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Evaluation of the effects of uncertainty on the predictions of landslide occurrences using the Shannon entropy theory and Dempster–Shafer theory

Author

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  • Amin Hosseinpoor Milaghardan

    (University of Tehran)

  • Rahim Ali Abbaspour

    (University of Tehran)

  • Mina Khalesian

    (University of Tehran)

Abstract

One of the requirements for planning and decision-making to develop the infrastructures is to prepare the landslide occurrence hazard map. For this purpose, in this article, the Shannon entropy and Dempster–Shafer intuition theory methods were used to prepare the hazard map and applying the data uncertainty in the Tutkabon region, Guilan Province. In this study, parameters of the slope, elevation, geomorphological conditions, the curvature of the earth, proximity to the river and proximity to faults were used as the affecting factors on the landslide occurrence. By using these parameters, the map of the landslide occurrence hazard was prepared using the entropy index; besides, the belief values were calculated by the Dempster–Shafer method. To investigate the uncertainty, the disbelief and uncertainty values were calculated by the Dempster–Shafer method. Besides, in the Shannon entropy method the maps were compared before and after applying the entropy. Finally, by evaluating the results using comparing the landslide occurrence places in the study area and modeled hazard map, the value of 0.69 was obtained for the area under the prediction rate curve (as the parameter of prediction total precision) in the status with entropy and the value of 0.54 was obtained for the status without entropy. Similarly, the evaluation of the hazard belief map by the Dempster–Shafer method indicates that 65% of the landslide occurrence places occur in the classes of high and very high hazard and the value of 0.74 was obtained for the area under the prediction rate curve in the belief map.

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  • Amin Hosseinpoor Milaghardan & Rahim Ali Abbaspour & Mina Khalesian, 2020. "Evaluation of the effects of uncertainty on the predictions of landslide occurrences using the Shannon entropy theory and Dempster–Shafer theory," 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. 100(1), pages 49-67, January.
  • Handle: RePEc:spr:nathaz:v:100:y:2020:i:1:d:10.1007_s11069-019-03798-8
    DOI: 10.1007/s11069-019-03798-8
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    References listed on IDEAS

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    1. Donatella Caniani & Stefania Pascale & Francesco Sdao & Aurelia Sole, 2008. "Neural networks and landslide susceptibility: a case study of the urban area of Potenza," 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. 45(1), pages 55-72, April.
    2. Krishna Devkota & Amar Regmi & Hamid Pourghasemi & Kohki Yoshida & Biswajeet Pradhan & In Ryu & Megh Dhital & Omar Althuwaynee, 2013. "Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya," 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. 65(1), pages 135-165, January.
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    Cited by:

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    3. Sara Beheshtifar, 2023. "Identification of landslide-prone zones using a GIS-based multi-criteria decision analysis and region-growing algorithm in uncertain conditions," 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. 115(2), pages 1475-1497, January.

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