Abstract

The study focused on actual demands in the field of remote sensing for building the landcover map from remote sensing data Sentinel-2 based on the random forest classification method. In the  orientation of water resource monitoring, the combination of remote sensing data and water resource computational model builds water resource scenarios for direct service of monitoring and decision support for climate change adaptation as well as socio-economic development planning. Land cover is the combination of many components such as vegetation cover, soil and water surface under advantages of natural factors such as the sun, wind, rainstorm, etc. Flows in the river basin is are not only impacted by the land cover but also by topographic impacts. In fact, there existed relationships between the distribution of land cover objects and topographic surface with the characteristics of topography, soil and climatic conditions. The article introduced the method to build the landcover database from remote sensing data Sentinel-2 based on the random forest classification method on the cloud computing platform Google Earth Engine. A case study using Sentinel-2 data collected in 2020 in Louangphabang province in northern part of Lao PDR