吴朝阳

中国科学院地理科学与资源研究所

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  • 吴朝阳
  • 研究员

个人简况

男,1982年生,研究员,博导,陆地表层格局与模拟重点实验室副主任。2010年毕业于中国科学院遥感与数字地球研究所,获得博士学位。2010至2014年在加拿大多伦多大学地理系从事博士后研究工作。主要研究基于遥感数据的植被生化参数、净初级生产力遥感反演、地面通量数据和生态模型的融合等方面的研究。获得中国科学院院长奖、中国科学院卢嘉锡青年人才奖、中国科学院百篇优秀博士学位论文、中国科学院青年创新促进会优秀会员、科技部首届青年科技人才、科技部十三五规划空天领域专家组成员。主持自然基金委青年基金、面上基金、优秀青年基金以及科学院知识创新工程等项目。第一作者 (通讯) 发表 SCI 论文40余篇,主要包括 Global Ecology and Biogeography、Remote Sensing of Environment、Agricultural and Forest Meteorology、Journal of Geophysical Research 等遥感与生态学科。

研究领域:

全球变化遥感与生态系统碳循环

主要研究项目

(1)中国科学院前沿局重点部署项目,植被物候变化遥感探测机理,2016-2020, 250万;

(2)自然科学基金优秀青年基金,植被碳循环遥感,2016-2018,150万;

(3)自然科学基金面上基金,基于遥感与通量数据的植被生产力反演,2014-2017,80万;

(4)中国科学院知识创新青年人才项目,光谱特征光能利用率遥感反演,2011-2013,60万;

(5)自然科学基金青年基金,基于高光谱遥感数据的植被光能利用率反演,2011-2013, 19万

主要学术成就

(1)提出了基于红边反射波段的叶绿素含量反演算法

植被叶绿素是研究植被生长状况的主要指标,如何提取有效的波段并给予明确物理解释仍然是制约高光谱应用的问题之一。通过PROSAIL 模拟叶片和冠层反射率在各波段受生化分组的影响,发现常用波段800 nm 和670 nm 处的反射率会随叶绿素的增加饱和,因此建立了红边波段750 nm 和705 nm 的植被指数,提高了叶绿素的反演精度,该成果发表于Agricultural and Forest Meteorology,是该期刊年度最多引用文章(Scupos,174)。

(2)提出秋天的物候变化是碳吸收年际变化的主要因素

研究表明春天的温度升高会增加年碳汇,但是却忽略了伴随着秋天温度的升高又会延长生态系统呼吸,进而抵消掉由于春天增温的影响,因此仅靠春天的温度无法研究碳吸收的年际变化。通过全球站点数据,发现秋天生长季的结束和净碳吸收之间的间隔才是碳汇年际变化的最主要因素。这一结果表明:(1)秋天的物候变化是NEP年际变化的主要因素,(2)生态系统呼吸比光合作用对NEP年际变化更重要。这些观点得到了全球变化研究领域专家的认可,文章发表于生态学杂志Global Ecology and Biogeography。

代表性学术论文

(1)Chaoyang Wu, Dailiang Peng, Kamel Soudani, Christopher M. Gough, M. Altaf Arain, Gil Bohrer, Shiguang Xu, Bin Fang, Quansheng Ge. 2017. Land surface phenology derived from normalized difference vegetation index (NDVI) at global FLUXNET sites. Agricultural and Forest Meteorology, 233, 171-182.

(2)Chaoyang Wu, Xuehui Hou, Dailiang Peng, Alemu Gonsamo, Shiguang Xu. 2016. Land surface phenology of China's temperate ecosystems over 1999-2013: Spatial-temporal patterns, interaction effects, covariation with climate and implications for productivity. Agricultural and Forest Meteorology, 216, 177-187.

(3)Chaoyang Wu, Alemu Gonsamo, Christopher M. Gough, Jing M. Chen, Shiguang Xu. 2014. Modeling growing season phenology in North American forests using seasonal mean vegetation indices from MODIS. Remote Sensing of Environment, 147, 79–88.

(4)Chaoyang Wu, Jing M. Chen, T. Andrew Black, David T. Price, Werner A. Kurz, Ankur R. Desai, Alemu Gonsamo, Rachhpal S. Jassal, Christopher M. Gough, Gil Bohrer, Danilo Dragoni, Mathias Herbst, Bert Gielen, Frank Berninger, Timo Vesala, Ivan Mammarella, Kim Pilegaard, Peter D. Blanken. 2013. Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn. Global Ecology and Biogeography, 22, 994-1006.

(5)Chaoyang Wu, Jing M. Chen, Ankur R. Desai, Peter M. Lafleur, Shashi B. Verma. 2013. Positive impacts of precipitation intensity on monthly CO2 fluxes in North America. Global and Planetary Change, 100, 204–214.

(6)Chaoyang Wu, Jing M. Chen, Alemu Gonsamo, David T. Price, T. Andrew Black, Werner A. Kurz. 2012. Interannual variability of net carbon exchange is related to the lag between the end-dates of net carbon uptake and photosynthesis: Evidence from long records at two contrasting forest stands. Agricultural and Forest Meteorology, 164, 29-38.

(7)Chaoyang Wu, Alemu Gonsamo, Jing M. Chen, Werner A. Kurz, David T. Price, Peter M. Lafleur, Rachhpal S. Jassal, Danilo Dragoni, Gil Bohrer, Christopher M. Gough, et al., 2012. Interannual and spatial impacts of phenological transitions, growing season length, and spring and autumn temperatures on carbon sequestration, A North America flux data synthesis. Global and Planetary Change, 164, 29-38.

(8)Chaoyang Wu, Jing M. Chen, Ankur R. Desai, David Y. Hollinger, M. Altaf Arain, Hank A. Margolis, Christopher M. Gough, Ralf M. Staebler. 2012. Remote sensing of canopy light use efficiency in temperate and boreal forests of North America using MODIS imagery. Remote Sensing of Environment, 118, 60–72.

(9)Chaoyang Wu, Jing M. Chen, Ni Huang. 2011. Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation, Evaluation and calibration. Remote Sensing of Environment, 115, 3424-3435.

(10)Chaoyang Wu, J. William Munger, Zheng Niu, Da Kuang. 2010. Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest. Remote Sensing of Environment, 114, 2925-2939.

(11)Chaoyang Wu, Zheng Niu, Quan Tang, Wenjiang Huang, Benoit Rivard, Jilu Feng. 2009. Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices. Agricultural and Forest Meteorology, 149, 1015-1021.

(12)Chaoyang Wu, Zheng Niu, Quan Tang, Wenjiang Huang. 2008. Estimating chlorophyll content from hyperspectral vegetation indices, Modeling and validation. Agricultural and Forest Meteorology, 148, 1230-1241.