| Popis: |
Fine terrain classification is one of the main applications of Synthetic Aperture Radar (SAR). In the multiband fully polarized SAR operating mode, obtaining information on different frequency bands of the target and polarization response characteristics of a target is possible, which can improve target classification accuracy. However, the existing datasets at home and abroad only have low-resolution fully polarized classification data for individual bands, limited regions, and small samples. Thus, a multidimensional SAR dataset from Hainan is used to construct a multiband fully polarized fine classification dataset with ample sample size, diverse land cover categories, and high classification reliability. This dataset will promote the development of multiband fully polarized SAR classification applications, supported by the high-resolution aerial observation system application calibration and verification project. This paper provides an overview of the composition of the dataset, and describes the information and dataset production methods for the first batch of published data (MPOLSAR-1.0). Furthermore, this study presents the preliminary classification experimental results based on the polarization feature classification and classical machine learning classification methods, providing support for the sharing and application of the dataset. |
