气候变化领域集成服务门户(CCPortal): NIRv and SIF better estimate phenology than NDVI and EVI: Effects of spring and autumn phenology on ecosystem production of planted forests

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DOI	10.1016/j.agrformet.2022.108819
	NIRv and SIF better estimate phenology than NDVI and EVI: Effects of spring and autumn phenology on ecosystem production of planted forests
	Zhang, Jingru; Xiao, Jingfeng; Tong, Xiaojuan; Zhang, Jinsong; Meng, Ping; Li, Jun; Liu, Peirong; Yu, Peiyang
发表日期	2022
ISSN	0168-1923
EISSN	1873-2240
卷号	315
英文摘要	Phenology plays an important role in affecting carbon sequestration in terrestrial ecosystems in the context of climate change. Remote sensing techniques have been widely used to investigate land surface phenology and the effects of phenology on ecosystem production at regional and global scales. Recently, the near-infrared reflectance of vegetation (NIRv) and solar-induced chlorophyll fluorescence (SIF) have been shown to be more promising metrics of gross primary production (GPP) than the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). However, there is a lack of comparison in the performance of these techniques for deriving phenological metrics. In this study, we explored the consistency in phenological metrics derived from both remote sensing approaches (NDVI, EVI, NIRv, and SIF) and flux tower GPP at six plantations (two broadleaf forests (BF) and four coniferous forests (CF)) in eastern China over the period 2006-2020. The vegetation indices (NDVI, EVI, NIRv) were derived from MODIS data, and SIF was based on the global, OCO-2 based SIF product (GOSIF). We further evaluated the effects of spring and autumn phenology on GPP. The results showed that the flux tower GPP was effectively tracked by NDVI, EVI, NIRv, and SIF (P < 0.001). Meanwhile, the phenological metrics derived from EVI, NIRv, and SIF, including the start of growing season (SOS), the end of growing season (EOS), and the length of growing season (GSL), had significant relationships with those derived from GPP at the six plantations (P < 0.05). NIRv and SIF were more effective at estimating phenological information than NDVI and EVI. In addition, the root mean squared deviation (RMSD) values between the GPPand NIRv-retrieved phenological dates were less than those derived from NDVI, EVI, and SIF at the BF sites. However, the differences among RMSD values of NDVI, EVI, NIRv, and SIF were not significant at the CF sites. The linear regression analysis showed that the advance of SOSGPP (i.e., SOS derived from GPP) significantly increased GPP (R2=0.29, P < 0.05) over the period from March to April, and the delay of EOSGPP (i.e., EOS derived from GPP) remarkably enhanced GPP (R2=0.61, P < 0.001) over the period from September to October at the BF sites. The relationship of EOSGPP with GPP (R2=0.90, P < 0.05) over the period September-October was strong at the CF sites. In addition, the variations of annual GPP could be captured by GSLGPP x GPPmax, GSLNIRv x NIRvmax, and GSLSIF x SIFmax effectively across the BF and CF sites. These findings can help us understand the potential ability of NIRv and SIF in estimating phenological metrics and in revealing the effects of vegetation phenology on the carbon cycle.
英文关键词	Phenology; Plantation; Vegetation index; Solar-induced chlorophyll fluorescence; Gross primary production; OCO-2
语种	英语
WOS研究方向	Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000798576700004
来源期刊	AGRICULTURAL AND FOREST METEOROLOGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280944
作者单位	Beijing Forestry University; University System Of New Hampshire; University of New Hampshire; Chinese Academy of Forestry; Research Institute of Forestry, CAF; Chinese Academy of Sciences; Institute of Geographic Sciences & Natural Resources Research, CAS
推荐引用方式 GB/T 7714	Zhang, Jingru,Xiao, Jingfeng,Tong, Xiaojuan,et al. NIRv and SIF better estimate phenology than NDVI and EVI: Effects of spring and autumn phenology on ecosystem production of planted forests[J],2022,315.
APA	Zhang, Jingru.,Xiao, Jingfeng.,Tong, Xiaojuan.,Zhang, Jinsong.,Meng, Ping.,...&Yu, Peiyang.(2022).NIRv and SIF better estimate phenology than NDVI and EVI: Effects of spring and autumn phenology on ecosystem production of planted forests.AGRICULTURAL AND FOREST METEOROLOGY,315.
MLA	Zhang, Jingru,et al."NIRv and SIF better estimate phenology than NDVI and EVI: Effects of spring and autumn phenology on ecosystem production of planted forests".AGRICULTURAL AND FOREST METEOROLOGY 315(2022).