Dynamics and Drivers of Vegetation Phenology in Three-River Headwaters Region Based on the Google Earth Engine

doi:10.3390/rs13132528

	Dynamics and Drivers of Vegetation Phenology in Three-River Headwaters Region Based on the Google Earth Engine
	Wang, Jiyan 4; Sun, Huaizhang 4; Xiong, Junnan 4,5; He, Dong 1,2; Cheng, Weiming 5; Ye, Chongchong 4; Yong, Zhiwei 4; Huang, Xianglin 3
刊名	REMOTE SENSING
	2021-07-01
卷号	13 期号:13 页码:17
关键词	plant phenology spatiotemporal patterns structural equation model Google Earth Engine Three-River Headwaters region
DOI	10.3390/rs13132528
通讯作者	Xiong, Junnan(Xiongjn@swpu.edu.cn)
英文摘要	Phenology shifts over time are known as the canary in the mine when studying the response of terrestrial ecosystems to climate change. Plant phenology is a key factor controlling the productivity of terrestrial vegetation under climate change. Over the past several decades, the vegetation in the three-river headwaters region (TRHR) has been reported to have changed greatly owing to the warming climate and human activities. However, uncertainties related to the potential mechanism and influence of climatic and soil factors on the plant phenology of the TRHR are poorly understood. In this study, we used harmonic analysis of time series and the relative and absolute change rate on Google Earth Engine to calculate the start (SOS), end (EOS), and length (LOS) of the growing season based on MOD09A1 datasets; the results were verified by the observational data from phenological stations. Then, the spatiotemporal patterns of plant phenology for different types of terrain and basins were explored. Finally, the potential mechanism involved in the influence of climatic and soil factors on the phenology of plants in the TRHR were explored based on the structural equation model and Pearson's correlation coefficients. The results show the remotely sensed monitoring data of SOS (R-2 = 0.84, p < 0.01), EOS (R-2 = 0.72, p < 0.01), and LOS (R-2 = 0.86, p < 0.01) were very similar to the observational data from phenological stations. The SOS and LOS of plants possessed significant trends toward becoming advanced (Slope < 0) and extended (Slope > 0), respectively, from 2001 to 2018. The SOS was the earliest and the LOS was the longest in the Lancang River Basin, while the EOS was the latest in the Yangtze River Basin owing to the impact of climate change and soil factors. Meanwhile, the spatial patterns of SOS, EOS, and LOS have strong spatial heterogeneity at different elevations, slopes, and aspects. In addition, the results show that the drivers of plant phenology have basin-wide and stage differences. Specifically, the influence of soil factors on plant phenology in the Yangtze River Basin was greater than that of climatic factors, but climatic factors were key functional indicators of LOS in the Yellow and Lancang river basins, which directly or indirectly affect plant LOS through soil factors. This study will be helpful for understanding the relationship between the plant phenology of the alpine wetland ecosystem and climate change and improving the level of environmental management.
资助项目	National Natural Science Foundation of China[41701428] ; Key R&D project of Sichuan Science and Technology Department[2021YFQ0042] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA20030302] ; Science and Technology Project of Xizang Autonomous Region[XZ201901-GA-07] ; National Key R&D Program of China[2020YFD1100701]
WOS关键词	NET PRIMARY PRODUCTION ; LEAF-AREA INDEX ; CLIMATE-CHANGE ; TIBETAN PLATEAU ; TEMPERATURE SENSITIVITY ; ECOSYSTEM PRODUCTIVITY ; NDVI ; RESPONSES ; FOREST ; CHINA
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	MDPI
WOS记录号	WOS:000671175700001
资助机构	National Natural Science Foundation of China ; Key R&D project of Sichuan Science and Technology Department ; Strategic Priority Research Program of Chinese Academy of Sciences ; Science and Technology Project of Xizang Autonomous Region ; National Key R&D Program of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/163845]
专题	中国科学院地理科学与资源研究所
通讯作者	Xiong, Junnan
作者单位	1.Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Peoples R China 2.Nanjing Univ, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210023, Peoples R China 3.Hohai Univ, Sch Earth Sci & Engn, Nanjing 211106, Peoples R China 4.Southwest Petr Univ, Sch Civil Engn & Geomat, Chengdu 610500, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Wang, Jiyan,Sun, Huaizhang,Xiong, Junnan,et al. Dynamics and Drivers of Vegetation Phenology in Three-River Headwaters Region Based on the Google Earth Engine[J]. REMOTE SENSING,2021,13(13):17.
APA	Wang, Jiyan.,Sun, Huaizhang.,Xiong, Junnan.,He, Dong.,Cheng, Weiming.,...&Huang, Xianglin.(2021).Dynamics and Drivers of Vegetation Phenology in Three-River Headwaters Region Based on the Google Earth Engine.REMOTE SENSING,13(13),17.
MLA	Wang, Jiyan,et al."Dynamics and Drivers of Vegetation Phenology in Three-River Headwaters Region Based on the Google Earth Engine".REMOTE SENSING 13.13(2021):17.