Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data

doi:10.3390/rs15143641

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	Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data
	Dong, Xiujuan 2; Zhou, Yuke 3; Liang, Juanzhu 2; Zou, Dan 1; Wu, Jiapei 3; Wang, Jiaojiao 4
刊名	REMOTE SENSING
	2023-07-01
卷号	15 期号:14 页码:17
关键词	climate change meteorological drought vegetation dynamics SIF NDVI Yangtze River Basin
DOI	10.3390/rs15143641
通讯作者	Zhou, Yuke(zhouyk@igsnrr.ac.cn)
英文摘要	Global climate change and human activities have increased the frequency and severity of droughts. This has become a critical factor affecting vegetation growth and diversity, resulting in detrimental effects on agricultural production, ecosystem stability, and socioeconomic development. Therefore, assessing the response of vegetation dynamics to drought can offer valuable insights into the physiological mechanisms of terrestrial ecosystems. Here, we applied long-term datasets (2001-2020) of solar-induced chlorophyll fluorescence (SIF) and normalized difference vegetation index (NDVI) to unveil vegetation dynamics and their relationship to meteorological drought (SPEI) across different vegetation types in the Yangtze River Basin (YRB). Linear correlation analysis was conducted to determine the maximum association of SPEI with SIF and NDVI; we then compared their responses to meteorological drought. The improved partial wavelet coherence (PWC) method was utilized to quantitatively assess the influences of large-scale climate patterns and solar activity on the relationship between vegetation and meteorological drought. The results show that: (1) Droughts were frequent in the YRB from 2001 to 2020, and the summer's dry and wet conditions exerted a notable influence on the annual climate. (2) SPEI exhibits a more significant correlation with SIF than with NDVI. (3) NDVI has a longer response time (3-6 months) to meteorological drought than SIF (1-4 months). Both SIF and NDVI respond faster in cropland and grassland but slower in evergreen broadleaf and mixed forests. (4) There exists a significant positive correlation between vegetation and meteorological drought during the 4-16 months period. The teleconnection factors of Pacific Decadal Oscillation (PDO), El Nino Southern Oscillation (ENSO), and sunspots are crucial drivers that affect the interaction between meteorological drought and vegetation, with sunspots having the most significant impact. Generally, our study indicates that drought is an essential environmental stressor that disrupts vegetation growth over the YRB. Additionally, SIF demonstrates great potential in monitoring vegetation response to drought. These findings will be meaningful for drought prevention and ecosystem conservation planning in the YRB.
资助项目	National Key Research and Development Program[2021xjkk0303] ; National Natural Science Foundation of China[72074209]
WOS关键词	CHLOROPHYLL FLUORESCENCE ; PRECIPITATION ; VARIABILITY ; INDEX ; TEMPERATURE ; EXTREMES
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:001039042800001
资助机构	National Key Research and Development Program ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53831]
专题	舆论大数据科学与技术应用联合实验室
通讯作者	Zhou, Yuke
作者单位	1.Longyan Univ, Sch Resource Engn, Longyan 364012, Peoples R China 2.Fuzhou Univ, Acad Digital China, Fuzhou 350002, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Dong, Xiujuan,Zhou, Yuke,Liang, Juanzhu,et al. Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data[J]. REMOTE SENSING,2023,15(14):17.
APA	Dong, Xiujuan,Zhou, Yuke,Liang, Juanzhu,Zou, Dan,Wu, Jiapei,&Wang, Jiaojiao.(2023).Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data.REMOTE SENSING,15(14),17.
MLA	Dong, Xiujuan,et al."Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data".REMOTE SENSING 15.14(2023):17.