نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، بخش تحقیقات حفاظت خاک و آبخیزداری، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و
2 استادیار، بخش تحقیقات جنگلها و مراتع، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان خوزستان، سازمان تحقیقات، آموزش و ترویج
3 عضو هیات علمی مرکز تحقیقات و آموزش کشاورزی و منابعطبیعی خراسانرضوی
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Landslide is one of the geomorphological and geological phenomena that plays an effective role in changing the shape of the earth's surface. The purpose of this research is to spatially model landslide susceptibility using two methods: generalized linear model (GLM) and support vector machine (SVM) and compare the efficiency of these models in zoning landslide susceptibility in Karganeh Watershed, Lorestan Province. The research method in this study is applied in terms of purpose and in terms of descriptive-analytical nature, library methods, field visits and modeling are used. For this purpose, the distribution map of landslides in the region including 95 landslides was prepared and randomly divided into two groups for model training (70%) and model validation (30%). Also, 16 factors affecting the occurrence of landslides in the studied area were identified according to the review of extensive sources and digital layers were prepared in the geographic information system. Then, the landslide hazard map was prepared based on the two mentioned methods in the ModEco software environment. Next, in order to evaluate the accuracy of the modeling and compare the efficiency of the models, the relative performance recognition index (ROC) was used. The results showed that the support vector machine (SVM) method with ROC equal to 0.913 was chosen as the best model for the basin. Support vector machine algorithm provides not only better results. The predicted map is reliable and can be used for planning future land use and reducing landslide susceptibility in the study area.
کلیدواژهها [English]
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