Abstract Recent advances in L-band passive microwave remote sensing provide an unprecedented opportunity to monitor soil moisture at ~40 km spatial resolution around the globe. Nevertheless, retrieval of the accurate high spatial resolution soil moisture maps that are required to satisfy hydro-meteorological and agricultural applications remains a challenge. Currently, a variety of downscaling, otherwise known as disaggregation techniques have been proposed as the solution to disaggregate the coarse passive microwave soil moisture into high-to-medium resolutions. These techniques take advantage of the strengths of both the passive microwave observations of soil moisture having low spatial resolution and the spatially detailed information on land surface features that either influence or represent soil moisture variability. However, such techniques have typically been developed and tested individually under differing weather and climate conditions, meaning that there is no clear guidance on which technique performs the best. Consequently, this paper presents a quantitative assessment of the existing radar-, optical-, radiometer-, and oversampling-based downscaling techniques using a singular extensive data set collected specifically for that purpose, being the Soil Moisture Active Passive Experiment (SMAPEx)-4 and -5 airborne field campaigns, and the OzNet in situ stations, to determine the relative strengths and weaknesses of their performances. The oversampling-based soil moisture product best captured the temporal and spatial variability of the reference soil moisture overall, though the radar-based products had a better temporal agreement with airborne soil moisture during the short SMAPEx-4 period. Moreover, the difference between temporal analysis of products against in situ and airborne soil moisture reference data sets pointed to the fact that relying on in situ measurements alone is not appropriate for validation of spatially enhanced soil moisture maps.

中文翻译：

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替代降尺度土壤水分产品综合分析

摘要 L 波段无源微波遥感的最新进展为以~40 公里的空间分辨率监测全球土壤水分提供了前所未有的机会。然而，检索满足水文气象和农业应用所需的准确的高空间分辨率土壤湿度图仍然是一个挑战。目前，已经提出了各种降尺度，也称为分解技术，作为将粗糙的被动微波土壤水分分解为高到中等分辨率的解决方案。这些技术利用了具有低空间分辨率的土壤水分被动微波观测和影响或代表土壤水分变异性的地表特征的空间详细信息的优势。然而，此类技术通常是在不同的天气和气候条件下单独开发和测试的，这意味着对于哪种技术性能最佳没有明确的指导。因此，本文使用专门为此目的收集的单一广泛数据集，即土壤湿度主动被动实验 (SMAPEx)-4，对现有的基于雷达、光学、辐射计和过采样的降尺度技术进行了定量评估。和 -5 空降野战，以及 OzNet 现场站，以确定其性能的相对优势和劣势。基于过采样的土壤水分产品最好地捕捉了参考土壤水分整体的时间和空间变异性，尽管在短 SMAPEx-4 期间，基于雷达的产品与空气中土壤水分有更好的时间一致性。此外，产品的时间分析与原位和空气土壤水分参考数据集之间的差异表明，仅依靠原位测量不适合验证空间增强的土壤水分图。