Ghiasi, S., Rajabzadeh, F., Najirda, S., Feiznia, S., Nazari Samani, A. (2017). A determination of effective factors on shallow landslide occurrence in Khiov-Chai watershed. , 9(2), 140-154. doi: 10.22092/ijwmse.2017.109697
Seid Saeid Ghiasi; Faezeh Rajabzadeh; Somayye Najirda; Sadat Feiznia; Aliakbar Nazari Samani. "A determination of effective factors on shallow landslide occurrence in Khiov-Chai watershed". , 9, 2, 2017, 140-154. doi: 10.22092/ijwmse.2017.109697
Ghiasi, S., Rajabzadeh, F., Najirda, S., Feiznia, S., Nazari Samani, A. (2017). 'A determination of effective factors on shallow landslide occurrence in Khiov-Chai watershed', , 9(2), pp. 140-154. doi: 10.22092/ijwmse.2017.109697
Ghiasi, S., Rajabzadeh, F., Najirda, S., Feiznia, S., Nazari Samani, A. A determination of effective factors on shallow landslide occurrence in Khiov-Chai watershed. , 2017; 9(2): 140-154. doi: 10.22092/ijwmse.2017.109697

A determination of effective factors on shallow landslide occurrence in Khiov-Chai watershed

مهندسی و مدیریت آبخیز
Article 3, Volume 9, Issue 2, July 2017, Pages 140-154    PDF (1.32 M)
Document Type: Research Paper
DOI: 10.22092/ijwmse.2017.109697
Authors
Seid Saeid Ghiasi1; Faezeh Rajabzadeh2; Somayye Najirda* 3; Sadat Feiznia4; Aliakbar Nazari Samani5
1Young Researchers and Elite Club, Science and Research Branch, Islamic Azad University, Tehran, Ira
2Assistant Professor, Shahr-e-Qods Branch, Islamic Azad University, Iran
3Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran
4Professor, Faculty of Rehabilitation Dry and Mountain Areas, University of Tehran, Iran
5Associate Professor, Faculty of Rehabilitation Dry and Mountain Areas, University of Tehran, Iran
Abstract
Shallow landslide susceptibility assessment by using appropriate methods and determine of effective factors in reduce of its hazards is so effective. The aim of this study is to determine the effective factors on shallow landslide occurrence and investigation of Statistical Index Method (SIM) efficiency for landslide susceptibility mapping. So, determination of each class of factors’ weights was accomplished by using SIM. That was done by adoption of inventory landslide map and ten initial factors including: slope, aspect, rainfall, altitude, drainage density, plan curvature, land use, geology, geomorphological faces and rock unit sensitivity to erosion in ArcGIS 9.3. Then model efficiency was evaluated by using percentage of area under ROC curve and the results showed high accuracy (0.95) of SIM. Principal Component Analysis (PCA) was used for determination of primary causative factors of shallow landslide occurrence. Results showed that five variables of rainfall, slope, aspect, rock unit sensitivity to erosion and plain curvature are the most effective factors on landslide occurrence, respectively.
Keywords
ArcGIS 9.3; ROC curve; PCA; Statistical Index Method; Susceptibility
References
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