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A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter
Cao, RY (Cao, Ruyin)1; Chen, Y (Chen, Yang)1; Shen, MG (Shen, Miaogen)2; Chen, J (Chen, Jin)3; Zhou, J (Zhou, Jin)1; Wang, C (Wang, Cong)4; Yang, W (Yang, Wei)5
Source PublicationREMOTE SENSING OF ENVIRONMENT
2018-11-01
Volume217Issue:0Pages:244-257
DOI10.1016/j.rse.2018.08.022
Abstract

High-quality Normalized Difference Vegetation Index (NDVI) time-series data are important for many regional and global ecological and environmental applications. Unfortunately, residual noise in current NDVI time-series products greatly hinders their further applications. Several noise-reduction methods have been proposed during the past two decades, but two important issues remain to be resolved. First, the methods usually perform poorly for cases of continuous missing data in the NDVI time series. Second, they generally assume negatively biased noise in the NDVI time series and thus erroneously raise some local low NDVI values in certain cases (e.g., the harvest period for multi-season crops).We therefore developed a new noise-reduction algorithm called the Spatial-Temporal Savitzky-Golay (STSG) method. The new method assumes discontinuous clouds in space and employs neighboring pixels to assist in the noise reduction of the target pixel in a particular year. The relationship between the NDVI of neighboring pixels and that of the target pixel was obtained from multi-year NDVI time series thanks to the accumulation of NDVI data over many years, which would have been impossible a decade ago. We tested STSG on 16-day composite MODIS NDVI time-series data from 2001 to 2016 in regions of mainland China and 11 phenology camera sites in North American. The results showed that STSG performed significantly better compared with four previous widely used methods (i.e., the Asymmetric Gaussian, Double Logistic, Fourier-based, and Savitzky-Golay filter methods). One obvious advantage was that STSG was able to address the problem of temporally continuous NDVI gaps. STSG effectively increased local low NDVI values and simultaneously avoided overcorrecting low NDVI values during the crop harvest period. In addition, implementing STSG required only raw MODIS NDVI time-series products without any additional burden of data requirements. All of these advantages make STSG a promising noise-reduction method for generating high quality NDVI time-series data.

Subject Area生态学
WOS IDWOS:000447570900019
Language英语
Indexed BySCIE
KeywordDigital Repeat Photography Satellite Sensor Data Vegetation Phenology Harmonic-analysis Modis Ndvi Green-up Forest Reflectance Landsat Images
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
Cooperation Status国际
ISSN0034-4257
Department高寒生态重点实验室
PublisherELSEVIER SCIENCE INC
Citation statistics
Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itpcas.ac.cn/handle/131C11/8518
Collection图书馆
Corresponding AuthorChen, J (Chen, Jin)
Affiliation1.Univ Elect Sci & Technol China, Sch Resources & Environm, 2006 Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China;
2.Chinese Acad Sci, CAS Ctr Excellence Tibetan Plateau Earth Sci, Inst Tibetan Plateau Res, Key Lab Alpine Ecol & Biodivers, 16 Lincui Rd, Beijing 100101, Peoples R China;
3.Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China;
4.Univ Calif Santa Cruz, Dept Environm Studies, Santa Cruz, CA 95064 USA;
5.Chiba Univ, Ctr Environm Remote Sensing, Chiba 2638522, Japan.
Recommended Citation
GB/T 7714
Cao, RY ,Chen, Y ,Shen, MG ,et al. A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter[J]. REMOTE SENSING OF ENVIRONMENT,2018,217(0):244-257.
APA Cao, RY .,Chen, Y .,Shen, MG .,Chen, J .,Zhou, J .,...&Yang, W .(2018).A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter.REMOTE SENSING OF ENVIRONMENT,217(0),244-257.
MLA Cao, RY ,et al."A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter".REMOTE SENSING OF ENVIRONMENT 217.0(2018):244-257.
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