 There is a growing demand for detailed and accurate landslide maps and inventories around the globe, but particularly in hazard prone regions such as the Himalayas. Most standard mapping methods require expert knowledge, supervision and field work. In this study, we use optical data from the rapid eye satellite and topographic factors to analyze the potential of machine learning methods. This article was authored by Omid Gorbanzadeh, Thomas Blasch, Kaleel Golamnya and others.