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Fuzzy Shannon entropy: a hybrid GIS-based Landslide Susceptibility Mapping method


Roodposhti, MS and Aryal, J and Shahabi, H and Safarrad, T, Fuzzy Shannon entropy: a hybrid GIS-based Landslide Susceptibility Mapping method, Entropy, 18, (10) Article e18100343. ISSN 1099-4300 (2016) [Refereed Article]


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Copyright 2016 by the authors; licensee MDPI, Basel, Switzerland. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.3390/e18100343


Assessing Landslide Susceptibility Mapping (LSM) contributes to reducing the risk of living with landslides. Handling the vagueness associated with LSM is a challenging task. Here we show the application of hybrid GIS-based LSM. The hybrid approach embraces fuzzy membership functions (FMFs) in combination with Shannon entropy, a well-known information theory-based method. Nine landslide-related criteria, along with an inventory of landslides containing 108 recent and historic landslide points, are used to prepare a susceptibility map. A random split into training (≈70%) and testing (≈30%) samples are used for training and validation of the LSM model. The study area - Izeh - is located in the Khuzestan province of Iran, a highly susceptible landslide zone. The performance of the hybrid method is evaluated using receiver operating characteristics (ROC) curves in combination with area under the curve (AUC). The performance of the proposed hybrid method with AUC of 0.934 is superior to multi-criteria evaluation approaches using a subjective scheme in this research in comparison with a previous study using the same dataset through extended fuzzy multi-criteria evaluation with AUC value of 0.894, and was built on the basis of decision makersí evaluation in the same study area.

Item Details

Item Type:Refereed Article
Keywords:Shannon entropy, fuzzy membership function (FMF), landslide susceptibility mapping (LSM), Izeh
Research Division:Engineering
Research Group:Geomatic engineering
Research Field:Geospatial information systems and geospatial data modelling
Objective Division:Environmental Policy, Climate Change and Natural Hazards
Objective Group:Natural hazards
Objective Field:Natural hazards not elsewhere classified
UTAS Author:Roodposhti, MS (Mr Majid Roodposhti)
UTAS Author:Aryal, J (Dr Jagannath Aryal)
ID Code:111700
Year Published:2016
Web of Science® Times Cited:54
Deposited By:Geography and Spatial Science
Deposited On:2016-09-30
Last Modified:2017-11-01
Downloads:230 View Download Statistics

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