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作 者:刘成玉[1] 顾卫[1] 李澜涛[1] 许映军[1]
机构地区:[1]北京师范大学地表过程与资源生态国家重点实验室,北京100875
出 处:《海洋通报》2013年第2期200-207,共8页Marine Science Bulletin
基 金:国家863计划项目(2011AA100505);地表过程与资源生态国家重点实验室项目(2010-TD-02;2011-TDZD-050);国家科技支撑计划项目(2006BAB03A03)
摘 要:对所获取的2008年冬季的辽东湾西岸海域含有海冰的Hyperion高光谱图像进行了大气校正,得到了反射率图像。用ISODATA(Iterative Self-Organizing Data Analysis Technique)聚类分析方法对反射率图像进行计算机自动分类,并结合实测的同时期的海冰反射率光谱确定了不同海冰类型的分布范围。根据不同类型海冰的厚度特征,得到了海冰厚度分级分布图和海冰厚度图。结果表明,Hyperion图像可以区分光谱有区别的冰型,无法区分浮冰和固定冰,可以更清晰地显示出海冰的光谱反射率,与实测光谱曲线更加相似,优于MODIS多光谱图像。同时,用主成分分析方法对海冰Hyperion图像进行了分析。海冰Hyperion图像中,各个波段之间的相关系数都较大,光谱维信息冗余度较大,其中30波段贡献率最高。The hyper-spectral image which contains sea ice of western Liaodong Bay in the winter of 2008 was obtained by the Hyperion sensor. The reflectance image has been retrieved through the atmospheric correction. It was classified by the computer automatic classification using the ISODATA (Iterative Self-Organizing Data Analysis Technique) clustering analysis method. The distributions of different ice types were determined by using the reflectance spectrums measured at the same period. According to the thickness characteristics of different ice types, the maps of different sea ice thickness grades and sea ice thickness were achieved with the classification. The results showed that the Hyperion image could distinguish different sea ice types with different reflectance spectrums, but it couldn't tell the difference between float ice and land fast ice. It could clearly show the reflectance spectrum of sea ice and they were more similar to the measured spectral reflectance curves, which was far better than the MOD1S multi-spectral image. Meanwhile, Hyperion image of the sea ice was also analyzed by use of the principal component analysis. The correlation coefficient between each band was large, and the spectral information redundancy was also huge in the sea ice Hyperion image, with the biggest contribution ratio of band 30.
关 键 词:高光谱遥感 Hyperion图像 渤海海冰
分 类 号:TP75[自动化与计算机技术—检测技术与自动化装置]
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