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Development and application of Shannon’s entropy integrated information value model for landslide susceptibility assessment and zonation in Sikkim Himalayas in India

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  • L. Sharma
  • Nilanchal Patel
  • M. Ghose
  • P. Debnath

Abstract

The state of Sikkim in India has many steep slopes and has been susceptible to landslides. Since 1968 there have been innumerable losses of lives and properties due to landslides. There is an urgent need for advance assessment of degrees of vulnerability and delineation of the most vulnerable zone for shifting of the population and infrastructure to a safer zone. The identification and formulation of most suitable and acceptable method for such assessment is still nascent and research based. In this study, an attempt has been made to integrate the concept of Shannon’s entropy with the information value-based statistical model to evaluate the landslide susceptibility in the study area and assess the improvement made through the integration of Shannon’s entropy by comparing the results with the landslide susceptibility determined from the information value-based statistical model alone. Initially, the thematic layers pertaining to all the causative parameters were overlaid with the help of geographical information system that resulted in the formation of 78,256 numbers of polygons for each one of which landslide susceptibility was determined. For each polygon, the total landslide information value (TLIV) was computed as the summation of the landslide information values determined for the individual sub-categories present within the respective polygons. Again for each polygon, the Shannon’s entropy value of the individual parameters was multiplied with the summation of the landslide information values of all the sub-categories present within the respective parameters. The product values computed for the different causative parameters were summed up to determine the total landslide information value with entropy (TLIV_e). Finally, the entire study area was categorized into five zones of landslides susceptibility based on the TLIV and TLIV_e, respectively. The prediction accuracy of the landslides determined based on the landslide susceptibility derived from TLIV_e was found to be significantly high (91 %) as compared to that derived from TLIV (85 %) indicating the potential contribution of Shannon’s entropy in the improved delineation of the landslide susceptibility zones. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • L. Sharma & Nilanchal Patel & M. Ghose & P. Debnath, 2015. "Development and application of Shannon’s entropy integrated information value model for landslide susceptibility assessment and zonation in Sikkim Himalayas in India," 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. 75(2), pages 1555-1576, January.
  • Handle: RePEc:spr:nathaz:v:75:y:2015:i:2:p:1555-1576
    DOI: 10.1007/s11069-014-1378-y
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    Citations

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    Cited by:

    1. 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.
    2. Hao Pu & Jia Xie & Paul Schonfeld & Taoran Song & Wei Li & Jie Wang & Jianping Hu, 2021. "Railway Alignment Optimization in Mountainous Regions Considering Spatial Geological Hazards: A Sustainable Safety Perspective," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    3. Qianqian Wang & Dongchuan Wang & Yong Huang & Zhiheng Wang & Lihui Zhang & Qiaozhen Guo & Wei Chen & Wengang Chen & Mengqin Sang, 2015. "Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment," Sustainability, MDPI, vol. 7(12), pages 1-17, December.
    4. Chen Cao & Jianping Chen & Wen Zhang & Peihua Xu & Lianjing Zheng & Chun Zhu, 2019. "Geospatial Analysis of Mass-Wasting Susceptibility of Four Small Catchments in Mountainous Area of Miyun County, Beijing," IJERPH, MDPI, vol. 16(15), pages 1-19, August.
    5. Rui-Xuan Tang & E-Chuan Yan & Tao Wen & Xiao-Meng Yin & Wei Tang, 2021. "Comparison of Logistic Regression, Information Value, and Comprehensive Evaluating Model for Landslide Susceptibility Mapping," Sustainability, MDPI, vol. 13(7), pages 1-25, March.

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