| A Simple Method for Detecting Phenological Change From Time Series of Vegetation Index | |
| Chen, J (Chen, Jin)1; Rao, YH (Rao, Yuhan)1; Shen, MG (Shen, Miaogen)2,3; Wang, C (Wang, Cong)1; Zhou, Y (Zhou, Yuan)1; Ma, L (Ma, Lei)1; Tang, YH (Tang, Yanhong)4; Yang, X (Yang, Xi)5,6; Chen, J | |
| Source Publication | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
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| 2016 | |
| Volume | 54Issue:6Pages:3436-3449 |
| DOI | 10.1109/TGRS.2016.2518167 |
| Abstract | Remote sensing is a valuable way to retrieve spatially continuous information on vegetation phenological changes, which are widely used as an indicator of climate change. We propose a simple method called weighted cross-correlogram spectral matching-phenology (CCSM-P), which combines CCSM and a weighted correlation system, for detecting vegetation phenological changes by using multiyear vegetation index (VI) time series. In experiments with simulated enhanced VI (EVI) for various scenarios, CCSM-P exhibited high accuracy and robustness to noise and the potential to capture long-term phenological change trends. For a temperate grassland in northern China, CCSM-P retrieved more reasonable vegetation spring phenology fromModerate Resolution Imaging Spectroradiometer (MODIS) EVI images than the MODIS phenology product (MCD12Q2). When validated against field phenological observations in five of the AmeriFlux Network sites in the U.S. (four deciduous broadleaf forest sites and a closed shrublands site), and a cropland site in China, CCSM-P exhibited mean absolute differences (MADs) ranging from 2 to 10 days (median: 4.2 days), whereas MAD of non-CCSM methods showed larger variations, ranging from 5 to 58 days (median: 21.3 days). This is because CCSM-P integrates field phenological observations. Compared with non-CCSM methods, which are widely used to identify phenological events, CCSM-P is more accurate and less dependent on prior knowledge (thresholds or predefined functions), which indicates its effectiveness and applicability for detecting year-to-year variations and long-term change trends in phenology, and should facilitate more reliable assessments of phenological changes in climate change studies. |
| Subject Area | 普通生物学 |
| WOS ID | WOS:000377477100027 |
| Language | 英语 |
| Indexed By | SCI |
| Keyword | Winter-wheat Phenology Land-surface Phenology Green-up Date Spring Phenology Tibetan Plateau Climate-change Growing-season Satellite China Variability |
| Cooperation Status | 国际 |
| Department | 生态 |
| Subtype | Article |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.itpcas.ac.cn/handle/131C11/7688 |
| Collection | 图书馆 |
| Corresponding Author | Chen, J |
| Affiliation | 1.Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China 2.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Alpine Ecol & Biodivers, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China 4.Natl Inst Environm Studies, Ibaraki 3058506, Japan 5.Brown Univ, Dept Geol Sci, Providence, RI 02912 USA 6.Marine Biol Lab, Ctr Ecosyst, Woods Hole, MA 02543 USA |
| Recommended Citation GB/T 7714 | Chen, J ,Rao, YH ,Shen, MG ,et al. A Simple Method for Detecting Phenological Change From Time Series of Vegetation Index[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2016,54(6):3436-3449. |
| APA | Chen, J .,Rao, YH .,Shen, MG .,Wang, C .,Zhou, Y .,...&Chen, J.(2016).A Simple Method for Detecting Phenological Change From Time Series of Vegetation Index.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,54(6),3436-3449. |
| MLA | Chen, J ,et al."A Simple Method for Detecting Phenological Change From Time Series of Vegetation Index".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 54.6(2016):3436-3449. |
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| File Name/Size | DocType | Version | Access | License | ||
| V.54(6) 3436-3449 20（2949KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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