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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #331449
Title: Assessment of the spatial heterogeneity on microwave satellite soil moisture periodic error

Author
item LEI, FANGNI - Wuhan University
item Crow, Wade
item SHEN, HUANFENG - Wuhan University
item SU, CHUN-HSU - University Of Melbourne
item HOLMES, T. - Goddard Space Flight Center

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/1/2017
Publication Date: 2/1/2018
Citation: Lei, F., Crow, W.T., Shen, H., Su, C., Holmes, T. 2018. Assessment of the spatial heterogeneity on microwave satellite soil moisture periodic error. Remote Sensing of Environment. 205:85-99. https://doi.org/10.106/j.rse.2017.11.002.
DOI: https://doi.org/10.106/j.rse.2017.11.002

Interpretive Summary: Satellite-based surface soil moisture retrievals can potentially be used to enhance a wide range of agricultural water resource applications. However, in order to meet this potential, we must first better understand important sources of errors within these retrievals. One significant type of error are periodic artifacts associated with the orbit repeat cycle of the satellite. Here we demonstrate that – for the first time – these temporal periodic errors can be related to the magnitude of spatial land surface heterogeneity present in a given scene. Once we fully understand the source of such errors, we can design mitigation strategies to optimally correct for them and minimize their impact on data quality. Therefore, this research will ultimately be used to improve the quality of remotely-sensed surface soil moisture retrievals available for agricultural drought monitoring and water resource applications.

Technical Abstract: An accurate temporal and spatial characterization of errors is required for the efficient processing, evaluation, and assimilation of remotely-sensed surface soil moisture retrievals. However, empirical evidence exists that passive microwave soil moisture retrievals are prone to periodic artifacts which may complicate their application to data assimilation systems (which commonly treat observational errors as being temporally white). In this paper, the link between such temporally-periodic errors and spatial land surface heterogeneity is examined. Site-specified cases reveal that, when combined with strong spatial heterogeneity, temporal periodicity in satellite sampling patterns (associated with exact repeat intervals of the polar-orbiting satellites) can lead to spectral peaks in soil moisture retrievals. In addition, the global distribution of the most prominent and consistent 8-day spectral peak in the Advanced Microwave Scanning Radiometer – Earth Observing System soil moisture retrievals is revealed via a peak detection method. Through introducing a spatial heterogeneity index which is inspired by the retrieval algorithm, the prediction of the 8-day peaks has been conducted. Both the verification scores and a statistical hypothesis test suggest that the heterogeneity index can adequately predict the occurrence of 8-day spectral peaks. This suggests a predictable relationship between spatial land surface heterogeneity and temporal periodicity in remotely-sensed surface soil moisture retrievals.