干旱区生态环境知识资源中心(Arid): Identifying Anomalous Regions of Vegetation Change From 2000 to 2020, China: Driving Forces, Probability, and Colocation Patterns

Arid

DOI	10.1109/JSTARS.2024.3441765
	Identifying Anomalous Regions of Vegetation Change From 2000 to 2020, China: Driving Forces, Probability, and Colocation Patterns
	Zhang, Xinyue; Peng, Li; Tan, Jing; Zhang, Huijuan; Yu, Huan
通讯作者	Peng, L
来源期刊	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN	1939-1404
EISSN	2151-1535
出版年	2024
卷号	17 页码:14337-14352
英文摘要	Differentiating between the effects of climate change and human activities on vegetation change is important in the context of vegetation restoration and management. In this study, we used the Theil-Sen slope and Mann-Kendall test to analyze the spatiotemporal changes in vegetation cover in China from 2000 to 2020, defining a series of anomalous regions. The probability of vegetation greening and browning under different climates and population pressures was evaluated using copula functions, and their spatial aggregation was studied through the colocation quotient. Geodetector was then used to analyze the influencing factors of vegetation change in these anomalous regions. Our findings have shown that the vegetation recovery rate in northern China has surpassed that of southern China. Precipitation and temperature across the entire region showed a positive feedback relationship with normalized difference vegetation index, indicating substantial spatial heterogeneity. Anomalous regions of vegetation change were predominantly concentrated in eastern China. The statistical probability of the copula function reflects that the synchronization probability of vegetation response to the external environment is higher. The sensitivity of temperature to vegetation is higher than that of precipitation and higher than that of population density. However, in the Tibetan Plateau and western arid zone, the feedback of population density has exceeded that of precipitation due to improvements in land management from population concentration. The findings have also shown that the vegetation dynamics are primarily influenced by soil water content, with the slope aspect having a minimal influence. Nonlinear interactions were observed among most of the influencing factors, with the interaction between soil water content and altitude being the strongest.
英文关键词	Climate change Human activity recognition Vegetation mapping Indexes Probability Statistical analysis Weather forecasting Environmental monitoring Normalized difference vegetation index Anomalous region climate change colocation patterns human activity normalized difference vegetation index (NDVI)
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:001303437700003
WOS关键词	ECOLOGICAL RESTORATION PROJECTS ; GRASSLAND VEGETATION ; PRECIPITATION ; TEMPERATURE ; NDVI ; DYNAMICS ; COPULA ; RESPONSES ; LIGHT
WOS类目	Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Engineering ; Physical Geography ; 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/2XILL650/404143
推荐引用方式 GB/T 7714	Zhang, Xinyue,Peng, Li,Tan, Jing,et al. Identifying Anomalous Regions of Vegetation Change From 2000 to 2020, China: Driving Forces, Probability, and Colocation Patterns[J],2024,17:14337-14352.
APA	Zhang, Xinyue,Peng, Li,Tan, Jing,Zhang, Huijuan,&Yu, Huan.(2024).Identifying Anomalous Regions of Vegetation Change From 2000 to 2020, China: Driving Forces, Probability, and Colocation Patterns.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,17,14337-14352.
MLA	Zhang, Xinyue,et al."Identifying Anomalous Regions of Vegetation Change From 2000 to 2020, China: Driving Forces, Probability, and Colocation Patterns".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 17(2024):14337-14352.