Narges Javidan; Ataollah Kavian; Sajad Rajabi; Hamidreza Pourghasemi; Christian Conoscenti; Zeinab Jafarian
Abstract
Slope instability and landslides are important hazards to human activities that often result in the loss of economic resources, property damage and facilities. These hazards occur in the natural or man-made slopes. In the current study, the maximum entropy model was used which is one of the progressive ...
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Slope instability and landslides are important hazards to human activities that often result in the loss of economic resources, property damage and facilities. These hazards occur in the natural or man-made slopes. In the current study, the maximum entropy model was used which is one of the progressive data mining models, in order to modelling landslide susceptibility map for Gorganrood watershed. In the first step, the landslide inventory map was prepared consiste of 351 landslides. 18 geo-environmental factors were selected as predictors, such as: Digital elevation model, slope percent, aspect, distance from fault, distance from river, distance from road, rainfall, landuse, drainage density, lithology, soil texture, plan curvature, profil curvature, lithological formation, Topographic wetness index, LS factor, stream power index, Relative Slope Position and Surface roughness index. Three different sample data sets (S1, S2, and S3) including 70% for training and 30% for validation were randomly prepared to evaluate the robustness of the model. The accuracy of the predictive model was evaluated by drawing receiver operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The ME model performed excellently both in the degree of fitting and in predictive performance (AUC values well above 0.8), which resulted in accurate predictions. Furthermore, In this study the importance of variables was evaluated by the model. Dem (digital elevation model) (32.4% importance), lithology (22.9% importance) and distance from fault (14.8% importance) were identified respectively the main controlling factor among all other variables.
Omid Rahmati; Naser Tahmasebipour; Ali Haghizadeh; Hamidreza Pourghasemi; Bakhtiar Feizizadeh
Abstract
Gully erosion is an important challenge in natural resource management and sustainable development that often has severe environmental, economic, and social consequences. Thus, the objective of the present study is to assess the capability of maximum entropy (ME) model for spatial prediction of gully ...
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Gully erosion is an important challenge in natural resource management and sustainable development that often has severe environmental, economic, and social consequences. Thus, the objective of the present study is to assess the capability of maximum entropy (ME) model for spatial prediction of gully erosion susceptibility at Kashkan-Poldokhtar Watershed, between Lorestan and Ilam provinces, Iran. At first, a gully erosion inventory map was produced using GPS in field surveys. The gully conditioning factors including lithology, soil texture, land use, drainage density, distance to streams, topographic wetness index, altitude, slope percent, slope aspect, plan curvature, and distance from road were selected, and their maps were prepared in geographical information system (GIS). A total of 65 gully locations were divided into two groups (1) training of the model (45 gully occurrences), and (2) validation of the model (20 gully occurrences). The prediction of gully susceptibility and variables importance analysis were carried out based on maximum entropy model using MAXENT software. Finally, the validation of the prediction results was conducted based on the receiver operating characteristic (ROC) curve method, and the area under the curve (AUC) was calculated using MedCalc software. Results indicated that highest gully erosion susceptibility is located on the center parts of the study area. According to validation results, the resulting map of areas susceptible to gully erosion obtained by ME model has a prediction accuracy of 90.7%. In addition, the results demonstrated soil texture, drainage density, lithology, and distance to streams are most important factors and their variable importance index (VII) 23, 18, 15.2, and 15.1 were obtained, respectively. However, altitude, distance from road, slope aspect, land use, topographic wetness index, and plan curvature have a less influence on gully erosion occurrence. Therefore, it was established in current study that the ME is promising of make accurate prediction in gully erosion susceptibility.
