Evaluating the Efficiency of Frequency Ratio, Bivariate (Wi), and (Wf) Methods of Landslide Susceptibility Mapping, A Case Study: Vazroud Watershed, Mazandaran Province, N Iran

Solaimani, K; Zandi, J; Habibnejad, M

doi:10.22071/gsj.2015.43116

Evaluating the Efficiency of Frequency Ratio, Bivariate (Wi), and (Wf) Methods of Landslide Susceptibility Mapping, A Case Study: Vazroud Watershed, Mazandaran Province, N Iran

Document Type : Original Research Paper

Authors

K Solaimani ¹

J Zandi ²

M Habibnejad ¹

¹ Professor, Department of Watershed Management, College of Natural Resources Sciences, Agricultural Sciences and Natural Resources University, Sari, Iran

² Ph.D. Student, Department of Watershed Management, College of Natural Resources Sciences, Agricultural Sciences and Natural Resources University, Sari, Iran

10.22071/gsj.2015.43116

Abstract

Over the last few decades, many studies have been resulted in landslide susceptibility maps using different techniques including the probability method (frequency ratio), the Analytical Hierarchy Process (AHP), bivariate, multivariate, logistic regression, fuzzy logic and artificial neural network (ANN). This study aimed to evaluate the susceptibility of the occurrence of landslides in the Vazroud watershed located in MazandaranProvince, north of Iran. The achieved results were based on three methods of frequency ratio model, statistical index (Wi) and weighting factor (Wf), which integrated to Geographical Information System (GIS) and remote sensing techniques. Vazroud as mountainous watershed morphologically is with increasing occurrence of landslides and it caused many failures of the mass movement, which seem continues now. In order to reduce the effects of this occurrence, it is necessary to scientifically assess the area where are susceptible to the landslide. For this reason, landslide susceptible areas were mapped and the landslide occurrence parameters were analyzed using three different methods. The results of these analyseswere confirmed using the relative operating characteristics curve (ROC). The validation process showed that the value for the area under the ROC curve for the Wf method was found to be 0.962, with an estimated standard error of 0.002 and is better in prediction than the other methods of frequency ratio and the statistical index (Wi) model.

Keywords

Landslide

Frequency Ratio Model

Bivariate Statistic

GIS