STAR: Spatio-temporal altimeter waveform retracking using sparse representation and conditional random fields
STAR: Spatio-temporal altimeter waveform retracking using sparse representation and conditional random fields
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DOI：
10.1016/j.rse.2017.07.024
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发表时间：
2017-11-01
影响因子：
13.5
通讯作者：
Kusche, Juergen
中科院分区：
文献类型：
--
作者：
Roscher, Ribana;Uebbing, Bernd;Kusche, Juergen
卫星雷达测高是测量海面高度变化的最强大的技术之一，应用范围从业务海洋学到气候研究。在开阔的海洋上，高度计的返回波形通常符合布朗模型，通过反演，估计的形状参数提供了平均表面高度和风速。然而，在沿海地区或内陆水域，波形形状往往受到陆地影响的扭曲，导致峰值或快速衰减的后缘。其结果是，得出的海面高度不太准确，需要用复杂的算法重新处理波形。为此，本文提出了一种新的时空测高重跟踪(STAR)技术。我们表明，与现有的再追踪方法相比，STAR能够获得开阔海洋和沿海地区至少相同质量的海面高度，但循环次数更多，因此保留了更有用的数据。该方法的新颖元素是：(A)通过条件随机场方法整合来自空间和时间相邻波形的信息；(B)子波形检测，其中相关的子波形通过稀疏表示方法从受损或不相关的部分中分离出来；以及(C)使用Dijkstra的算法从多个可能的高度中识别最终的最佳海面高度集。我们将STAR应用于来自Jason-1、Jason-2和Envisat任务的意大利的里雅斯特湾和孟加拉国恒河-雅鲁藏布江-梅赫纳河口沿海地区的研究地点的数据。我们比较了几种已建立的和最新的重新跟踪方法，以及与验潮仪数据的比较。我们的实验表明，与其他方法得到的结果相比，得到的海面高度受离群值的影响要小得多。
Satellite radar altimetry is one of the most powerful techniques for measuring sea surface height variations, with applications ranging from operational oceanography to climate research. Over open oceans, altimeter return waveforms generally correspond to the Brown model, and by inversion, estimated shape parameters provide mean surface height and wind speed. However, in coastal areas or over inland waters, the waveform shape is often distorted by land influence, resulting in peaks or fast decaying trailing edges. As a result, derived sea surface heights are then less accurate and waveforms need to be reprocessed by sophisticated algorithms. To this end, this work suggests a novel Spatio-Temporal Altimetry Retracking (STAR) technique. We show that STAR enables the derivation of sea surface heights over the open ocean as well as over coastal regions of at least the same quality as compared to existing retracking methods, but for a larger number of cycles and thus retaining more useful data. Novel elements of our method are (a) integrating information from spatially and temporally neighboring waveforms through a conditional random field approach, (b) sub-waveform detection, where relevant sub-waveforms are separated from corrupted or non-relevant parts through a sparse representation approach, and (c) identifying the final best set of sea surfaces heights from multiple likely heights using Dijkstra's algorithm. We apply STAR to data from the Jason-1, Jason-2 and Envisat missions for study sites in the Gulf of Trieste, Italy and in the coastal region of the Ganges-Brahmaputra-Meghna estuary, Bangladesh. We compare to several established and recent retracking methods, as well as to tide gauge data. Our experiments suggest that the obtained sea surface heights are significantly less affected by outliers when compared to results obtained by other approaches.