Land use and land cover classification using machine learning algorithms in google earth engine

Remote sensing and GIS-based study of land use/cover dynamics, driving factors, and implications in southern Ethiopia, with special reference to the Legabora watershed

“…In Bangladesh, for example, [ 18 ]; examained combining GIS and machine learning to monitor and predict vegetation vulnerability. Similarly, in China, [ 19 ]; in Bangladesh, [ 20 ]; and in India [ 21 ], have also investigated the potential of this approach. Since the mid-1970s, RS has been considered a quick and valuable tool for accurately documenting changes in land use/cover on regional and worldwide levels.…”