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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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    1. King, Gary & Zeng, Langche, 2001. "Logistic Regression in Rare Events Data," Political Analysis, Cambridge University Press, vol. 9(2), pages 137-163, January.
    2. Dieu Bui & Owe Lofman & Inge Revhaug & Oystein Dick, 2011. "Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression," 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. 59(3), pages 1413-1444, December.
    3. Mualla Yalçinkaya & Temel Bayrak, 2005. "Comparison of Static, Kinematic and Dynamic Geodetic Deformation Models for Kutlugün Landslide in Northeastern Turkey," 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. 34(1), pages 91-110, January.
    4. Ali Yalcin & Fikri Bulut, 2007. "Landslide susceptibility mapping using GIS and digital photogrammetric techniques: a case study from Ardesen (NE-Turkey)," 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. 41(1), pages 201-226, April.
    5. Alexander Brenning & Stephan Gruber & Martin Hoelzle, 2005. "Sampling and statistical analyses of BTS measurements," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 16(4), pages 383-393, October.
    6. Andrea Fabbri & Chang-Jo Chung & Antonio Cendrero & Juan Remondo, 2003. "Is Prediction of Future Landslides Possible with a GIS?," 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. 30(3), pages 487-503, November.
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    3. 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.
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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. 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.
    7. 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.
    8. 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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