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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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    Cited by:

    1. Quynh Duy Bui & Hang Ha & Dong Thanh Khuc & Dinh Quoc Nguyen & Jason von Meding & Lam Phuong Nguyen & Chinh Luu, 2023. "Landslide susceptibility prediction mapping with advanced ensemble models: Son La province, Vietnam," 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. 116(2), pages 2283-2309, March.
    2. Richard Mind’je & Lanhai Li & Jean Baptiste Nsengiyumva & Christophe Mupenzi & Enan Muhire Nyesheja & Patient Mindje Kayumba & Aboubakar Gasirabo & Egide Hakorimana, 2020. "Landslide susceptibility and influencing factors analysis in Rwanda," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7985-8012, December.
    3. Sandipta Debanshi & Swades Pal, 2020. "Assessing gully erosion susceptibility in Mayurakshi river basin of eastern India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 883-914, February.
    4. Asmita Ahmad & Meutia Farida & Nirmala Juita & Muh Jayadi, 2023. "Soil micromorphology for modeling spatial on landslide susceptibility mapping: a case study in Kelara Subwatershed, Jeneponto Regency of South Sulawesi, Indonesia," 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. 118(2), pages 1445-1462, September.
    5. Shahab S. Band & Saeid Janizadeh & Sunil Saha & Kaustuv Mukherjee & Saeid Khosrobeigi Bozchaloei & Artemi Cerdà & Manouchehr Shokri & Amirhosein Mosavi, 2020. "Evaluating the Efficiency of Different Regression, Decision Tree, and Bayesian Machine Learning Algorithms in Spatial Piping Erosion Susceptibility Using ALOS/PALSAR Data," Land, MDPI, vol. 9(10), pages 1-23, September.
    6. 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.
    7. Di Wang & Mengmeng Hao & Shuai Chen & Ze Meng & Dong Jiang & Fangyu Ding, 2021. "Assessment of landslide susceptibility and risk factors in China," 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. 108(3), pages 3045-3059, September.
    8. Weidong Wang & Zhuolei He & Zheng Han & Yange Li & Jie Dou & Jianling Huang, 2020. "Mapping the susceptibility to landslides based on the deep belief network: a case study in Sichuan Province, China," 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. 103(3), pages 3239-3261, September.
    9. 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.
    10. Mária Barančoková & Matej Šošovička & Peter Barančok & Peter Barančok, 2021. "Predictive Modelling of Landslide Susceptibility in the Western Carpathian Flysch Zone," Land, MDPI, vol. 10(12), pages 1-28, December.

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