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A Convolutional Neural Network Architecture for Sentinel-1 and AMSR2 Data Fusion
2020
IEEE Transactions on Geoscience and Remote Sensing
With a growing number of different satellite sensors, data fusion offers great potential in many applications. In this work, a convolutional neural network (CNN) architecture is presented for fusing Sentinel-1 synthetic aperture radar (SAR) imagery and the Advanced Microwave Scanning Radiometer 2 (AMSR2) data. The CNN is applied to the prediction of Arctic sea ice for marine navigation and as input to sea ice forecast models. This generic model is specifically well suited for fusing data
doi:10.1109/tgrs.2020.3004539
fatcat:fzh25y65gvc6nmtxjtreqjghju