Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications
文献类型：期刊论文
| 作者 | Ma, Xuanlong4; Zhu, Xiaolin5; Xie, Qiaoyun6; Jin, Jiaxin7; Zhou, Yuke8; Luo, Yunpeng2,9; Liu, Yuxia3,6; Tian, Jiaqi1,5; Zhao, Yuhe4 |
| 刊名 | GLOBAL CHANGE BIOLOGY
 |
| 出版日期 | 2022-09-26 |
| 页码 | 19 |
| 关键词 | big data biodiversity carbon cycle global change public health vegetation dynamics |
| ISSN号 | 1354-1013 |
| DOI | 10.1111/gcb.16436 |
| 通讯作者 | Ma, Xuanlong(xlma@lzu.edu.cn) |
| 英文摘要 | Vegetation phenology has been viewed as the nature's calendar and an integrative indicator of plant-climate interactions. The correct representation of vegetation phenology is important for models to accurately simulate the exchange of carbon, water, and energy between the vegetated land surface and the atmosphere. Remote sensing has advanced the monitoring of vegetation phenology by providing spatially and temporally continuous data that together with conventional ground observations offers a unique contribution to our knowledge about the environmental impact on ecosystems as well as the ecological adaptations and feedback to global climate change. Land surface phenology (LSP) is defined as the use of satellites to monitor seasonal dynamics in vegetated land surfaces and to estimate phenological transition dates. LSP, as an interdisciplinary subject among remote sensing, ecology, and biometeorology, has undergone rapid development over the past few decades. Recent advances in sensor technologies, as well as data fusion techniques, have enabled novel phenology retrieval algorithms that refine phenology details at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. As such, here we summarize the recent advances in LSP and the associated opportunities for science applications. We focus on the remaining challenges, promising techniques, and emerging topics that together we believe will truly form the very frontier of the global LSP research field. |
| WOS关键词 | NET ECOSYSTEM PRODUCTIVITY ; DIGITAL REPEAT PHOTOGRAPHY ; WATER-USE EFFICIENCY ; TIME-SERIES DATA ; VEGETATION PHENOLOGY ; GRASS-POLLEN ; PLANT PHENOLOGY ; CLIMATE-CHANGE ; AIRBORNE POLLEN ; CARBON-DIOXIDE |
| 资助项目 | National Natural Science Foundation of China[42171305] ; National Natural Science Foundation of China[41971374] ; National Natural Science Foundation of China[42022060] ; Natural Science Foundation of Gansu Province, China[21JR7RA499] ; Fundamental Research Funds for the Central Universities[lzujbky-2021-ct11] ; Director Fund of the International Research Center of Big Data for Sustainable Development Goals[CBAS2022DF006] ; Open Fund of Key laboratory of Geographic Information Science (Ministry of Education), East China Normal University[KLGIS2022A02] ; Open Fund of State Key Laboratory of Remote Sensing Science[OFSLRSS202229] ; University of Technology Sydney Chancellor's Postdoctoral Research Fellowship ; University of Technology Sydney Faculty of Science Seed Funding (Round 2 in 2021) |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000859769500001 |
| 出版者 | WILEY |
| 资助机构 | National Natural Science Foundation of China ; Natural Science Foundation of Gansu Province, China ; Fundamental Research Funds for the Central Universities ; Director Fund of the International Research Center of Big Data for Sustainable Development Goals ; Open Fund of Key laboratory of Geographic Information Science (Ministry of Education), East China Normal University ; Open Fund of State Key Laboratory of Remote Sensing Science ; University of Technology Sydney Chancellor's Postdoctoral Research Fellowship ; University of Technology Sydney Faculty of Science Seed Funding (Round 2 in 2021) |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185356]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Ma, Xuanlong |
| 作者单位 | 1.Natl Univ Singapore, Dept Geog, Singapore, Singapore 2.Swiss Fed Inst Technol, Dept Environm Syst Sci, Zurich, Switzerland 3.South Dakota State Univ, Geospatial Sci Ctr Excellence GSCE, Brookings, SD 57007 USA 4.Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou 730000, Gansu, Peoples R China 5.Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong, Peoples R China 6.Univ Technol Sydney, Fac Sci, Sch Life Sci, Sydney, NSW, Australia 7.Hohai Univ, Coll Hydrol & Water Resources, Nanjing, Peoples R China 8.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modelling, Beijing, Peoples R China 9.Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland |
| 推荐引用方式 GB/T 7714 | Ma, Xuanlong,Zhu, Xiaolin,Xie, Qiaoyun,et al. Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications[J]. GLOBAL CHANGE BIOLOGY,2022:19. |
| APA | Ma, Xuanlong.,Zhu, Xiaolin.,Xie, Qiaoyun.,Jin, Jiaxin.,Zhou, Yuke.,...&Zhao, Yuhe.(2022).Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications.GLOBAL CHANGE BIOLOGY,19. |
| MLA | Ma, Xuanlong,et al."Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications".GLOBAL CHANGE BIOLOGY (2022):19. |
入库方式： OAI收割
来源：地理科学与资源研究所
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