Global evaluation of gap-filling approaches for seasonal NDVI with considering vegetation growth trajectory, protection of key point, noise resistance and curve stability
文献类型：期刊论文
| 作者 | Liu, Ronggao2; Shang, Rong1,2; Liu, Yang2; Lu, Xiaoliang3 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2017-02-01 |
| 卷号 | 189页码:164-179 |
| 关键词 | MODIS NDVI time series Gap filling Seasonal patterns Vegetation phenology |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2016.11.023 |
| 通讯作者 | Liu, Ronggao(liurg@igsnrr.ac.cn) |
| 英文摘要 | A 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. |
| WOS关键词 | TIME-SERIES DATA ; MODIS NDVI ; HARMONIC-ANALYSIS ; PHENOLOGY ; PRODUCTS ; REDUCTION ; FILTER ; EXTRACTION |
| 资助项目 | Key Research and Development Programs for Global Change and Adaptation[2016YFA0600201] ; National Natural Science Foundation from China[41171285] ; Chinese Academy of Sciences[XDA05090303] |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000393005400013 |
| 出版者 | ELSEVIER SCIENCE INC |
| 资助机构 | Key Research and Development Programs for Global Change and Adaptation ; National Natural Science Foundation from China ; Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/64937]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu, Ronggao |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Marine Biol Lab, Ctr Ecosyst, Woods Hole, MA 02543 USA |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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