Fusing AMSR-E and QuikSCAT Imagery for Improved Sea Ice Recognition
Fusing AMSR-E and QuikSCAT Imagery for Improved Sea Ice Recognition
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DOI：
10.1109/tgrs.2009.2013632
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发表时间：
2009-03
影响因子：
8.2
通讯作者：
P. Yu;David A Clausi;S. Howell
中科院分区：
文献类型：
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作者：
P. Yu;David A Clausi;S. Howell
研究了用快速散射仪(QuikSCAT)图像数据扩充先进微波对地观测系统(AMSR-E)图像数据对北极西部地区有监督的海冰分类的益处。实验比较了最大似然分类器在使用AMSR-E-Only数据集和使用组合数据时的性能。研究了用于分类的首选波段数量，以及是否可以使用主成分分析(PCA)来降低数据的维度。此外，还研究了训练数据随时间变化的可靠性。添加QuikSCAT通常会以统计显著的方式提高分类器的精度，当使用足够数量的波段时，它永远不会显著降低。结合这些数据集对海冰测绘是有益的。建议使用所有可用的频段，与主成分分析的数据融合不会为这些数据提供任何好处，并且来自特定日期的训练数据在30天内仍然可靠。
The benefits of augmenting Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) image data with Quick Scatterometer (QuikSCAT) image data for supervised sea ice classification in the Western Arctic region are investigated. Experiments compared the performance of a maximum likelihood classifier when used with the AMSR-E-only data set against using the combined data. The preferred number of bands to use for classification was examined, as well as whether principal component analysis (PCA) can be used to reduce the dimensionality of the data. The reliability of training data over time was also investigated. Adding QuikSCAT often improves classifier accuracy in a statistically significant manner and never decreases it significantly when a sufficient number of bands are used. Combining these data sets is beneficial for sea ice mapping. Using all available bands is recommended, data fusion with PCA does not offer any benefit for these data, and training data from a specific date remains reliable within 30 days.