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Proceedings Paper

Analysis of light use efficiency and gross primary productivity based on remote sensing data over a phragmites-dominated wetland in Zhangye, China
Author(s): Guoqing Jiang; Rui Sun; Lei Zhang; Shaomin Liu; Ziwei Xu; Chen Qiao
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Paper Abstract

Light use efficiency (LUE) is a critical parameter for estimating carbon exchange in many ecosystem models, especially those models based on remote sensing algorithms. Estimation and monitoring of LUE and gross primary productivity (GPP) over wetland is very important for the global carbon cycle research and modelling, since the wetland plays a vital role in the ecosystem balance. In this paper, carbon flux data observed with an eddy covariance tower over a reedsdominated wetland in Zhangye, northwest of China, was used to calculate LUE. Through the postprocessing of carbon flux data and estimation of ecosystem respiration, daily GPP was calculated firstly. Combining with fraction of absorbed photosynthetically active radiation (FPAR) inversed from HJ-1 satellite, LUE was determined. The maximum value of LUE was 1.03 g C·MJ-1 occurred in summer. Furthermore, a regional vegetation productivity model based on meteorological data and remote sensing data was used to estimate the wetland GPP. The results show that the modeled GPP results were consistent with in situ data.

Paper Details

Date Published: 8 November 2014
PDF: 8 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 926033 (8 November 2014); doi: 10.1117/12.2068840
Show Author Affiliations
Guoqing Jiang, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Beijing Key Lab. for Remote Sensing of Environment and Digital Cities (China)
Rui Sun, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Beijing Key Lab. for Remote Sensing of Environment and Digital Cities (China)
Lei Zhang, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Beijing Key Lab. for Remote Sensing of Environment and Digital Cities (China)
Shaomin Liu, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Ziwei Xu, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Chen Qiao, State Key Lab. of Remote Sensing Science (China)
Beijing Normal Univ. (China)
Beijing Key Lab. for Remote Sensing of Environment and Digital Cities (China)


Published in SPIE Proceedings Vol. 9260:
Land Surface Remote Sensing II
Thomas J. Jackson; Jing Ming Chen; Peng Gong; Shunlin Liang, Editor(s)

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