslide susceptibility; ROC curve; SUSCEPTIBILITY;
D O I
10.1127/zfg/2016/0404
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Landslides are among the most destructive natural hazards in several regions. Here we summarize our findings regarding this phenomenon in the Transylvanian Plain (Romania) using two susceptibility models: the statistical index and the frequency ratio model. Using Esri's ArcGIS Raster Calculator tool we generated susceptibility maps by summarizing the following twelve landslide predisposition factors: lithology, soil type, fault distance, drainage network distance, roads distance, land use (Corrine Land Cover and NDVI), slope angle, aspect, elevation, plan curvature and soil erosion (RUSLE). The landslide susceptibility has been assessed by computing the values for each class of the predisposing factors and thus evaluating the distribution of the landslide zones within each factor, using Esri's Tabulate Area Tool. The extracted predisposing factors maps have then been reclassified on the basis of the computed values in a raster format. Finally, the landslide susceptibility map has been reclassified into five classes using Natural Breaks (Jenks) classification method. The model performance was assessed with Receiver Operating Characteristic (ROC) curve and the R-index. The models with high number of factors had the lowest accuracy (AUC values being <0.8). The best frequency ratio model (AUC = 0.884) contained only three factors (slope, aspect, elevation) while in the case of the statistical index model the best model (AUC = 0.879) contained four factors (slope, aspect, elevation and NDVI). A significant part (33%) of the study area is characterized by a high to very high degree of susceptibility for landslides.
引用
收藏
页码:359 / 371
页数:13
相关论文
共 50 条
  • [1] Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania)
    Mihaela Constantin
    Martin Bednarik
    Marta C. Jurchescu
    Marius Vlaicu
    Environmental Earth Sciences, 2011, 63 : 397 - 406
  • [2] Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania)
    Constantin, Mihaela
    Bednarik, Martin
    Jurchescu, Marta C.
    Vlaicu, Marius
    ENVIRONMENTAL EARTH SCIENCES, 2011, 63 (02) : 397 - 406
  • [3] Comparative landslide susceptibility assessment using information value and frequency ratio bivariate statistical methods: a case study from Northwestern Himalayas, Jammu and Kashmir, India
    Imran Khan
    Ashutosh Kainthola
    Harish Bahuguna
    Md. Sarfaraz Asgher
    Arabian Journal of Geosciences, 2024, 17 (8)
  • [4] Landslide susceptibility prediction using frequency ratio model: a case study of Uttarakhand, Himalaya (India)
    Singh, Prafull
    Sur, Ujjwal
    Rai, Praveen Kumar
    Singh, Sushant K.
    PROCEEDINGS OF THE INDIAN NATIONAL SCIENCE ACADEMY, 2023, 89 (03): : 600 - 612
  • [5] Landslide susceptibility prediction using frequency ratio model: a case study of Uttarakhand, Himalaya (India)
    Prafull Singh
    Ujjwal Sur
    Praveen Kumar Rai
    Sushant K. Singh
    Proceedings of the Indian National Science Academy, 2023, 89 : 600 - 612
  • [6] Evaluating the use of training areas in bivariate statistical landslide hazard analysis - a case study in Colombia
    Naranjo, J. L.
    Van Western, C. J.
    Soeters, R.
    I T C Journal, 1994, (03)
  • [7] Landslide Susceptibility Zonation Mapping Using Bivariate Statistical Frequency Ratio method and GIS: A Case Study in Part of SH 37 Ghat Road, Nadugani, Panthalur Taluk, The Nilgiris
    Saranaathan, S. E.
    Mani, S.
    Ramesh, V.
    Prasanna Venkatesh, S.
    JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2021, 49 (02) : 275 - 291
  • [8] Landslide Susceptibility Zonation Mapping Using Bivariate Statistical Frequency Ratio method and GIS: A Case Study in Part of SH 37 Ghat Road, Nadugani, Panthalur Taluk, The Nilgiris
    S. E. Saranaathan
    S. Mani
    V. Ramesh
    S. Prasanna Venkatesh
    Journal of the Indian Society of Remote Sensing, 2021, 49 : 275 - 291
  • [9] Landslide susceptibility assessment using Frequency Ratio, a case study of northern Pakistan
    Khan, Hawas
    Shafique, Muhammad
    Khan, Muhammad A.
    Bacha, Mian A.
    Shah, Safeer U.
    Calligaris, Chiara
    EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES, 2019, 22 (01): : 11 - 24
  • [10] Assessing shallow landslide susceptibility by using the Generalized Additive Model: a case study
    Bartelletti, Carlotta
    Galanti, Yuri
    Barsanti, Michele
    Giannecchini, Roberto
    Avanzi, Giacomo D'Amato
    Persichillo, Maria Giuseppina
    Bordoni, Massimiliano
    Meisina, Claudia
    Cevasco, Andrea
    Galve, Jorge Pedro
    RENDICONTI ONLINE SOCIETA GEOLOGICA ITALIANA, 2018, 46 : 115 - 121