干旱区生态环境知识资源中心(Arid): Quantifying the Spatio-Temporal Variations and Impacts of Factors on Vegetation Water Use Efficiency Using STL Decomposition and Geodetector Method

Arid

DOI	10.3390/rs14235926
	Quantifying the Spatio-Temporal Variations and Impacts of Factors on Vegetation Water Use Efficiency Using STL Decomposition and Geodetector Method
	Wang, Guigang; Li, Xuemei; Zhao, Kaixin; Li, Yikun; Sun, Xuwei
通讯作者	Wang, GG
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2022
卷号	14 期号:23
英文摘要	Water use efficiency of vegetation (WUE), the ratio of carbon gain to water loss, is a valid indicator to describe the photosynthetic carbon-water coupling relationship. Understanding how and why WUE changes are essential for regional ecological conservation. However, the impacts of various factors and their interactions on the spatial variation of WUE remain uncertain in the arid land of Northwest China. Here, we selected the Qilian Mountains (QM) and Hexi Corridor (HC) as the study areas. Supported by the Google Earth Engine, we explored the spatio-temporal variations of WUE in QM and HC for 2002-2021 using STL decomposition (a seasonal-trend decomposition procedure), trend analysis, and the Hurst index. Then, the Geodetector method was applied to quantify impacts of geographical and eco-meteorological factors on the spatial variation of WUE. The WUE in HC was higher than that in QM. Interestingly, the opposite longitude zonality characteristics are shown in the QM and HC. In QM, the WUE showed an upward trend with longitude increasing, while a downward trend with longitude increasing in the oases of HC. The WUE of cropland was the highest (1.15 +/- 0.35 gC kg(-1) H2O), and that of alpine vegetation was the lowest (0.2 +/- 0.15 gC kg(-1) H2O). WUE showed a decreasing trend across the study area, almost certainly due to a drop from May to July during 2002-2021. The air temperature is the dominant factor influencing the spatial variation of WUE. In addition, the interaction of any two factors is greater than the independent influence of either factor alone. The Geodetector method proved to be effective for quantifying the impact of complex multi-factors on the spatial variation of WUE. This study provides a new technical scheme to analyze the spatio-temporal pattern and quantify the impact of multi-factors on the spatial variation of WUE. These findings aid in understanding underlying mechanisms of WUE variation and thereby will be beneficial for clarifying the response of vegetation to climate change.
英文关键词	WUE MODIS STL decomposition Geodetector Google Earth Engine vegetation dynamics
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000896627100001
WOS关键词	CLIMATE ; NDVI ; CARBON ; PRODUCTIVITY ; TEMPERATURE ; VARIABILITY ; ECOSYSTEMS ; RESPONSES ; DYNAMICS ; REGION
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394246
推荐引用方式 GB/T 7714	Wang, Guigang,Li, Xuemei,Zhao, Kaixin,et al. Quantifying the Spatio-Temporal Variations and Impacts of Factors on Vegetation Water Use Efficiency Using STL Decomposition and Geodetector Method[J],2022,14(23).
APA	Wang, Guigang,Li, Xuemei,Zhao, Kaixin,Li, Yikun,&Sun, Xuwei.(2022).Quantifying the Spatio-Temporal Variations and Impacts of Factors on Vegetation Water Use Efficiency Using STL Decomposition and Geodetector Method.REMOTE SENSING,14(23).
MLA	Wang, Guigang,et al."Quantifying the Spatio-Temporal Variations and Impacts of Factors on Vegetation Water Use Efficiency Using STL Decomposition and Geodetector Method".REMOTE SENSING 14.23(2022).