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Open AccessArticle

GIS-Based Evaluation of Landslide Susceptibility Models Using Certainty Factors and Functional Trees-Based Ensemble Techniques

by 1,2 and 1,2,*
1
College of Geology & Environment, Xi’an University of Science and Technology, Xi’an 710054, China
2
Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi’an 710021, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(1), 16; https://doi.org/10.3390/app10010016
Received: 15 October 2019 / Revised: 25 November 2019 / Accepted: 25 November 2019 / Published: 18 December 2019
(This article belongs to the Special Issue Recent Advances in Geographic Information System for Earth Sciences)
The main purpose of this paper is to use ensembles techniques of functional tree-based bagging, rotation forest, and dagging (functional trees (FT), bagging-functional trees (BFT), rotation forest-functional trees (RFFT), dagging-functional trees (DFT)) for landslide susceptibility modeling in Zichang County, China. Firstly, 263 landslides were identified, and the landslide inventory map was established, and the landslide locations were randomly divided into 70% (training data) and 30% (validation data). Then, 14 landslide conditioning factors were selected. Furthermore, the correlation analysis between conditioning factors and landslides was applied using the certainty factor method. Hereafter, four models were applied for landslide susceptibility modeling and zoning. Finally, the receiver operating characteristic (ROC) curve and statistical parameters were used to evaluate and compare the overall performance of the four models. The results showed that the area under the curve (AUC) for the four models was larger than 0.74. Among them, the BFT model is better than the other three models. In addition, this study also illustrated that the integrated model is not necessarily more effective than a single model. The ensemble data mining technology used in this study can be used as an effective tool for future land planning and monitoring. View Full-Text
Keywords: landslide susceptibility mapping; ensemble techniques; functional trees; bagging; rotation forest; dagging landslide susceptibility mapping; ensemble techniques; functional trees; bagging; rotation forest; dagging
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MDPI and ACS Style

Zhao, X.; Chen, W. GIS-Based Evaluation of Landslide Susceptibility Models Using Certainty Factors and Functional Trees-Based Ensemble Techniques. Appl. Sci. 2020, 10, 16. https://doi.org/10.3390/app10010016

AMA Style

Zhao X, Chen W. GIS-Based Evaluation of Landslide Susceptibility Models Using Certainty Factors and Functional Trees-Based Ensemble Techniques. Applied Sciences. 2020; 10(1):16. https://doi.org/10.3390/app10010016

Chicago/Turabian Style

Zhao, Xia; Chen, Wei. 2020. "GIS-Based Evaluation of Landslide Susceptibility Models Using Certainty Factors and Functional Trees-Based Ensemble Techniques" Appl. Sci. 10, no. 1: 16. https://doi.org/10.3390/app10010016

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