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Landslide susceptibility mapping of the Sera River Basin using logistic regression model

Author

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  • Nussaïbah B. Raja

    (Ankara University)

  • Ihsan Çiçek

    (Ankara University)

  • Necla Türkoğlu

    (Ankara University)

  • Olgu Aydin

    (Ankara University)

  • Akiyuki Kawasaki

    (The University of Tokyo)

Abstract

Of the natural hazards in Turkey, landslides are the second most devastating in terms of socio-economic losses, with the majority of landslides occurring in the Eastern Black Sea Region. The aim of this study is to use a statistical approach to carry out a landslide susceptibility assessment in one area at great risk from landslides: the Sera River Basin located in the Eastern Black Sea Region. This paper applies a multivariate statistical approach in the form of a logistics regression model to explore the probability distribution of future landslides in the region. The model attempts to find the best fitting function to describe the relationship between the dependent variable, here the presence or absence of landslides in a region and a set of independent parameters contributing to the occurrence of landslides. The dependent variable (0 for the absence of landslides and 1 for the presence of landslides) was generated using landslide data retrieved from an existing database and expert opinion. The database has information on a few landslides in the region, but is not extensive or complete, and thus unlike those normally used for research. Slope, angle, relief, the natural drainage network (including distance to rivers and the watershed index) and lithology were used as independent parameters in this study. The effect of each parameter was assessed using the corresponding coefficient in the logistic regression function. The results showed that the natural drainage network plays a significant role in determining landslide occurrence and distribution. Landslide susceptibility was evaluated using a predicted map of probability. Zones with high and medium susceptibility to landslides make up 38.8 % of the study area and are located mostly south of the Sera River Basin and along streams.

Suggested Citation

  • Nussaïbah B. Raja & Ihsan Çiçek & Necla Türkoğlu & Olgu Aydin & Akiyuki Kawasaki, 2017. "Landslide susceptibility mapping of the Sera River Basin using logistic regression model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(3), pages 1323-1346, February.
  • Handle: RePEc:spr:nathaz:v:85:y:2017:i:3:d:10.1007_s11069-016-2591-7
    DOI: 10.1007/s11069-016-2591-7
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    References listed on IDEAS

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    5. Hassan Abedi Gheshlaghi & Bakhtiar Feizizadeh, 2021. "GIS-based ensemble modelling of fuzzy system and bivariate statistics as a tool to improve the accuracy of landslide susceptibility mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(2), pages 1981-2014, June.
    6. Chi Yang & Jinghan Wang & Shuyi Li & Ruihan Xiong & Xiaobo Li & Lin Gao & Xu Guo & Chuanming Ma & Hanxiang Xiong & Yang Qiu, 2024. "Landslide Susceptibility Assessment and Future Prediction with Land Use Change and Urbanization towards Sustainable Development: The Case of the Li River Valley in Yongding, China," Sustainability, MDPI, vol. 16(11), pages 1-26, May.
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    9. Ahmed Cemiloglu & Licai Zhu & Agab Bakheet Mohammednour & Mohammad Azarafza & Yaser Ahangari Nanehkaran, 2023. "Landslide Susceptibility Assessment for Maragheh County, Iran, Using the Logistic Regression Algorithm," Land, MDPI, vol. 12(7), pages 1-20, July.
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