Methods to Remove the Border Noise From Sentinel-1 Synthetic Aperture Radar Data: Implications and Importance For Time-Series Analysis
Methods to Remove the Border Noise From Sentinel-1 Synthetic Aperture Radar Data: Implications and Importance For Time-Series Analysis
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DOI：
10.1109/jstars.2017.2787650
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发表时间：
2018-03-01
影响因子：
5.5
通讯作者：
Wagner, Wolfgang
中科院分区：
文献类型：
--
作者：
Ali, Iftikhar;Cao, Senmao;Wagner, Wolfgang
由欧洲空间局仪器处理设施生成的Sentinel-1 GRD（地面距离探测）一级产品在图像边界处存在噪声伪影，这些伪影在卫星交叉轨迹的左右两侧以及数据沿轨迹的开始和结束处都相当一致。Sentinel-1的边界噪声干扰了反向散射的干净和一致的时间序列的产生。当涉及到大规模的数据处理时，无论是从空间覆盖还是数据量上来说，数据质量控制和管理都是一项非常具有挑战性的任务。在本文中，我们评估了三种去除Sentinel-1边界噪声的技术，并将结果与Sentinel应用平台Sentinel-1工具箱中实现的现有“Sentinel-1 GRD边界噪声去除”算法进行了比较。1对新提出的算法进行验证和评估，使用随机样本，其中包含从完整的Sentinel-1存档中选择的1500个Sentinel-1场景。该方法成功地达到了所需的精度水平，并解决了边界噪声引起的时间序列异常问题。
The Sentinel-1 GRD (ground range detected) Level-1 product generated by the Instrument Processing Facility of the European Space Agency has noise artifacts at the image borders, which are quite consistent at both left and right sides of the satellite's cross track and at the start and end of the data take along track. The Sentinel-1 border noise troubles the creation of clean and consistence time series of backscatter. Data quality control and management become very challenging tasks, when it comes to the large-scale data processing, both in terms of spatial coverage and data volume. In this paper, we evaluate three techniques for removing the Sentinel-1 border noise and compare the results with the existing "Sentinel-1 GRD Border Noise Removal" algorithm implemented in the Sentinel-1 toolbox of the Sentinel application platform. 1 Validation and evaluation of the newly proposed algorithms was done using random samples containing 1500 Sentinel-1 scenes selected from a complete Sentinel-1 archive. The newly proposed approach has successfully achieved the required level of accuracy and solved the issue of time-series anomalies due to the border noise.