Sea Ice Thickness Measurement Using Spaceborne GNSS-R: First Results With TechDemoSat-1 Data
Sea Ice Thickness Measurement Using Spaceborne GNSS-R: First Results With TechDemoSat-1 Data
复制标题
DOI：
10.1109/jstars.2020.2966880
复制
发表时间：
2020-01
影响因子：
5.5
通讯作者：
Q. Yan;Weimin Huang
中科院分区：
文献类型：
--
作者：
Q. Yan;Weimin Huang
在这篇文章中，一个有效的示意图估计海冰厚度（SIT）的反射率（$\Gamma$）与TechDemoSat-1（TDS-1）全球导航卫星系统反射计数据产生。在这里，$\Gamma$被公式化为由于SIT和底层海水的反射系数的传播损耗的乘积。当只考虑相干反射信号时，表面粗糙度对$\Gamma$的影响被忽略。实际上，镜面反射点处的$\Gamma$首先使用TDS-1数据生成。之后，SIT计算TDS-1 $\Gamma$的基础上提出的反射率模型，并验证了两套参考SIT数据;一个是由土壤水分海洋盐度（SMOS）卫星，另一个是SMOS/土壤水分主被动（SMAP）测量组合。该分析是在SIT小于1 m的数据上进行的。经比较，TDS-1 SIT与参考SIT具有较好的一致性，与SMOS的相关系数r = 0.84，均方根差（RMSD）为9.39 cm;与SMOS/SMAP的相关系数r = 0.67，均方根差（RMSD）为9.49 cm。这证明了所开发的模型的适用性和TDS-1数据的实用性SIT估计。此外，该方法被证明是有用的，以提高现有的海冰检测精度。
In this article, an effective schematic is developed for estimating sea ice thickness (SIT) from the reflectivity ($\Gamma$) produced with TechDemoSat-1 (TDS-1) Global Navigation Satellite System-Reflectometry data. Here, $\Gamma$ is formulated as the product of the propagation loss due to SIT and the reflection coefficient of underlying seawater. The effect of surface roughness on $\Gamma$ is neglected when only considering signals of coherent reflection. In practice, $\Gamma$ at the specular point is first generated using TDS-1 data. Afterwards, SIT is calculated from TDS-1 $\Gamma$ based on the proposed reflectivity model, and verified with two sets of reference SIT data; one is obtained by the Soil Moisture Ocean Salinity (SMOS) satellite, and the other is the combined SMOS/Soil Moisture Active Passive (SMAP) measurements. This analysis is performed on the data with SIT less than 1 m. Through comparison, good consistency between the derived TDS-1 SIT and the reference SIT is obtained, with a correlation coefficient ($r$) of 0.84 and a root-mean-square difference (RMSD) of 9.39 cm with SMOS, and an $r$ of 0.67 and an RMSD of 9.49 cm with SMOS/SMAP, which demonstrates the applicability of the developed model and the utility of TDS-1 data for SIT estimation. In addition, this method is proved to be useful for improving existing sea ice detection accuracy.