Monitoring the Arctic Seas: How Satellite Altimetry Can Be Used to Detect Open Water in Sea-Ice Regions

Monitoring the Arctic Seas: How Satellite Altimetry Can Be Used to Detect Open Water in Sea-Ice Regions
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DOI:
10.3390/rs9060551
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发表时间:
2017-06
期刊:
Remote. Sens.
影响因子:
--
通讯作者:
F. Müller;D. Dettmering;Wolfgang Bösch;F. Seitz
F. Müller;D. Dettmering;Wolfgang Bösch;F. Seitz
中科院分区:
其他
文献类型:
--
作者:
F. Müller;D. Dettmering;Wolfgang Bösch;F. Seitz

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被海冰包围的开阔水域对海洋-冰-大气相互作用有显著影响,并对北极气候变化有贡献。卫星测高可以探测到这些冰口,并使人们能够估计海面高度和进一步的测高数据衍生产品。该研究基于Envisat和SARAL的高频数据,引入了一种创新的无监督分类方法,用于探测格陵兰海的开放水域。分析了不同地面条件下的测高雷达回波,又称波形。定义了六个波形特征,将雷达回波聚类成不同的组,表示开放水域和海冰波形。因此,采用了K-medoids分割聚类算法和基于记忆的K-nearest neighbor分类方法,内部误分类误差约为2%。与多幅SAR图像的定量比较显示,SARAL的一致性率为76.9%,Envisat的一致性率为70.7%。这些数字在很大程度上取决于SAR图像的质量和两种技术测量之间的时间差。通过几个例子,可以证明一致性率超过90%,真水检测率为94%。创新的分类程序可用于检测不同空间范围的水域,并可应用于所有可用的脉冲限高数据集。
Open water areas surrounded by sea ice significantly influence the ocean-ice-atmosphere interaction and contribute to Arctic climate change. Satellite altimetry can detect these ice openings and enables one to estimate sea surface heights and further altimetry data derived products. This study introduces an innovative, unsupervised classification approach for detecting open water areas in the Greenland Sea based on high-frequency data from Envisat and SARAL. Altimetry radar echoes, also called waveforms, are analyzed regarding different surface conditions. Six waveform features are defined to cluster radar echoes into different groups indicating open water and sea ice waveforms. Therefore, the partitional clustering algorithm K-medoids and the memory-based classification method K-nearest neighbor are employed, yielding an internal misclassification error of about 2%. A quantitative comparison with several SAR images reveals a consistency rate of 76.9% for SARAL and 70.7% for Envisat. These numbers strongly depend on the quality of the SAR images and the time lag between the measurements of both techniques. For a few examples, a consistency rate of more than 90% and a true water detection rate of 94% can be demonstrated. The innovative classification procedure can be used to detect water areas with different spatial extents and can be applied to all available pulse-limited altimetry datasets.