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基于Radarsat-2雷达数据具有多极化方式、多分辨率等成像模式的特点,以中国东部海域为研究区选取多景Radarsat-2影像进行海面风速反演研究。采用导入ERA-Interim数据构建初始海面风向的方法,针对不同极化方式的Radarsat-2数据,利用GMF模型和极化率模型组合进行海面风速反演,并将反演风速与ERA-Interim风速数据进行比较分析。结果表明:对于VV极化的Radarsat-2数据采用3种GMF模型均可反演出较高精度的海面风速,其中CMOD4模型总体表现好于其他二者,其均方根误差可达到1.5m/s以内;HH极化Radarsat-2数据采用Kirchhoff模型进行极化转换更适用于海面风速的反演,3种GMF模型之间反演效果差异不大,其均方根误差均在2m/s以内。同时,研究发现VV和HH极化的Radarsat-2数据均表现出高分辨率成像模式影像的风速反演效果优于低分辨率成像模式的特点。
Based on the characteristics of Radarsat-2 radar data, such as multi-polarization and multi-resolution imaging modes, the multi-scene Radarsat-2 images were selected for the retrieval of sea surface wind velocity in the study area of eastern China. Using the method of introducing ERA-Interim data to construct the initial wind direction of the sea surface, Radarsat-2 data of different polarization modes are used to carry out the inversion of sea surface wind velocity by using GMF model and polarizability model combination. The wind speed of ERA-Interim wind speed data For comparative analysis. The results show that the wind speed of sea surface can be inverted by using three kinds of GMF models for Radarsat-2 data of VV polarization. The CMOD4 model performs better than the other two models and the root mean square error can reach 1.5m / s . The polarization inversion of HH-polarized Radarsat-2 data by Kirchhoff model is more suitable for the inversion of sea surface wind speed. The inversion results of the three GMF models show little difference, and the root-mean-square error is within 2m / s. At the same time, it was found that Radarsat-2 data of VV and HH polarizations all showed that the wind velocity inversion of high-resolution imaging mode was better than that of low-resolution imaging mode.