Arid
DOI10.1016/j.rse.2010.05.001
Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling
Wang, Hesong1,2; Jia, Gensuo1; Fu, Congbin1; Feng, Jinming1; Zhao, Tianbao1; Ma, Zhuguo1
通讯作者Jia, Gensuo
来源期刊REMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
EISSN1879-0704
出版年2010
卷号114期号:10页码:2248-2258
英文摘要

Remote sensing models based on light use efficiency (LUE). provide promising tools for monitoring spatial and temporal variation of gross primary production (GPP) at regional scale. In most of current LUE-based models, maximal LUE (epsilon(max)) heavily relies on land cover types and is considered as a constant, rather than a variable for a certain vegetation type or even entire eco-region. However, species composition and plant functional types are often highly heterogeneous in a given land cover class; therefore, spatial heterogeneity of epsilon(max) must be fully considered in GPP modeling, so that a single cover type does not equate to a single epsilon(max) value. A spatial dataset of epsilon(max) accurately represents the spatial heterogeneity of maximal light use would be of significant beneficial to regional GPP models. Here, we developed a spatial dataset of epsilon(max) by integrating eddy covariance flux measurements from 14 field sites in a network of coordinated observation across northern China and satellite derived indices such as enhanced vegetation index (EVI) and visible albedo to simulate regional distribution of GPP. This dynamic modeling method recognizes the spatial heterogeneity of epsilon(max) and reduces the uncertainties in mixed pixels. Further, we simulated GPP with the spatial dataset of epsilon(max) generated above. Both epsilon(max) and growing season GPP show complex patterns over northern China that reflect influences of humidity, green vegetation fractions, and land use intensity. "Green spots" such as oasis meadow and alpine forests in dryland and "brown spots" such as build-up and heavily degraded vegetation in the east are clearly captured by the simulation. The correlation between simulated GPP and EC measured GPP indicate that the simulated GPP from this new approach is well matched with flux-measured GPP. Those results have demonstrated the importance of considering epsilon(max) as both a spatially and temporally variable values in GPP rnodeling. (C) 2010 Elsevier Inc. All rights reserved.


英文关键词Maximal light use efficiency (epsilon(max)) Satellite Flux site Gross primary production (GPP) Modeling Northern China
类型Article
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000281187400012
WOS关键词PHOTOCHEMICAL REFLECTANCE INDEX ; NET PRIMARY PRODUCTION ; DECIDUOUS FOREST ; GENERALIZED-MODEL ; VEGETATION INDEX ; EDDY COVARIANCE ; CLIMATE DATA ; MODIS ; CARBON ; WATER
WOS类目Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构中国科学院大气物理研究所
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/166246
作者单位1.Chinese Acad Sci, Inst Atmospher Phys, RCE TEA, Beijing 100029, Peoples R China;
2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Wang, Hesong,Jia, Gensuo,Fu, Congbin,et al. Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling[J]. 中国科学院大气物理研究所,2010,114(10):2248-2258.
APA Wang, Hesong,Jia, Gensuo,Fu, Congbin,Feng, Jinming,Zhao, Tianbao,&Ma, Zhuguo.(2010).Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling.REMOTE SENSING OF ENVIRONMENT,114(10),2248-2258.
MLA Wang, Hesong,et al."Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling".REMOTE SENSING OF ENVIRONMENT 114.10(2010):2248-2258.
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