气候变化领域集成服务门户(CCPortal): Evolution of NDVI secular trends and responses to climate change: A perspective from nonlinearity and nonstationarity characteristics

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DOI	10.1016/j.rse.2020.112247
	Evolution of NDVI secular trends and responses to climate change: A perspective from nonlinearity and nonstationarity characteristics
	Yang L.; Guan Q.; Lin J.; Tian J.; Tan Z.; Li H.
发表日期	2021
ISSN	00344257
卷号	254
英文摘要	The evolution of vegetation patterns plays a crucial role in monitoring ecosystem dynamics in face of global warming. Notably, the time-series vegetation trends vary unevenly over time. However, conventional linear methods based on the stationarity assumption, cannot detect the implicit characteristics of nonlinear and gradual vegetation changes. Meanwhile, characterizing the inherent features of nonlinearity and nonstationarity of climatic drivers remains a challenge. This study applied multidimensional ensemble empirical mode decomposition (MEEMD) and Breaks For Additive Seasonal and Trend (BFAST) algorithm to diagnose spatiotemporal evolution and abrupt change in vegetation secular trends based on normalized difference vegetation index (NDVI) data of the Hexi Corridor during 1982–2015. Geographically and temporally weighted regression (GTWR) was used to address the spatiotemporal nonlinearity and nonstationarity of climatic drivers. A wide range of browning trends gradually evolved into greening trends from 1982 to 2015. Compared with ordinary least squares regression, MEEMD could adaptively decompose short-term trends of noise and seasonality and elucidate the entire evolutionary process of NDVI trends. Browning trends prevailed before abrupt changes, and greening trends widely expanded after 2006 due to drought before and intense precipitation during this year. GTWR addressed the nonequilibrium effect of the time dimension on climate drivers, and the R-squared achieved 0.86. The response processes between vegetation and climatic drivers showed significant spatiotemporal nonstationarity and aggregation characteristics based on three-dimensional visualization. In addition to the drivers of temperature, precipitation, solar radiation, and potential evapotranspiration, the drying effect and mechanical stimuli of wind speed on vegetation could not be underestimated. This study provides a novel framework to solve nonlinearity and nonstationarity problems related to vegetation trends and their response mechanisms and promotes the application of remote sensing to solve practical problems. © 2020 Elsevier Inc.
英文关键词	Climate drivers; Geographically and temporally weighted regression; Greening and browning trends; Multidimensional ensemble empirical mode decomposition
语种	英语
scopus关键词	Global warming; Remote sensing; Three dimensional computer graphics; Wind; Ensemble empirical mode decomposition; Intense precipitation; Non-equilibrium effects; Normalized difference vegetation index datum; Ordinary least squares regressions; Potential evapotranspiration; Spatiotemporal evolution; Three dimensional visualization; Vegetation; climate change; climate effect; decomposition analysis; ecosystem dynamics; empirical analysis; evapotranspiration; global warming; monitoring system; NDVI; nonlinearity; trend analysis; vegetation dynamics; wind velocity; China; Gansu; Hexi Corridor
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179002
作者单位	Key Laboratory of Western China's Environmental Systems (Ministry of Education) &Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, China
推荐引用方式 GB/T 7714	Yang L.,Guan Q.,Lin J.,et al. Evolution of NDVI secular trends and responses to climate change: A perspective from nonlinearity and nonstationarity characteristics[J],2021,254.
APA	Yang L.,Guan Q.,Lin J.,Tian J.,Tan Z.,&Li H..(2021).Evolution of NDVI secular trends and responses to climate change: A perspective from nonlinearity and nonstationarity characteristics.Remote Sensing of Environment,254.
MLA	Yang L.,et al."Evolution of NDVI secular trends and responses to climate change: A perspective from nonlinearity and nonstationarity characteristics".Remote Sensing of Environment 254(2021).