This paper presents Pol-InSAR-Island, the first publicly available multi-frequency Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR) dataset labeled with detailed land cover classes, which serves as a challenging benchmark dataset for land cover classification. In recent years, machine learning has become a powerful tool for remote sensing image analysis. While there are numerou…
The application of deep learning methods to remote sensing data has produced good results in recent studies. A promising application area is automatic land cover classification (semantic segmentation) from very high-resolution satellite imagery. However, the deep learning methods require large, labelled training datasets that are suitable for the study area. Map data can be used as training dat…