一个RFI抑制的SMOS L频段多角度亮度温度数据集,跨越了十年 (自2010年以来)
Zhiqing Peng1,2, Tianjie Zhao3, Jiancheng Shi4
1State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China.
Scientific data
|September 8, 2023
概括
一个精制的土壤水分海洋盐度 (SMOS) 数据集可以减少射频干扰 (RFI) 和别名效应. 这种改进的L频段亮度温度数据提高了土壤湿度检索的准确性,并提供了十多年可靠的全球土地参数应用.
科学领域:
- 地球观测 地球观测
- 遥感 遥感 遥感 遥感
- 地质物理学 地质物理学
背景情况:
- 土壤水分海洋盐度 (SMOS) 任务提供全球L频段多角度亮度温度 (TB) 数据.
- 无线电频率干扰 (RFI) 和别名效应降低了SMOS TB数据,影响了陆地参数检索.
- 由于这些干扰,现有的数据集往往会在数据质量方面扎.
研究的目的:
- 为了生成精细的SMOS多角度亮度温度 (TB) 数据集.
- 为了减轻RFI和伪造SMOSTB数据的负面影响.
- 为了提高从SMOS数据中检索土地参数的准确性.
主要方法:
- 采用两步回归方法来平滑和重建SMOSTB数据.
- 数据以发生角度重建,具有显著的结核病不确定性.
- 该方法专门针对抑制RFI和别名效应.
主要成果:
- 经过改进的数据集显示,与土壤湿度主动被动 (SMAP) 结核病数据的一致性更好.
- 观察到与现场测量的土壤湿度有较强的相关性.
- 数据集跨越了十年 (自2010年以来),提供了长期的,RFI压制的记录.
结论:
- 通过RFI压制的SMOS TB数据集为土地参数检索提供了更好的数据质量.
- 这一数据集促进了需要精确的L频段亮度温度测量的增强科学应用.
- 这些精细数据的长期可用性支持陆地表面水文学的持续监测和研究.
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