Efficiency assessment of two statistical land slid hazard zonation models Models: valuing information and valuing area accumulation (Case study: Shastkalate forest, Gorgan)

Identification of susceptible areas to landslide occurrence is one of the basic measures to reduce the possible risk and hazard management. The main aim of this research was to compare applicability of two statistical landslide hazard zonation models (valuing information and valuing area accumulation) in the Shastkalate forest, Gorgan, Golestan province. By using fielding works, the occurred land slides in the study area were gathered and rectified by GPS. The occurred land slides map was generated using GIS software. By review of previous works and field works, the seven following factors were recognized as primary effective factors on the landslide occurrence: altitude, slope, aspect, rainfall, geology, distance from fault, and distance from hydrographic network. After preparing the map for above-mentioned factors in GIS, these maps were crossed with the occurred landslide map. Landslides amounts and their areas were computed in each class. After determining the rate of each factor (element), land slide zonation was performed in GIS by statistical models i.e., valuing information and valuing area accumulation according to area density and the weighted quantitative amounts. The efficiency of output results of models was assessed by DR and QS indices. The results of DR index showed that both models had better functioned to recognize the hazard classes with high danger than ones with low danger. The results showed that in the study area that was analyzed by QS index, the valuing information model with QS=1.039 had relative desirability than the valuing area accumulation with QS=0.45.