Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques

doi:10.1016/j.rse.2017.05.037

	Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques
	Massari, Christian 1; Su, Chun-Hsu 2; Brocca, Luca 1; Sang, Yan-Fang 3; Ciabatta, Luca 1; Ryu, Dongryeol 2; Wagner, Wolfgang 4
刊名	REMOTE SENSING OF ENVIRONMENT
	2017-09-01
卷号	198 页码:17-29
关键词	De-noising Wavelet Satellite soil moisture observations Near real time
ISSN号	0034-4257
DOI	10.1016/j.rse.2017.05.037
通讯作者	Massari, Christian(christian.massari@irpi.cnr.it)
英文摘要	Real-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.
资助项目	National Natural Science Foundation of China[91647110] ; Institute of Geographic Sciences and Natural Resources Research, CAS ; Youth Innovation Promotion Association, CAS[2017074]
WOS关键词	ERROR CHARACTERIZATION ; SERIES ANALYSIS ; DECOMPOSITION ; COMPLEXITY ; THRESHOLD ; DATASETS
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000406818500002
资助机构	National Natural Science Foundation of China ; Institute of Geographic Sciences and Natural Resources Research, CAS ; Youth Innovation Promotion Association, CAS
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/61456]
专题	中国科学院地理科学与资源研究所
通讯作者	Massari, Christian
作者单位	1.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
推荐引用方式 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.