A Comparison of Satellite-Derived Vegetation Indices for Approximating Gross Primary Productivity of Grasslands

doi:10.2111/REM-D-13-00059.1

	A Comparison of Satellite-Derived Vegetation Indices for Approximating Gross Primary Productivity of Grasslands
	Zhou, Yu 1; Zhang, Li ; Xiao, Jingfeng 2; Chen, Shiping3 ; Kato, Tomomichi 4; Zhou, Guangsheng 5
	2014
发表期刊	RANGELAND ECOLOGY & MANAGEMENT
ISSN	1550-7424
卷号	67 期号:1 页码:9-18
摘要	Gross primary productivity (GPP) is a key component of ecosystem carbon fluxes and the carbon balance between the biosphere and the atmosphere. Accurate estimation of GPP is essential for quantifying plant production and carbon balance for grasslands. Satellite-derived vegetation indices (VIs) are often used to approximate GPP. The widely used VIs include atmospherically resistant vegetation index, enhanced vegetation index (EVI), normalized difference greenness index, normalized difference vegetation index, reduced simple ratio, ratio vegetation index, and soil-adjusted vegetation index (SAVI). The evaluation of the performance of these VIs for approximating GPP, however, has been limited to one or two VIs and/or using GPP observations from one or two sites. In this study, we examined the relationships between the nine VIs derived from the moderate resolution imaging spectroradiometer (MODIS) and tower-based GPP at five eddy covariance flux sites over the grasslands of northern China. Our results showed that the nine VIs were generally good predictors of GPP for grasslands of northern China. Overall, EVI was the best predictor. The correlation between EVI and GPP also declined from the south to the north, indicating that EVI and GPP exhibited closer relationships in more southerly sites with higher vegetation cover. We also examined the seasonal influence on the correlation between VIs and GPP. SAVI exhibited the best correlation with GPP in spring when the grassland canopy was sparse, while EVI exhibited the best correlation with GPP in summer when the grassland cover was dense. Our results also showed that VIs could capture variations in observed GPP better in drought period than in nondrought period for an alpine meadow site because of the suppression of vegetation growth by drought.
关键词	China grasslands gross primary productivity MODIS vegetation indices
学科领域	Ecology ; Environmental Sciences
DOI	10.2111/REM-D-13-00059.1
收录类别	SCI
语种	英语
WOS关键词	CARBON-DIOXIDE ; INNER-MONGOLIA ; CO2 FLUX ; LAND-USE ; ECOSYSTEM ; TEMPERATE ; EXCHANGE ; MODEL ; PRECIPITATION ; ATMOSPHERE
WOS研究方向	Environmental Sciences & Ecology
WOS记录号	WOS:000330495700002
出版者	SOC RANGE MANAGEMENT
文献子类	Article
出版地	LAKEWOOD
EISSN	1551-5028
资助机构	Director Innovation Foundation of CEODE, CAS [Y2ZZ19101B] ; National Natural Science Foundation of China [41271372] ; National Science Foundation through MacroSystems Biology [1065777]
作者邮箱	lizhang@ceode.ac.cn
引用统计	被引频次：25[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/27032
专题	植被与环境变化国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Univ New Hampshire, Inst Study Earth Oceans & Space, Earth Syst Res Ctr, Durham, NH 03824 USA 4.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 5.CEA CNRS UVSQ, Lab Sci Climat & Environm, Paris, France 6.Chinese Acad Meteorol Sci, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Yu,Zhang, Li,Xiao, Jingfeng,et al. A Comparison of Satellite-Derived Vegetation Indices for Approximating Gross Primary Productivity of Grasslands[J]. RANGELAND ECOLOGY & MANAGEMENT,2014,67(1):9-18.
APA	Zhou, Yu,Zhang, Li,Xiao, Jingfeng,Chen, Shiping,Kato, Tomomichi,&Zhou, Guangsheng.(2014).A Comparison of Satellite-Derived Vegetation Indices for Approximating Gross Primary Productivity of Grasslands.RANGELAND ECOLOGY & MANAGEMENT,67(1),9-18.
MLA	Zhou, Yu,et al."A Comparison of Satellite-Derived Vegetation Indices for Approximating Gross Primary Productivity of Grasslands".RANGELAND ECOLOGY & MANAGEMENT 67.1(2014):9-18.

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