Assessment and comparison of combined bivariate and AHP models with logistic regression for landslide susceptibility map
- PDF / 3,104,211 Bytes
- 15 Pages / 595.276 x 790.866 pts Page_size
- 52 Downloads / 225 Views
ORIGINAL PAPER
Assessment and comparison of combined bivariate and AHP models with logistic regression for landslide susceptibility mapping in the Chaharmahal-e-Bakhtiari Province, Iran Ebrahim Karimi Sangchini 1 & Seyed Naim Emami 2 & Naser Tahmasebipour 3 & Hamid Reza Pourghasemi 4 & Seyed Amir Naghibi 5 & Seyed Abdolhossein Arami 6 & Biswajeet Pradhan 7
Received: 3 August 2015 / Accepted: 18 November 2015 / Published online: 10 March 2016 # Saudi Society for Geosciences 2016
Abstract Landslide is one of the most important natural hazards that make numerous financial damages and life losses each year in the worldwide. Identifying the susceptible areas and prioritizing them in order to provide an efficient susceptibility management is very vital. In current study, a comparative analysis was made between combined bivariate and AHP models (bivariate-AHP) with a logistic regression. At first, landslide inventory map of the study area was prepared using extensive field surveys and aerial photographs interpretation. In the next step, nine landslide causative factors were selected including altitude, slope percentage, slope aspect, lithology, distance from faults, streams and roads, land use, and * Hamid Reza Pourghasemi [email protected]; [email protected] 1
Department of Watershed Management Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
2
Institute of Agriculture and Natural Resources, Shahrekord, Iran
3
Department of Watershed Management Engineering, College of Agriculture, Lorestan University, Khorramabad, Iran
4
Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran
5
Department of Watershed Management Engineering, College of Natural Resources, Tarbiat Modares University, Noor, Mazandaran, Iran
6
Combating Desertification, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
7
Department of Civil Engineering, Faculty of Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
precipitation which affect occurrence of the landslides in the study area. Subsequently, landslide susceptibility maps were produced using weighted (AHP) bivariate and logistic regression models. Finally, receiver operating characteristics (ROC) curve was used in order to evaluate the prediction capability of the mentioned models for landslide susceptibility mapping. According to the results, the combined bivariate and AHP models provided slightly higher prediction accuracy than logistic regression model. The combined bivariate and AHP, and logistic regression models had the area under the curve (AUCROC) values of 0.914, and 0.865, respectively. The resultant landslide susceptibility maps can be useful in appropriate watershed management practices and for sustainable development in the regions with similar conditions. Keywords Landslide susceptibility . Combined bivariate and AHP models . Logistic regression . GIS . Iran
Introduction L
Data Loading...
