资源简介

摘要： 提出了一种利用SAR插补因云遮挡导致CCD数据缺失的算法。通过分析云及其阴影的光谱特征,设计出云及其阴影的提取模型,并运用CCD和SAR之间匹配转化算法和有云影响像元的替换运算,得到插补后的新CCD数据。利用高光谱数据反演海面盐度算法所得海面盐度与实测海面盐度做相关性比较分析对本缺失数据插补算法进行检验。结果表明:研究海域中缺失数据区域的海盐反演精度为R2=0.8441,RMSE=0.7031,即SAR插补CCD缺失数据算法具有较强的可靠性和多源遥感数据兼容性,一定程度上恢复了噪声下垫面的实际情况,可以用于融合多传感器生成时空完整、高精度的数据产品。 关键词： 插补算法;  CCD缺失数据;  SAR;  去云;  海面盐度     Abstract: An algorithm of missing CCD data interpolated by SAR due to cloud was proposed in this paper.The core of this algorithm was:by analyzing the spectral characteristics of the cloud and its shadow,the cloud and its shadow extraction model was put forward;the CCD and SAR matching transformation algorithm as well as the cloud-effected pixel replacement operation were then used to generate the new interpolated CCD data.The correlation between the measured sea surface salinity and the retrieved sea surface salinity which was obtained by the CCD data retrieval algorithm which was used to test the above missing data interpolation algorithm.The results demonstrated that the accuracy of retrieved sea surface salinity in the missing data region of the target sea area was R2=0.8441,RMSE=0.7031.Therefore,the algorithm of missing CCD data interpolated by SAR was generally practical and compatible with different sources of data.Moreover,the algorithm restored the actual condition of the noise underlying surface in some extent,and along with multiple sensors,it could generate the complete space-time data products with high precision.

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