Abedini M., and Tulabi S. 2018. Assessing LNRF, FR, and AHP models in landslide susceptibility mapping index: a comparative study of Nojian watershed in Lorestan province, Iran. Environmental earth sciences, 77(11): 405- 418.
Amir Ahmadi A., Naemi Tabar M., and Gholkar ostadi B. 2017. Prioritize and zoning factors affecting the landslide model entropy (Case study: Bajgiran, Ghochan. Hydrogeomorphology, 3(11): 105-125. (In Persian)
Ariapour M., Bashiri M., and Golkarian A. 2019. Modeling of Mass Movements Using Data Mining Methods in the Southeast of Neyshabur City, Razavi Khorasan Province. Hydrogeomorphology, 5(19): 57-77. (In Persian)
Basu S.R., and Ghatowar L. 1988. Landslides in the Lish Basin of the eastern Himalayas and their control. Geomorphology and Environment. Allababad Geographical Society, Allahabad: 428-443.
Capitani M., Ribolini A., and Federici P.R. 2011. Influence of deep-seated gravitational slope deformations on landslide distributions: a statistical approach. Geomorphology, 201: 127-134.
Chen, W., Zhang, S., Li, R., & Shahabi, H. 2018. Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling. Science of the Total Environment, 644: 1006-1018.
Gholami M., soleymani K., and Nekoee E. 2017. Landslide susceptibility mapping by use of Weight of Evidence (WofE) and Frequency Ratio (FR) and Dempster-Shafer (DSH) models: A case study of Sari-Kiasar region, Northern Iran. Journal of Range and Watershed Management, 70(3): 735-750 (In Persian)
Guha-Sapir D., Below R., and Hoyois P. 2020. EM-DAT: international disaster database. Brussels, Belgium: Université Catholique de Louvain.
HatamiFard R., Mousavi S., and Alimoradi M. 2012. Landslide hazard zonation using AHP model and GIS technique in Khoram Abad City. Geography and Environmental Planning, 23(3): 43-60. (In Persian)
Kornejady A., Ownegh M., and Bahremand, A. 2017. Landslide susceptibility assessment using maximum entropy model with two different data sampling methods. Catena, 152: 144-162.
Lau NN. 2018. Determination of ground displacement of 25 April 2015 Nepal earthquake by GNSS precise point positioning Vietnam. J. Earth. Sci, 40:17–25.
Pham BT., Jaafari A., Prakash I., and Bui, DT. 2019. A novel hybrid intelligent model of support vector machines and the Multiboot ensemble for landslide susceptibility modeling. Bulletin of Engineering Geology and the Environment, 78(4): 2865-2886.
Pourghasemi HR., Moradi HR., and Aghda SF. 2013. Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances. Natural hazards, 69(1): 749-779.
Pradhan B. 2013. A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. Computers & Geosciences, 51: 350-365.
Regmi NR., Giardino JR., Vitek JD., and Dangol V. 2010. Mapping landslide hazards in western Nepal: Comparing qualitative and quantitative approaches. Environmental & Engineering Geoscience, 16(2), 127-142.
Samodra G., Chen G., Sartohadi J., and Kasama K. 2018. Generating landslide inventory by participatory mapping: an example in Purwosari Area, Yogyakarta, Java. Geomorphology, 30(6): 306-313.
Sharma L.P., Patel N., Ghose M.K., and Debnath, P. 2012. Influence of Shannon’s entropy on landslide-causing parameters for vulnerability study and zonation—a case study in Sikkim, India. Arabian Journal of Geosciences,5(5): 421-431.
Song Y., Gong J., Gao S., Wang D., Cui T., Li Y., and Wei B., 2012. Susceptibility assessment of earthquake-induced landslides using Bayesian network: a case study in Beichuan, China. Computers & Geosciences, 42: 189-199.
Tay L.T., Lateh H., Hossain M.K., and Kamil A.A. 2014. Landslide hazard mapping using a Poisson distribution: a case study in Penang Island, Malaysia. In Landslide Science for a Safer Geoenvironment. Springer, Cham. (521-525 pp.).
Wang H.B., Li J.M., Zhou B., Zhou Y., Yuan Z.Q., and Chen Y.P. 2017. Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility. Geoenvironmental Disasters, 4)15(: 1-12.
Wang Q., Li W., Wu Y., Pei Y., and Xie P. 2016. Application of statistical index and index of entropy methods to landslide susceptibility assessment in Gongliu (Xinjiang, China). Environmental Earth Sciences, 75(7): 1-13.
Yalcin A. 2011. A geotechnical study on the landslides in the Trabzon Province, NE, Turkey. Applied clay science, 52: 11-29.
Yufeng S., and Fengxiang J. 2009. Landslide stability analysis based on generalized information entropy in 2009. international conference on environmental science and information application technology, 2: 83-85. IEEE.
Zhang TY., Han L., Zhang H., Zhao YH., Li XA., and Zhao L. 2019. GIS-based landslide susceptibility mapping using hybrid integration approaches of fractal dimension with index of entropy and support vector machine. Journal of Mountain Science, 16(6): 1275-1288.
Zhao H., Yao L., Mei G., Liu T., and Ning Y. 2017. A fuzzy comprehensive evaluation method based on AHP and entropy for a landslide susceptibility map. Entropy, 19(8):1-16.
Zhuang J., Peng J., Wang G., Javed I., Wang Y., and Li W. 2018. Distribution and characteristics of landslide in Loess Plateau: A case study in Shaanxi province. Engineering Geology, 236: 89-96.