Journal article

Multi-scale analysis of bias correction of soil moisture

C-H Su, D Ryu



Remote sensing, in situ networks and models are now providing unprecedented information for environmental monitoring. To conjunctively use multi-source data nominally representing an identical variable, one must resolve biases existing between these disparate sources, and the characteristics of the biases can be non-trivial due to spatio-temporal variability of the target variable, inter-sensor differences with variable measurement supports. One such example is of soil moisture (SM) monitoring. Triple collocation (TC) based bias correction is a powerful statistical method that is increasingly being used to address this issue, but is only applicable to the linear regime, whereas the non-linea..

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University of Melbourne Researchers


Awarded by Australian Research Council (ARC)

Funding Acknowledgements

We thank Wade Crow for valuable discussions and Clara Draper for her critiques of the early drafts. We acknowledge gratefully the feedback of Simon Zwieback, two anonymous reviewers, Wolfgang Wagner, and Editor Niko Verhoest in the refinement of our manuscript. We also thank all who contributed to the data sets used in this study. Kyeamba in situ data were produced by colleagues at Monash University and the University of Melbourne who have been involved in the OzNet programme. AMSR-E data were produced by Richard de Jeu and colleagues at Vrije University Amsterdam and NASA. The MERRA-Land data set was provided by NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The land cover/use map was produced by merging land cover (Lymburner et al., 2010) and land use (Australian Bureau of Rural Science, 2010) data sets. The recalibrated precipitation data of the Australian Water Availability Project (AWAP) (Jones et al., 2009) were obtained from the Australian Bureau of Meteorology. National soil data (McKenzie et al., 2005) were provided by the Australian Collaborative Land Evaluation Program ACLEP, endorsed through the National Committee on Soil and Terrain NCST ( The 9 s digital elevation map is obtained from Geoscience Australia (2008). This research was conducted with financial support from the Australian Research Council (ARC Linkage Project No. LP110200520) and the Bureau of Meteorology, Australia.