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A Revised Two-Leaf Light Use Efficiency Model for Improving Gross Primary Production Estimation at a Tropical Evergreen Broadleaved Forest Site

文献类型： 会议论文

第一作者： Lingxiao Huang

作者： Lingxiao Huang 1 ; Meng Liu 2 ; Yazhen Jiang 1 ; Ronglin Tang 1 ;

作者机构： 1.State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China|University of Chinese Academy of Sciences, Beijing, China

2.Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China

关键词： Climate change;Systematics;Clouds;Estimation;Geoscience and remote sensing;Production;Forestry

会议名称： IEEE International Geoscience and Remote Sensing Symposium

主办单位：

页码： 7153-7155

摘要： Accurate quantification of terrestrial gross primary production (GPP) is essential for enhancing our in-depth understanding of the global carbon budget and climate change [1] [2] . The two-leaf light use efficiency (TL-LUE) model, considering more deeply the disparities of photosynthesis capacity between sunlit and shaded leaves, has been proven to be a more efficient and potent approach than the big-leaf light use efficiency (BL-LUE) model for global GPP simulations [3] . However, the TL-LUE model is theoretically applicable for sunny days and fails to reflect the real configuration of the canopy under overcast and cloudy days, since the direct radiation could be shaded by clouds and thus all the leaves within the canopy are in reality shaded leaves (i.e., no sunlit leaves should exist). This mismatch between the theory and reality could definitely introduce a certain degree of systematic errors into the GPP simulations by the TL-LUE model. Here, we proposed a revised two-leaf light use efficiency (RTL-LUE) model for improving GPP estimation through better quantifying the sunlit and shaded leaf area index (LAI) under different sky conditions.

分类号： tp7-53

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