Volume 6, Issue 2 (9-2019)                   2019, 6(2): 165-180 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

darabi shahmari S, saffari A. Landslide susceptibility mapping of Dalahoo Mountains using index of Entropy and Logistic Regression model. Journal title 2019; 6 (2) :165-180
URL: http://jsaeh.khu.ac.ir/article-1-2401-en.html
1- kharazmi university , sdarabi@ut.ac.ir
2- kharazmi university
Abstract:   (2644 Views)

Landslide susceptibility mapping is  essential for  land use  planning and decision-making especially in  the mountainous areas. The main objective of this  study is to produce landslide susceptibility maps (LSM) at Dalahoo basin, Iran  using two statistical models such as an  index of entropy and Logistic Regression and to compare the  obtained results. At the  first stage, landslide locations identified by Natural Resources Department of Kermanshah Province is used to prepare of LSM map. Of the 29 lanslides identified, 21 (≈ 70%) locations were used for the landslide susceptibility maps, while the remaining 8 (≈ 30%) cases were used for the model validation. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, distance to faults, distance to rivers, distance to roads, land use, and  lithology  were extracted from the spatial database. Using these factors,  landslide susceptibility and weights of each factor were analyzed by index of entropy and Logistic Regression models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and  the areas under the curve (AUC) were calculated. The verification results showed that the index of entropy model (AUC = 86.08%) performed slightly better than conditional probability (AUC = 80. 13%) model. The produced susceptibility maps can be useful for general land use  planning in the Dalahoo basin, Iran.

Full-Text [PDF 1546 kb]   (840 Downloads)    
Type of Study: Research | Subject: Special
Received: 2016/03/1 | Accepted: 2019/06/25 | Published: 2019/10/30

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2023 CC BY-NC 4.0 | Journal of Spatial Analysis Environmental hazarts

Designed & Developed by : Yektaweb