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Global evaluation of gap-filling approaches for seasonal NDVI with considering vegetation growth trajectory, protection of key point, noise resistance and curve stability
Liu, Ronggao1; Shang, Rong1,2; Liu, Yang1; Lu, Xiaoliang3
2017-02-01
Source PublicationREMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
Volume189Pages:164-179
Corresponding AuthorLiu, Ronggao(liurg@igsnrr.ac.cn)
AbstractA variety of approaches are available to fill the gaps in the time series of vegetation parameters estimated from satellite observations. In this paper, a scheme considering vegetation growth trajectory, protection of key point, noise resistance and curve stability was proposed to evaluate the gap-filling approaches. Six approaches for gap filling were globally evaluated pixel-by-pixel based on a reference NDVI generated from MODIS observations during the past 15 years. The evaluated approaches include the Fourier-based approach (Fourier), the double logistic model (DL), the iterative interpolation for data reconstruction (IDR), the Whittaker smoother (Whit), the Savitzky-Golay filter (SG) andthe locally adjusted cubic spline capping approach (LACC). Considering the five aspects, the ranks of the overall performance are LACC > Fourier > IDR > DL > SG > Whit. The six approaches are similar in filling the gaps and remaining the curve stability but there are large difference in protection of key points and noise resistance. The SG is sensitive to noises and the Whit is poor in protection of key points. In the monsoon regions of India, all evaluated approaches don't work well. This paper provides some new views for evaluating the gap filling approaches that will be helpful in selecting the optimal approach to reconstruct the time series of parameters for data applications. (C) 2016 Elsevier Inc All rights reserved.
KeywordMODIS NDVI time series Gap filling Seasonal patterns Vegetation phenology
DOI10.1016/j.rse.2016.11.023
WOS KeywordTIME-SERIES DATA ; MODIS NDVI ; HARMONIC-ANALYSIS ; PHENOLOGY ; PRODUCTS ; REDUCTION ; FILTER ; EXTRACTION
Indexed BySCI
Language英语
Funding ProjectKey Research and Development Programs for Global Change and Adaptation[2016YFA0600201] ; National Natural Science Foundation from China[41171285] ; Chinese Academy of Sciences[XDA05090303]
Funding OrganizationKey Research and Development Programs for Global Change and Adaptation ; National Natural Science Foundation from China ; Chinese Academy of Sciences
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000393005400013
PublisherELSEVIER SCIENCE INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64938
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Ronggao
Affiliation1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Marine Biol Lab, Ctr Ecosyst, Woods Hole, MA 02543 USA
Recommended Citation
GB/T 7714
Liu, Ronggao,Shang, Rong,Liu, Yang,et al. Global evaluation of gap-filling approaches for seasonal NDVI with considering vegetation growth trajectory, protection of key point, noise resistance and curve stability[J]. REMOTE SENSING OF ENVIRONMENT,2017,189:164-179.
APA Liu, Ronggao,Shang, Rong,Liu, Yang,&Lu, Xiaoliang.(2017).Global evaluation of gap-filling approaches for seasonal NDVI with considering vegetation growth trajectory, protection of key point, noise resistance and curve stability.REMOTE SENSING OF ENVIRONMENT,189,164-179.
MLA Liu, Ronggao,et al."Global evaluation of gap-filling approaches for seasonal NDVI with considering vegetation growth trajectory, protection of key point, noise resistance and curve stability".REMOTE SENSING OF ENVIRONMENT 189(2017):164-179.
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