陈镜明

个人履历

教  育：

博士 1986年 英国里丁大学 气象学专业

学士 1982年 南京气象学院（现南京信息工程大学） 气象学

工  作：

1986 - 1988   中国科学院北京地理学院 ，研究员

1988 - 1989   中国科学院北京地理学院，高级研究员

1989 - 1991   英属哥伦比亚大学，博士后

1991 - 1993   英属哥伦比亚大学，研究助理

1993 - 1997   加拿大遥感中心，研究员

1994 - 2000   加拿大渥太华大学，客座教授

1996 - 2009   加拿大约克大学，客座教授

1997 - 2000   加拿大遥感中心，高级研究员

1999 至今    南京大学，客座教授

2000 - 2000   加拿大遥感中心，首席研究员

2000 至今    加拿大多伦多大学，教授

2007 至今    南京信息大学，客座教授

2007 - 2011   南京信息大学应用气象学院，副院长

2007 至今    南京大学国际地球系统科学研究所，学术委员会主任

2008 至今    加拿大麦克马斯特大学，客座教授

2010 - 2011   加拿大多伦多大学环境中心，教务助理

2012 - 2014   加拿大多伦多大学地理与规划系，副主席

2020 至今    福建师范大学地理科学学院，教授

个人简介

陈镜明，加拿大高级首席科学家(2003)，加拿大皇家科学院院士(2006)，多伦多大学地理与规划系终身教授，教育部长江学者“讲座教授”，国际地球系统科学研究所（ESSI）学术委员会主任，中国科学院海外评审专家。1982年获南京气象学院学士学位，1986年获英国里丁大学博士学位。现任Remote Sensing of Environment 主编、Journal of Geophyiscal Research-Biogeosciences和Canadian Journal of Remote Sensing副主编、 Agricultural and Forest Meteorology 编委、美国通量观测网络科学指导委员会委员、中国科技部全球变化重大科学研究计划专家组成员、国务院侨办海外专家咨询委员会委员。

陈镜明教授在定量遥感方面、地球环境和气候变化以及在理保护环境方面做出了如下突出贡献：发明了测量叶面积指数的光学仪器；发展了用于卫星图像处理的最先进的几何光学4-尺度模式；发展了高光谱5尺度模式，成为机载图像分析和解译卫星图像的重要工具；利用卫星资料、地面资料和模型，发展了地面碳循环监测系统。在加拿大森林碳汇方面的研究成果对制定加拿大国家气候变化研究计划及其他相关的政策产生了影响。

代表性论文

Chen, J. M., and J. Liu, 2020. Evolution of evapotranspiration models using thermal and shortwave remote sensing data. Remote Sensing of Environment, 237, 111594. (doi.org/10.1016/J.RSE.2019.111594)

Chen, J. M., J. Liu, and X. Luo, 2020. Modification of the Penman-Monteith ET model based on the principle of water and carbon cycle coupling. Transactions of Atmospheric Science (invited paper in Chinese) (in press)

Chou, S., Chen, B., Chen, J.M., Wang, M., Wang, S., Croft, H., and Shi, Q. 2020. Estimation of leaf photosynthetic capacity from the photochemical reflectance index and leaf pigments. Ecological Indicators, 110,105867. (doi.org/10.1016/J.ECOLIND.2019.105867)

Croft, H., Chen, J.M., Wang, R., Mo, G., Luo, S., Luo, X., He, L., Gonsamo, A., Arabian, J., Zhang, Y., Simic-Milas, A., Noland, T. L., He, Y., Lomolova, L., Malenovsky, Z., Yi, Q., Beringer, J., Aimiri, R., Hutley, L., Arellano, P., Stahl, C., Bonal, D. 2020. The global distribution of leaf chlorophyll content. Remote Sensing of Environment,236, 111479. (doi.org/10.1016/J.RSE.2019.111479)

Croft, H., Arabian, J., Chen, J.M., Shang, J., and Liu, J. 2019. Mapping within-field leaf chlorophyll content in agricultural crops for nitrogen management using Landsat-8 imagery. Precision Agriculture. (doi.org/10.1007/S11119-019-09698-Y)

Chou, S., Chen, B., and Chen, J. M. 2019. Multi-angular instrument for tower-based observations of canopy sun-induced chlorophyll fluorescence. Instrumentation Science and Technology, 146-161. (doi.org/10.1080/10739149.2019.1674326)

Canisius, F., Wang, S., Croft, H., Leblanc, S. G., Russell, H. A. J., Chen, J. M., and Wang, R. 2019. AUAV-Based Sensor System for Measuring Land Surface Albedo: Tested over a Boreal Peatland Ecosystem. Drones, 3(1), 27. (doi.org/10.3390/DRONES3010027)

Wang, R., Chen, J. M., Luo, X., Black, A., and Arain, A. 2019. Seasonality of leaf area index and photosynthetic capacity for better estimation of carbon and water fluxes in evergreen conifer forests. Agricultural and Forest Meteorology, 279, 107708. (doi.org/10.1016/j.agrformet.2019.107708)

