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Entropy 2016, 18(10), 343; doi:10.3390/e18100343

Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method

1
Discipline of Geography and Spatial Sciences, School of Land & Food, University of Tasmania, Hobart 7001, Australia
2
Department of Geomorphology, Faculty of Natural Resources, University of Kurdistan, Sanandaj 66177-15175, Iran
3
Department of Geography and Urban Planning, Faculty of Humanities and Social Science, University of Mazandaran, Babolsar 47416-13534, Iran
*
Author to whom correspondence should be addressed.
Academic Editor: Raúl Alcaraz Martínez
Received: 1 August 2016 / Revised: 14 September 2016 / Accepted: 19 September 2016 / Published: 27 September 2016
(This article belongs to the Special Issue Applications of Information Theory in the Geosciences)
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Abstract

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 makers’ evaluation in the same study area. View Full-Text
Keywords: Shannon entropy; fuzzy membership function (FMF); landslide susceptibility mapping (LSM); Izeh Shannon entropy; fuzzy membership function (FMF); landslide susceptibility mapping (LSM); Izeh
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Shadman Roodposhti, M.; Aryal, J.; Shahabi, H.; Safarrad, T. Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method. Entropy 2016, 18, 343.

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