Next Article in Journal
Impact of Tectonic, Glacial and Contour Current Processes on the Late Cenozoic Sedimentary Development of the Southeast Greenland Margin
Previous Article in Journal
A Geophysical-Geochemical Approach to the Study of the Paleogene Julian—Slovenian Basin “Megabeds” (Southern Alps—Northwestern Dinarides, Italy/Slovenia)
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle

A Hybrid Spatial Multi-Criteria Evaluation Method for Mapping Landslide Susceptible Areas in Kullu Valley, Himalayas

1
Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria
2
Department of Geology, University of Delhi, New Delhi-06, Delhi 110007, India
*
Author to whom correspondence should be addressed.
Geosciences 2019, 9(4), 156; https://doi.org/10.3390/geosciences9040156
Received: 28 February 2019 / Revised: 28 March 2019 / Accepted: 1 April 2019 / Published: 3 April 2019
(This article belongs to the Section Natural Hazards)
  |  
PDF [5357 KB, uploaded 8 April 2019]
  |  

Abstract

In this paper we report our results from analysing a hybrid spatial multi-criteria evaluation (SMCE) method for generating landslide susceptibility mapping (LSM). This study is the first of its kind in the Kullu valley, Himalayas. We used eight related geospatial conditioning factors from three main groups: geological, morphological and topographical factors. Our landslide inventory dataset has a total of 149 GPS points of landslide locations, collected based on a field survey in July 2018. The relationships between landslide locations and conditioning factors were determined using the GIS-based statistical methods of frequency ratio (FR), multi-criteria decision-making (MCDM) and the integration method of hybrid SMCE. We compared the performance of applied methods by dividing the inventory into testing (70%) and validation (30%) datasets. The area under the curve (AUC) was used to validate the results. The integration method of hybrid SMCE gave the highest accuracy rate (0.910) compared to the other two methods, with 0.797 and 0.907 accuracy rates for the analytical hierarchy process (AHP) and FR, respectively. The applied methodologies are easily transferable to other areas, and the resulting landslide susceptibility maps (LSMs) can be useful for risk mitigation and development planning purposes in the Kullu valley, Himalayas. View Full-Text
Keywords: natural hazards; landslide susceptibility mapping (LSM); frequency ratio (FR); multi-criteria decision-making (MCDM) natural hazards; landslide susceptibility mapping (LSM); frequency ratio (FR); multi-criteria decision-making (MCDM)
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Meena, S.R.; Mishra, B.K.; Tavakkoli Piralilou, S. A Hybrid Spatial Multi-Criteria Evaluation Method for Mapping Landslide Susceptible Areas in Kullu Valley, Himalayas. Geosciences 2019, 9, 156.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Geosciences EISSN 2076-3263 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top