Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran; Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, Enschede, 7514 AE, Netherlands; Department of Watershed and Arid Zone Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, 49189-434, Iran; Forest Research Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran; School of Earth Sciences and Resources, China University of Geosciences Beijing, Beijing, 100083, China; Department of Earth Sciences, University of Adelaide, Adelaide, SA 5005, Australia
Recommended Citation:
Pourghasemi H.R.,Sadhasivam N.,Amiri M.,et al. Landslide susceptibility assessment and mapping using state-of-the art machine learning techniques[J]. Natural Hazards,2021-01-01,108(1)