%0 Journal Article %T A novel method based on combing statistical methods for improving the accuracy of landslide susceptibility maps (case study: Mazandaran province) %J Environmental Management Hazards %I %Z 2423-415X %A Atyabi, Sayed Mohammadreza %A Niazmardi, Saeid %A Ali Abbaspour, Rahim %D 2021 %\ 08/23/2021 %V 8 %N 2 %P 99-117 %! A novel method based on combing statistical methods for improving the accuracy of landslide susceptibility maps (case study: Mazandaran province) %K Landslide susceptibility map %K Statistical methods %K conditioning factors of landslide %K Area under the curve %K Mazandaran province %R 10.22059/jhsci.2021.319366.629 %X Landslide is one of the natural hazards which occur worldwide and causes loss of life and property every year. Landslide risk control and management have a vital role in reducing its damage. The first step of landslide risk management is to identify areas prone to landslides, for which different methods have been proposed. Evaluating these methods can provide valuable information to managers and decision-makers. In the present study, the landslide susceptibility map of Mazandaran province was produced using statistical index and confidence factor methods. Besides, to increase the accuracy of the maps, new methods by combining the index of entropy method with each one of statistical index and confidence factor methods have been proposed. To evaluate and compare the methods, 585 landslide data that occurred in a period of 50 years in Mazandaran province have been used. Fifteen conditioning factors have been considered to have the most effects of landslide occurrence, which were divided into four categories: topographic, hydrological, environmental and man-made, and geological. The results showed that topographic factors, among the others, have the most impact on landslide occurrence. In addition, comparing the accuracy of susceptibility maps generated using hybrid methods with SI and CF methods showed an increase of 3% and 3.5% (based on urea under curve index). %U https://jhsci.ut.ac.ir/article_83514_0c655d7751243489a41ad57aeb4921ae.pdf