کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4571767 1629255 2012 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran
چکیده انگلیسی

Landslide susceptibility mapping is essential for land use planning and decision-making especially in the mountainous areas. The main objective of this study is to produce landslide susceptibility maps at Safarood basin, Iran using two statistical models such as an index of entropy and conditional probability and to compare the obtained results. At the first stage, landslide locations were identified in the study area by interpretation of aerial photographs and from field investigations. Of the 153 landslides identified, 105 (≈ 70%) locations were used for the landslide susceptibility maps, while the remaining 48 (≈ 30%) cases were used for the model validation. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, distance to faults, distance to rivers, distance to roads, topographic wetness index (TWI), stream power index (SPI), slope–length (LS), land use, and plan curvature were extracted from the spatial database. Using these factors, landslide susceptibility and weights of each factor were analyzed by index of entropy and conditional probability models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and the areas under the curve (AUC) were calculated. The verification results showed that the index of entropy model (AUC = 86.08%) performed slightly better than conditional probability (AUC = 82.75%) model. The produced susceptibility maps can be useful for general land use planning in the Safarood basin, Iran.


► The landslide locations were identified by aerial photograph and field surveys.
► The spatial database including topography, geology and soil factors were constructed.
► We applied index of entropy (IOE) and conditional probability (CP) models for landslide mapping.
► We find that both the models have good predictive capacity.
► The IOE method performed slightly better than the CP model in landslide susceptibility mapping.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: CATENA - Volume 97, October 2012, Pages 71–84
نویسندگان
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