Zhang, Z., Chen, J. M., Guanter, L., He, L., and Zhang, Y. 2019. From Canopy-Leaving to Total Canopy Far-red Fluorescence Emission for Remote Sensing of Photosynthesis: First Results from TROPOMI. Geophysical Research Letters, 46(21), 12030-12040. (doi.org/10.1029/2019GL084832)

Braghiere, R. K., Quaife, T., Black, E., He, L., and Chen, J. M. 2019. Underestimation of global photosynthesis in Earth System Models due to representation of vegetation structure. Global Biogeochemical Cycles, 33(11), 1358-1369. (doi.org/10.1029/2018GB006135)

Dong, T., Shang, J., Chen, J. M., Liu, J., Qian, B., Ma, B., Morrison, M. J., Zhang, C., Liu, Y., Shi, Y., Pan, H., and Zhou, G. 2019. Assessment of Portable Chlorophyll Meters for Measuring Crop Leaf Chlorophyll Concentration. RemoteSensing,11(22), 2706. (doi.org/10.3390/RS11222706)

Qiu, B., Chen, J. M., Ju, W., Zhang, Q., and Zhang, Y. 2019. Simulating emission and scattering of solar-induced chlorophyll fluorescence at far-red band in global vegetation with different canopy structures. Remote Sensing of Environment, 233, 111373. (doi.org/10.1016/J.RSE.2019.111373)

Chen, B., Chen, J. M., Baldocchi, D. D., Liu, Y., Wang, S., Zheng, T., Black, T. A., and Croft, H. 2019. Including soil water stress in process-based ecosystem models by scaling dowm maximum carboxylation rate using accumulated soil water deficit. Agricultural and Forest Meteorology, 276-277, 107649. (doi.org/10.1016/J.AGRFORMET.2019.107649)

Gonsamo, A., Chen, J. M., He, L., Sun, Y., Rogers, C., and Liu, J. 2019. Exploring SMAP and OCO-2 observations to monitor soil moisture control on photosynthetic activity of global drylands and croplands. Remote Sensing of Environment. 232, 111314. (doi.org/10.1016/J.RSE.2019.111314)

He, L., Chen, J. M., Liu, J., Zheng, T., Wang, R., Joiner, J., Chou, S., Chen, B., Liu, Y., Liu, R., and Rogers, C. 2019. Diverse photosynthetic capacity of global ecosystems mapped by satellite chlorophyll fluorescence measurements. Remote Sensing of Environment, 232,111344. (doi.org/10.1016/J.RSE.2019.111344)

Wei, S., Fang, H., Schaaf, C. B., He, L., and Chen, J. M. 2019. Global 500m clumping index product derived from MODIS BRDF data (2001-2017).  Remote Sensing of Environment, 232, 111296. (doi.org/10.1016/J.RSE.2019.111296)

Wang, H., Jiang, F., Wang, J., Ju, W., and Chen, J. M. 2019. Terrestrial ecosystem carbon flux estimated using GOSAT and COC-2 XCO2 retrievals. Atmospheric Chemistry and Physics, 19, 12067-12082. (doi.org/10.5194/ACP-19-12067-2019)

Chen, J. M., Ju, W., Ciais, P., Viovy, N., Liu, R., Liu, Y., and Lu, X. 2019. Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink. Nature Communications, 10, 4259. (doi.org/10.1038/S41467-019-12257-8)

Gonsamo, A., Ter-Mikaelian, M. T., Chen, J. M., and Chen, J. 2019. Does Earlier and Increased Spring Plant Growth Lead to Reduced Summer Soil Mositure and Plant Growth on Landscpes Typical of Tundra-Taiga Interface? Remote Sesning, 11(17), 1989. (doi.org/10.3390/RS11171989)

Dong, T., Shang, J., Qian, B., Liu, J., Chen, J. M., Jing, Q., McConkey, B., Huffman, T., Daneshfar, B., Champagne, C., Davidson, a., and MacDonald, D. 2019. Field-Scale Crop Seeding Date Estimation from MODIS Data and Growing Degree Days in Manitoba, Canada. Remote Sensing, 11(15), 1760. (doi.org/10.3390/RS11151760)

Qiu, F., Chen, J. M., Croft, H., Li, J., Zhang, Q., Zhang, Y., and Ju, W. 2019. Retrieving Leaf Chlorophyll Content by Incorporating Variable Leaf Surface Reflectance in PROSPECT Model. Remote Sensing, 11(13), 1572. (doi.org/10.3390/RS11131572)

Luo, X., Croft, H., Chen, J. M., He, L., and Keenan, T. F. 2019. Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content. Global Change Biology,25(7), 2499-2514. (doi.org/10.1111/GCB.14624)

Shan, N., Ju, W., Migliavacca, M., Martini, D., Guanter, L., Chen, J. M., Goulas, Y., and Zhang, Y. 2019. Modeling canopy conductance and transpiration from solar-induced chlorophyll fluorescence. Agricultural Forest Meteorology,268: 189-201. (doi.org/10.1016/J.AGRFORMET.2019.01.031)

Xu, M., Liu, R., Chen, J. M., Liu, Y., Shang, R., Ju, W., Wu, C., and Huang, W. 2019. Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach. Remote Sensing of Environment, 224, 60-73.