| DOI: | 10.5194/hess-19-17-2015
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| Scopus记录号: | 2-s2.0-84920736362
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| 论文题名: | Multi-scale analysis of bias correction of soil moisture |
| 作者: | Su C; -H; , Ryu D
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| 刊名: | Hydrology and Earth System Sciences
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| ISSN: | 10275606
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| 出版年: | 2015
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| 卷: | 19, 期:1 | | 起始页码: | 17
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| 结束页码: | 31
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| 语种: | 英语
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| Scopus关键词: | Moisture
; Remote sensing
; Wavelet analysis
; Environmental Monitoring
; Multi scale analysis
; Multisource data
; Non-linear methods
; Spatio-temporal scale
; Spatiotemporal variability
; Statistical moments
; Wavelet thresholding
; Soil moisture
; correction
; data set
; environmental monitoring
; error analysis
; in situ measurement
; remote sensing
; soil moisture
; spatiotemporal analysis
; threshold
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| 英文摘要: | 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-linear method of statistical moment matching is susceptible to unintended biases originating from measurement error. Since different physical processes that influence SM dynamics may be distinguishable by their characteristic spatio-temporal scales, we propose a multi-timescale linear bias model in the framework of a wavelet-based multi-resolution analysis (MRA). The joint MRA-TC analysis was applied to demonstrate scale-dependent biases between in situ, remotely sensed and modelled SM, the influence of various prospective bias correction schemes on these biases, and lastly to enable multi-scale bias correction and data-adaptive, non-linear de-noising via wavelet thresholding. © 2015 Author(s). |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/78652
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| Appears in Collections: | 气候变化事实与影响
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作者单位: | Department of Infrastructure Engineering, University of Melbourne, Melbourne, VIC, Australia
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| Recommended Citation: | |
Su C,-H,, Ryu D. Multi-scale analysis of bias correction of soil moisture[J]. Hydrology and Earth System Sciences,2015-01-01,19(1)
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