Abstract
The arrival of cloud computing platform Google Earth Engine (GEE) in 2010 has brought a breakthrough for analysing and processing spatial data. Applying algorithms on this platform has overcome the limitations of commercial software while processing data in building thematic databases, including land cover data. These data are a critical factor for climate change and hydrological models. This study applied Object-based Random Forest (RF) classification in the Google Earth Engine platform to produce land cover data from Landsat 8 data of the Vu Gia - Thu Bon river basin. The classification results showed 7 categories of land cover consisting of artificial forest, natural forest, paddy area, urban area, rural area, bare land, and body water, with an overall accuracy Kappa of 0.70.
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