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Detection of shadows in high spatial resolution ocean satellite data using DINEOF
Remote Sensing of Environment ( IF 11.1 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.rse.2020.112229
Aida Alvera-Azcárate , Dimitry Van der Zande , Alexander Barth , João Felipe Cardoso dos Santos , Charles Troupin , Jean-Marie Beckers

Abstract Cloud shadows present in high spatial resolution remote sensing datasets can affect the quality of the data if they are not properly detected and removed. When working with ocean data, cloud shadows are often difficult to differentiate from non-shadow values, since they show similar spectral characteristics than water pixels. A methodology to detect cloud shadows over the ocean is proposed. The present approach combines a series of tests applied directly to the physical variables derived from the satellite measured radiances, and it therefore does not depend on the wavebands measured by a specific satellite sensor. The tests include a departure from an EOF basis calculated using DINEOF, a threshold test, a proximity to cloud test and a ray tracing test. The weighing of the different tests can be adapted to each case or domain of study. The results are compared to manually detected shadows and to another shadow detection method. The approach works with cloud shadows of all sizes, and also with very small objects shadows, like the shadows projected by offshore windmills.

中文翻译:

使用 DINEOF 检测高空间分辨率海洋卫星数据中的阴影

摘要 高空间分辨率遥感数据集中存在的云阴影如果没有被正确检测和去除会影响数据质量。在处理海洋数据时,云阴影通常难以与非阴影值区分开来,因为它们显示出与水像素相似的光谱特征。提出了一种检测海洋上空云影的方法。本方法结合了一系列直接应用于从卫星测量的辐射导出的物理变量的测试,因此它不依赖于特定卫星传感器测量的波段。测试包括偏离使用 DINEOF 计算的 EOF 基础、阈值测试、接近云测试和光线追踪测试。不同测试的权重可以根据每个案例或研究领域进行调整。将结果与手动检测的阴影和另一种阴影检测方法进行比较。该方法适用于各种大小的云影,也适用于非常小的物体阴影,例如海上风车投射的阴影。
更新日期:2021-02-01
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