Ye N, Walker J P, Bindlish R, Chaubell J, Das N N, Gevaert A I, Jackson T J, Rüdiger C
Department of Civil Engineering, Monash University, Australia.
NASA Godard Space Flight Center, United States.
Remote Sens Environ. 2019 Feb;221:363-372. doi: 10.1016/j.rse.2018.11.033.
The Soil Moisture Active and Passive (SMAP) mission, launched by the National Aeronautics and Space Administration (NASA) on 31 January 2015, was designed to provide global soil moisture every 2 to 3 days at 9 km resolution by downscaling SMAP passive microwave observations obtained at 36 km resolution using active microwave observations at 3 km resolution, and then retrieving soil moisture from the resulting 9 km brightness temperature product. This study evaluated the SMAP Active/Passive (AP) downscaling algorithm together with other resolution enhancement techniques. Airborne passive microwave observations acquired at 1 km resolution over the Murrumbidgee River catchment in south-eastern Australia during the fourth and fifth Soil Moisture Active Passive Experiments (SMAPEx-4/5) were used as reference data. The SMAPEx-4/5 data were collected in May and September 2015, respectively, and aggregated to 9 km for direct comparison with a number of available resolution-enhanced brightness temperature estimates. The results show that the SMAP AP downscaled brightness temperature had a correlation coefficient (R) of 0.84 and Root-Mean-Squared Error (RMSE) of ~10 K, while SMAP Enhanced, Nearest Neighbour, Weighted Average, and the Smoothing Filter-based Modulation (SFIM) brightness temperature estimates had somewhat better performance (RMSEs of ~7 K and an R exceeding 0.9). Although the SFIM had the lowest unbiased RMSE of ~6 K, the effect of cloud cover on Ka-band observations limits data availability.
土壤湿度主动和被动探测（SMAP）任务由美国国家航空航天局（NASA）于2015年1月31日发射，旨在通过将36公里分辨率的SMAP被动微波观测数据与3公里分辨率的主动微波观测数据进行降尺度处理，每2至3天以9公里分辨率提供全球土壤湿度，然后从生成的9公里亮温产品中反演土壤湿度。本研究评估了SMAP主动/被动（AP）降尺度算法以及其他分辨率增强技术。在澳大利亚东南部的墨累本吉河流域进行的第四次和第五次土壤湿度主动被动实验（SMAPEx - 4/5）期间，以1公里分辨率获取的机载被动微波观测数据被用作参考数据。SMAPEx - 4/5数据分别于2015年5月和9月收集，并聚合到9公里分辨率，以便与一些可用的分辨率增强亮温估计值进行直接比较。结果表明，SMAP AP降尺度后的亮温相关系数（R）为0.84，均方根误差（RMSE）约为10 K，而SMAP增强、最近邻、加权平均和基于平滑滤波器的调制（SFIM）亮温估计值的性能略好（RMSE约为7 K，R超过0.9）。尽管SFIM的无偏RMSE最低，约为6 K，但云覆盖对Ka波段观测的影响限制了数据可用性。
