Next Article in Journal
Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr
Previous Article in Journal
Working with Open BIM Standards to Source Legal Spaces for a 3D Cadastre
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2017, 6(11), 347; https://doi.org/10.3390/ijgi6110347

Variable-Weighted Linear Combination Model for Landslide Susceptibility Mapping: Case Study in the Shennongjia Forestry District, China

School of Civil Engineering, Wuhan University, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
Received: 21 August 2017 / Revised: 31 October 2017 / Accepted: 3 November 2017 / Published: 7 November 2017
View Full-Text   |   Download PDF [4769 KB, uploaded 9 November 2017]   |  

Abstract

A landslide susceptibility map plays an essential role in urban and rural planning. The main purpose of this study is to establish a variable-weighted linear combination model (VWLC) and assess its potential for landslide susceptibility mapping. Firstly, different objective methods are employed for data processing rather than the frequently-used subjective judgments: K-means clustering is used for classification; binarization is introduced to determine buffer length thresholds for locational elements (road, river, and fault); landslide area density is adopted as the contribution index; and a correlation analysis is conducted for suitable factor selection. Secondly, considering the dimension changes of the preference matrix varying with the different locations of the mapping cells, the variable weights of each optimal factor are determined based on the improved analytic hierarchy process (AHP). On this basis, the VWLC model is established and applied to regional landslide susceptibility mapping for the Shennongjia Forestry District, China, where shallow landslides frequently occur. The obtained map is then compared with a map using the traditional WLC, and the results of the comparison show that VWLC is more reasonable, with a higher accuracy, and can be used anywhere that has the same or similar geological and topographical conditions. View Full-Text
Keywords: geographic information system (GIS); landslide; susceptibility; K-means clustering; binarization; analytic hierarchy process (AHP); variable-weighted linear combination; China geographic information system (GIS); landslide; susceptibility; K-means clustering; binarization; analytic hierarchy process (AHP); variable-weighted linear combination; China
Figures

Figure 1

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

Chen, W.; Han, H.; Huang, B.; Huang, Q.; Fu, X. Variable-Weighted Linear Combination Model for Landslide Susceptibility Mapping: Case Study in the Shennongjia Forestry District, China. ISPRS Int. J. Geo-Inf. 2017, 6, 347.

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]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top