Literature DB >> 33100408

Assessment of the impact of spatial heterogeneity on microwave satellite soil moisture periodic error.

Fangni Lei1,2, Wade T Crow1, Huanfeng Shen2, Chun-Hsu Su3, Thomas R H Holmes4, Robert M Parinussa5, Guojie Wang6.   

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 in 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. Both the synthetic experiment and 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 spurious high frequency 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. Three spatial heterogeneity indicators - based on microwave brightness temperature, land cover types, and long-term averaged vegetation index - are proposed to characterize the degree to which the variability of land surface is capable of inducing periodic error into satellite-based soil moisture retrievals. Regions demonstrating 8-day periodic errors are generally consistent with those exhibiting relatively higher heterogeneity indicators. This implies a causal relationship between spatial land surface heterogeneity and temporal periodic error in remotely-sensed surface soil moisture retrievals.

Entities:  

Keywords:  Microwave remote sensing; Periodicity; Satellite-derived soil moisture; Spatial heterogeneity; Spectral analysis

Year:  2017        PMID: 33100408      PMCID: PMC7580830          DOI: 10.1016/j.rse.2017.11.002

Source DB:  PubMed          Journal:  Remote Sens Environ        ISSN: 0034-4257            Impact factor:   10.164


  3 in total

1.  Regions of strong coupling between soil moisture and precipitation.

Authors:  Randal D Koster; Paul A Dirmeyer; Zhichang Guo; Gordon Bonan; Edmond Chan; Peter Cox; C T Gordon; Shinjiro Kanae; Eva Kowalczyk; David Lawrence; Ping Liu; Cheng-Hsuan Lu; Sergey Malyshev; Bryant McAvaney; Ken Mitchell; David Mocko; Taikan Oki; Keith Oleson; Andrew Pitman; Y C Sud; Christopher M Taylor; Diana Verseghy; Ratko Vasic; Yongkang Xue; Tomohito Yamada
Journal:  Science       Date:  2004-08-20       Impact factor: 47.728

2.  Robust smoothing of gridded data in one and higher dimensions with missing values.

Authors:  Damien Garcia
Journal:  Comput Stat Data Anal       Date:  2010-04-01       Impact factor: 1.681

3.  Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data.

Authors:  Jörn P W Scharlemann; David Benz; Simon I Hay; Bethan V Purse; Andrew J Tatem; G R William Wint; David J Rogers
Journal:  PLoS One       Date:  2008-01-09       Impact factor: 3.240

  3 in total

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