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Spatial prediction of rainfall-induced shallow landslides using gene expression programming integrated with GIS: a case study in Vietnam

Author

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  • Nhat-Duc Hoang

    (Duy Tan University)

  • Dieu Tien Bui

    (University College of Southeast Norway)

Abstract

Shallow landslide represents one of the most devastating morphodynamic processes that bring about great destructions to human life and infrastructure. Landslide spatial prediction can significantly help government agencies in land use and mitigation measure planning. Nevertheless, landslide spatial modeling remains a very challenging problem due to its inherent complexity. This study proposes an integration of geographical information system (GIS) and gene expression programming (GEP) for predicting rainfall-induced shallow landslide occurrences in Son La Province, Vietnam. A landslide inventory map has been constructed based on historical landslide locations. Furthermore, a dataset which features 12 influencing factors is collected using GIS technology. Based on the GEP algorithm and the collected dataset, an empirical model for spatial prediction of the shallow landslide has been established by means of natural selection. The predictive capability of the model has been verified by the area under the curve calculation. Experimental results point out that the newly proposed approach is a promising tool for shallow landslide prediction.

Suggested Citation

  • Nhat-Duc Hoang & Dieu Tien Bui, 2018. "Spatial prediction of rainfall-induced shallow landslides using gene expression programming integrated with GIS: a case study in 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. 92(3), pages 1871-1887, July.
    • Handle: RePEc:spr:nathaz:v:92:y:2018:i:3:d:10.1007_s11069-018-3286-z
    DOI: 10.1007/s11069-018-3286-z
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    References listed on IDEAS

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    1. repec:dau:papers:123456789/11413 is not listed on IDEAS
    2. Quang-Khanh Nguyen & Dieu Tien Bui & Nhat-Duc Hoang & Phan Trong Trinh & Viet-Ha Nguyen & Isık Yilmaz, 2017. "A Novel Hybrid Approach Based on Instance Based Learning Classifier and Rotation Forest Ensemble for Spatial Prediction of Rainfall-Induced Shallow Landslides using GIS," Sustainability, MDPI, vol. 9(5), pages 1-24, May.
    3. Michael Ahlheim & Oliver Frör & Antonia Heinke & Alwin Keil & Nguyen Minh Duc & Pham Van Dinh & Camille Saint-Macary & Manfred Zeller, 2008. "Landslides in mountainous regions of Northern Vietnam: Causes, protection strategies and the assessment of economic losses," Diskussionspapiere aus dem Institut für Volkswirtschaftslehre der Universität Hohenheim 298/2008, Department of Economics, University of Hohenheim, Germany.
    4. Paolo Magliulo & Antonio Di Lisio & Filippo Russo & Antonio Zelano, 2008. "Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: a case study in southern Italy," 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. 47(3), pages 411-435, December.
    5. Giulio Iovine & Roberto Greco & Stefano Gariano & Annamaria Pellegrino & Oreste Terranova, 2014. "Shallow-landslide susceptibility in the Costa Viola mountain ridge (southern Calabria, Italy) with considerations on the role of causal factors," 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. 73(1), pages 111-136, August.
    6. Paraskevas Tsangaratos & Andreas Benardos, 2014. "Estimating landslide susceptibility through a artificial neural network classifier," 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. 74(3), pages 1489-1516, December.
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    2. 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.
    3. Hang Wang & Gang Tian & Yonghong Zhao & Yuqing Xie & Qiong Zhang & Andong Xu & Xiaofan Li, 2019. "Dynamic modeling of Meiping landslide process," 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. 96(2), pages 879-892, March.

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