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Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques
Massari, Christian1; Su, Chun-Hsu2; Brocca, Luca1; Sang, Yan-Fang3; Ciabatta, Luca1; Ryu, Dongryeol2; Wagner, Wolfgang4
2017-09-01
Source PublicationREMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
Volume198Pages:17-29
Corresponding AuthorMassari, Christian(christian.massari@irpi.cnr.it)
AbstractReal-time de-noising of satellite-derived soil moisture observations presents opportunities to deliver more accurate and timely satellite data for direct satellite users. So far, the most commonly used techniques for reducing the impact of noise in the retrieved satellite soil moisture observations have been based on moving average filters and Fourier based methods. This paper introduces a new alternative wavelet based approach called Wiener-Wavelet-Based Filter (WiW), which uses an entropy based de-noising method to design a causal version of the filter. WiW is used as a post-retrieval processing tool to enhance the quality of observations derived from one active (the Advanced Scatterometer, ASCAT) and one passive (the Advanced Microwave Scanning Radiometer for Earth Observing System, AMSRE) satellite sensors. The filter is then compared with two candidate de-noising techniques, namely: i) a Wiener causal filter introduced by Su et al. (2013) and ii) a conventional moving average filter. The validation is carried out globally at 173 (for AMSRE) and 243 (for ASCAT) soil moisture stations. Results show that all the three de-noising techniques can increase the agreement between satellite and in situ measurements in terms of correlation and signal-to-noise ratio. The Wiener-based methods show least signal distortion and demonstrate to be conservative in retaining the signal information in de-noised data. Importantly, the Wiener filters can be calibrated with the data at hand, without the need for auxiliary data. (C) 2017 Elsevier Inc. All rights reserved.
KeywordDe-noising Wavelet Satellite soil moisture observations Near real time
DOI10.1016/j.rse.2017.05.037
WOS KeywordERROR CHARACTERIZATION ; SERIES ANALYSIS ; DECOMPOSITION ; COMPLEXITY ; THRESHOLD ; DATASETS
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[91647110] ; Institute of Geographic Sciences and Natural Resources Research, CAS ; Youth Innovation Promotion Association, CAS[2017074]
Funding OrganizationNational Natural Science Foundation of China ; Institute of Geographic Sciences and Natural Resources Research, CAS ; Youth Innovation Promotion Association, CAS
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000406818500002
PublisherELSEVIER SCIENCE INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/61457
Collection中国科学院地理科学与资源研究所
Corresponding AuthorMassari, Christian
Affiliation1.CNR, Res Inst Geo Hydrol Protect, Perugia, Italy
2.Univ Melbourne, Dept Infrastruct Engn, Parkville, Vic, Australia
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
4.Vienna Univ Technol, Dept Geodesy & Geoinformat, Vienna, Austria
Recommended Citation
GB/T 7714
Massari, Christian,Su, Chun-Hsu,Brocca, Luca,et al. Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques[J]. REMOTE SENSING OF ENVIRONMENT,2017,198:17-29.
APA Massari, Christian.,Su, Chun-Hsu.,Brocca, Luca.,Sang, Yan-Fang.,Ciabatta, Luca.,...&Wagner, Wolfgang.(2017).Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques.REMOTE SENSING OF ENVIRONMENT,198,17-29.
MLA Massari, Christian,et al."Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques".REMOTE SENSING OF ENVIRONMENT 198(2017):17-29.
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