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The estimation of deforestation in the Amazon Forest is challenge taskbecause of the vast size of the area and the difficulty of direct human access.However, it is a crucial problem in that deforestation results in seriousenvironmental problems such as global climate change, reduced biodiversity,etc. In order to effectively solve the problems, satellite imagery would be agood alternative to estimate the deforestation of the Amazon. With acombination of optical images and Synthetic aperture radar (SAR) images,observation of such a massive area regardless of weather conditions becomepossible. In this paper, we present an accurate deforestation estimation methodwith conventional UNet and comprehensive data processing. The diverse channelsof Sentinel-1, Sentinel-2 and Landsat 8 are carefully selected and utilized totrain deep neural networks. With the proposed method, deforestation status fornovel queries are successfully estimated with high accuracy.

MultiEarth 2022 Deforestation Challenge -- ForestGump