Prediction of Gully Erosion Using RADAR Sensor of Alos and Maximum Entropy Model in Alvand Basin

The evidences showing that remote sensing has a significant role as a powerful tool around the world, which can reduced the costs and time of projects, especially since they have a comprehensive view of the large areas where are difficult to access. This study has aimed to predict gully erosion using remote sensing data and Maxent model in Alvand basin located in the western part of Kermanshah province, Iran. Alvand basin with a difficulty accessing due to the extent of the minefield during the imposed war and interconnected with Iraq, on the other hand, the shape of Marne lands and absence of proper vegetation have led to acceleration of gully erosion. Therefore, in this study with a combination method of fieldwork and remote sensing which used in the Google Earth environment, then the essential spatial analysis layout has prepared by Maxent model and the zonation of the gully area has digitized as independent variables that introduced to model. In addition, for analysing the ground surface, a digital elevation model of the Alos data has used with 15 environmental layers of 10/m resolution were prepared as dependent variables. Three goals have attained based on this quantitative and statistical model. First, the effect level of each environmental layer has obtained using the Jackknife test. Second, trend of maximum and minimum effects of each parameter has investigated using logistic regression and finally, Potential map of gully erosion was prepared for the whole region. Then the model validation has performed using the ROC curve and the area under the curve (AUC). It has concluded that the most effective index in gully erosion creation related to elevation index, vertical distance from channel level and flow accumulation. The validation is calculated equal to AUC = 0.899, which shows a good level of results.