气候变化领域集成服务门户(CCPortal): Large discrepancies of global greening: Indication of multi-source remote sensing data

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DOI	10.1016/j.gecco.2022.e02016
	Large discrepancies of global greening: Indication of multi-source remote sensing data
	Wang, Zhaoqi; Wang, Hong; Wang, Tongfang; Wang, Lina; Liu, Xiang; Zheng, Kai; Huang, Xiaotao
通讯作者	Wang, ZQ (通讯作者)，Qinghai Univ, State Key Lab Plateau Ecol & Agr, Xining 810016, Qinghai, Peoples R China. ; Huang, XT (通讯作者)，Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Restorat Ecol Cold Reg Lab Qinghai, Xining 810008, Qinghai, Peoples R China.
发表日期	2022
EISSN	2351-9894
卷号	34
英文摘要	Global warming has a great impact on the activities of terrestrial vegetation. A consensus has been reached that the global vegetation is greening from the 1980-2010s. However, the trends of global vegetation are highly uncertain after 2000. Therefore, we used multi-source remote sensing vegetation index (VI), climate data, and Mann-Kendall trend analysis to explore the global vegetation trend and its uncertainty from 2001 to 2016. The effects of climate on the changes in vegetation were also investigated. We found that GIMMS-based VIs exhibited decreasing trends. By contrast, MODIS-based VIs and GLOBMAP LAI tended to increase. Evergreen broad-leaf forest contributed the most to the uncertainty of global vegetation trends, and the uncertainty of December-January-February and September-October-November was higher than that in the other seasons. The correlation of forest VI and temperature was the highest in March-April-May, whereas the correlation of non-forest VI and precipitation was higher than that of the forest. The anomalies of GIMMS-based VIs and mean annual precipitation were more consistent in the evergreen broad-leaf forest, woody savannas, mixed forest, evergreen needle-leaf forest, and deciduous needle-leaf forest than those in biomes under the impact of 2015-2016 El Nino.
关键词	ECOLOGICAL RESPONSES VEGETATION TREND CHINA GIMMS MODIS NDVI SATELLITE DRIVERS SURFACE
英文关键词	Inter-comparison; Uncertainty; Vegetation greening; Global warming
语种	英语
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
WOS类目	Biodiversity Conservation ; Ecology
WOS记录号	WOS:000748713200007
来源期刊	GLOBAL ECOLOGY AND CONSERVATION
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254260
作者单位	[Wang, Zhaoqi; Wang, Hong; Wang, Tongfang; Wang, Lina; Liu, Xiang; Zheng, Kai] Qinghai Univ, State Key Lab Plateau Ecol & Agr, Xining 810016, Qinghai, Peoples R China; [Huang, Xiaotao] Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Restorat Ecol Cold Reg Lab Qinghai, Xining 810008, Qinghai, Peoples R China; [Huang, Xiaotao] Chinese Acad Sci, Key Lab Adaptat & Evolut Plateau Biota, Xining 810008, Qinghai, Peoples R China
推荐引用方式 GB/T 7714	Wang, Zhaoqi,Wang, Hong,Wang, Tongfang,et al. Large discrepancies of global greening: Indication of multi-source remote sensing data[J]. 中国科学院西北生态环境资源研究院,2022,34.
APA	Wang, Zhaoqi.,Wang, Hong.,Wang, Tongfang.,Wang, Lina.,Liu, Xiang.,...&Huang, Xiaotao.(2022).Large discrepancies of global greening: Indication of multi-source remote sensing data.GLOBAL ECOLOGY AND CONSERVATION,34.
MLA	Wang, Zhaoqi,et al."Large discrepancies of global greening: Indication of multi-source remote sensing data".GLOBAL ECOLOGY AND CONSERVATION 34(2022).