EFFICIENCY EVALUATION OF FOUR STATISTICAL LANDSLIDE HAZARD ZONATION METHODS USING GIS

摘要

Prediction of spatial landslide occurrences and landslide hazard zonation is a suitable way to prevent more damages. Selection the best model to predict landslide occurrences help to decrease costs and time. Since different statistical and experimental landslide zonation methods were used by scientists. In this study, capability of four statistical methods including Valuing Information, Valuing Area Accumulation, Relative Effect and Landslide Numerical Risk Factor were investigated in the forested basin of Seyedkalateh watershed at the Ramian, northeast of Iran. An occurred landslides map of study area was generated by GPS and aerial photo interpretation. Topographic and geologic attributes together with land use, distance from fault, road and river were gathered from different creditable sources and maps. These attributes were imported in the GIS and were classified and weighted to main classes and scores. By importing these weighted attributes into mentioned models, the landslide hazard zonation was accomplished in the study area. Evaluation of obtained results of models were done using accumulation ratio in each hazard class and the Dr and Qs factors were calculated to evaluate result of models. Results shows that comparing to other used methods, the Relative Effect (RE) method had high Qs and consequently could better separate the hazard zones.