Abstract
High resolution synthetic aperture radar (SAR) data have important research significance and application prospects in crop fine classification. In order to make full use of high resolution SAR data, this paper introduced the deep learning semantics segmentation methods, which have already achieved tremendous success in the field of computer vision, into the corn fine classification using SAR images. Therefore, a corn fine classification method, based on U-Net network for high resolution SAR data, was proposed in this paper. Experiments were carried out using one scene high resolution GF-3 SAR data covering Fuyu City, Jilin Province, China. The experimental result shows that the proposed crop fine classification method based on deep learning semantics segmentation method can achieve a satisfactory classification result.
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