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	Evaluating Parameter Adjustment in the MODIS Gross Primary Production Algorithm Based on Eddy Covariance Tower Measurements
	Chen J.
	2014
关键词	gross primary production MODIS parameter adjustment model structure light use efficiency eddy covariance leaf-area index net ecosystem productivity use efficiency model carbon-dioxide exchange energy-balance closure ensemble kalman filter primary production gpp douglas-fir forest terrestrial gross boreal forest
英文摘要	How well parameterization will improve gross primary production (GPP) estimation using the MODerate-resolution Imaging Spectroradiometer (MODIS) algorithm has been rarely investigated. We adjusted the parameters in the algorithm for 21 selected eddy-covariance flux towers which represented nine typical plant functional types (PFTs). We then compared these estimates of the MOD17A2 product, by the MODIS algorithm with default parameters in the Biome Property Look-Up Table, and by a two-leaf Farquhar model. The results indicate that optimizing the maximum light use efficiency ((max)) in the algorithm would improve GPP estimation, especially for deciduous vegetation, though it could not compensate the underestimation during summer caused by the one-leaf upscaling strategy. Adding the soil water factor to the algorithm would not significantly affect performance, but it could make the adjusted (max) more robust for sites with the same PFT and among different PFTs. Even with adjusted parameters, both one-leaf and two-leaf models would not capture seasonally photosynthetic dynamics, thereby we suggest that further improvement in GPP estimaiton is required by taking into consideration seasonal variations of the key parameters and variables.
出处	Remote Sensing
卷	6
期	4
页	3321-3348
收录类别	SCI
语种	英语
ISSN号	2072-4292
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/29951]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Chen J.. Evaluating Parameter Adjustment in the MODIS Gross Primary Production Algorithm Based on Eddy Covariance Tower Measurements. 2014.

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