Asghar Kouhpeima; Sadat Feiznia
Abstract
Landslide causes many social and economic losses in many parts of the world every year. These losses can be greatly reduced by using appropriate management measures such as mapping landslide susceptibility mapping in the basin. The aim of this study is landslide susceptibility mapping using Mahalanobis ...
Read More
Landslide causes many social and economic losses in many parts of the world every year. These losses can be greatly reduced by using appropriate management measures such as mapping landslide susceptibility mapping in the basin. The aim of this study is landslide susceptibility mapping using Mahalanobis distance in the Latyan catchment. First, a total of 208 cases of landslides identificated and geo-referenced using geographic information systems based on an interpretation of aerial photographs and extensive field surveys and provided a landslide inventory map. The map of 12 factors, including rainfall, land use, distance to fault, distance from river, distance from road, lithology, altitude, slope, aspect, plan curvature, Peak Ground Acceleration and topographic wetness index as the most important factors in landslides was prepared. Then the correlating each factor and the landslide was examined. Finally landslide susceptibility zoning map was provided based on the Mahalanobis distance in Latyan catchment. To evaluate the results, the ROC and chi-square tests were used. The results show more than 80 % of the catchment located in range of high and very high susceptibility classes and need to suitable management operations. AUC index (area under the curve ROC) for this model is achieved to 0.896 or 89.6% which represent capability and high accuracy. Chi-square test results also reflect the proper separation of landslide susceptibility classes by model.
