phenofit: An R package for extracting vegetation phenology from time series remote sensing
文献类型：期刊论文
| 作者 | Kong, Dongdong3,4; McVicar, Tim R.5; Xiao, Mingzhong6; Zhang, Yongqiang1; Pena-Arancibia, Jorge L.5; Filippa, Gianluca2; Xie, Yuxuan3; Gu, Xihui3,4 |
| 刊名 | METHODS IN ECOLOGY AND EVOLUTION
 |
| 出版日期 | 2022-04-27 |
| 页码 | 20 |
| ISSN号 | 2041-210X |
| 关键词 | cloud contamination R language satellite data time series reconstruction vegetation indices vegetation phenology |
| DOI | 10.1111/2041-210X.13870 |
| 通讯作者 | Xiao, Mingzhong(xmingzh@mail2.sysu.edu.cn) ; Gu, Xihui(guxh@cug.edu.cn) |
| 英文摘要 | Satellite-derived vegetation indices (VIs) provide a way to analyse vegetation phenology over decades globally. However, these data are often contaminated by different kinds of optical noise (e.g. cloud, cloud shadow, snow, aerosol), making accurate phenology extraction challenging. We present an open-source state-of-the-art R package called phenofit$$ phenofit $$ to extract vegetation phenological information from satellite-derived VIs. phenofit$$ phenofit $$ adopts state-of-the-art phenology extraction methods, such as a weight updating function for reducing optical noise contamination, a growing season division function for separating the VI time series into different vegetation cycles, and rough and fine fitting functions for reconstructing VI time series. They work together to make phenology extraction from frequently contaminated VIs easier and more accurate. Compared against other widely used phenology extraction tools, for example, TIMESAT$$ \mathrm{TIMESAT} $$ and phenopix$$ phenopix $$, phenofit$$ phenofit $$ provides flexible input and output options, a practical growing season division function, rich curve fitting and phenology extraction functions, and robust performance under different kinds of optical noise. In addition to working with VIs from mesoscale satellites (e.g. MODIS and AVHRR), phenofit$$ phenofit $$ can also reconstruct vegetation time series and extract phenology using other sources, such as VIs from high-resolution optical satellites (e.g. Sentinel-2 and Landsat) and radar satellites (e.g. Sentinel-1), vegetation greenness indices from digital cameras and gross primary production estimations from eddy-covariance sites. As such, phenofit$$ phenofit $$ can contribute to the study of ecological process dynamics and assist in effective modelling of global change impacts on vegetation, as caused by climate variability and human intervention. Code and data of case studies are available at (Kong, 2022a). |
| WOS关键词 | LAND-SURFACE PHENOLOGY ; TIBETAN PLATEAU ; FOREST PHENOLOGY ; GROWING-SEASON ; CLIMATE-CHANGE ; SENTINEL-2 ; DYNAMICS ; QUALITY ; INDEX ; SENSITIVITY |
| 资助项目 | National Natural Science Foundation of China[4210011820] ; Fundamental Research Funds for the Central Universities ; China University of Geosciences (Wuhan)[CUG2106107] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| 出版者 | WILEY |
| WOS记录号 | WOS:000794236900001 |
| 资助机构 | National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; China University of Geosciences (Wuhan) |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/176393]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xiao, Mingzhong; Gu, Xihui |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China 2.Environm Protect Agcy Aosta Valley, Climate Change Unit, Valle Daosta, Italy 3.China Univ Geosci, Sch Environm Studies, Dept Atmospher Sci, Wuhan, Peoples R China 4.Ctr Severe Weather & Climate & Hydrogeol Hazards, Wuhan, Peoples R China 5.CSIRO Land & Water, Black Mt Sci & Innovat Pk, Canberra, ACT, Australia 6.Sun Yat Sen Univ, Ctr Water Resources & Environm, Sch Civil Engn, Guangzhou, Peoples R China |
| 推荐引用方式 GB/T 7714 | Kong, Dongdong,McVicar, Tim R.,Xiao, Mingzhong,et al. phenofit: An R package for extracting vegetation phenology from time series remote sensing[J]. METHODS IN ECOLOGY AND EVOLUTION,2022:20. |
| APA | Kong, Dongdong.,McVicar, Tim R..,Xiao, Mingzhong.,Zhang, Yongqiang.,Pena-Arancibia, Jorge L..,...&Gu, Xihui.(2022).phenofit: An R package for extracting vegetation phenology from time series remote sensing.METHODS IN ECOLOGY AND EVOLUTION,20. |
| MLA | Kong, Dongdong,et al."phenofit: An R package for extracting vegetation phenology from time series remote sensing".METHODS IN ECOLOGY AND EVOLUTION (2022):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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