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基本信息Basic Information
姓 名：许明珠
职 称：副教授
硕导/博导：硕导
最高学位：理学博士
单 位：福建师范大学地理科学学院
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联系方式Contact
通讯地址：福建省福州市闽侯县上街镇乌龙江中大道18号福建师范大学旗山校区科技楼16#
邮政编码：350117
电子邮箱：xumz@fjnu.edu.cn
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研究方向Research Interests
植被遥感与陆地生态系统碳水循环
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个人履历Resume
教育：
2016-2020南京大学地理与海洋科学学院，博士
2018-2019德国地学研究中心，博士联合培养
2013-2016中国科学院地理科学与资源研究所，硕士
2009-2013武汉大学资源与环境科学学院，学士
工作：
2026至今福建师范大学地理科学学院，副教授
2024-2025福建师范大学地理科学学院，讲师
2021-2023福建师范大学地理科学学院，博士后
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个人简介Brief
许明珠，南京大学地理学博士，福建省级高层次人才，福建师范大学“宝琛计划”青年英才。主要研究方向包括基于卫星遥感的植被结构和生化参数反演算法以及数据产品的开发，全球变化下的陆地生态系统碳水循环模拟等，希望利用卫星遥感精确刻画区域和全球尺度上的植被属性变化，进而探讨植被对气候变化的响应机制。工作内容主要涉及野外数据采集、植被辐射传输过程和碳水循环过程模拟，以及对区域和全球尺度中高分辨率卫星资料的处理与分析。
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教学工作Teaching Work
遥感导论（本科生必修课）、植被遥感（本科生选修课）等。
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代表性论文Selected Publications
（1）第一/通讯作者论文
Zhou, H., Xu, M.*, Chen, J. M.*, Wang, X., Shang, R., Wang, R., Yan, Y., Wang, J. 2026. Synergistic retrievals of leaf area index and leaf chlorophyll content in deciduous broadleaf forests from Sentinel-2 and Landsat. Remote Sensing of Environment, 338, 115382. https://doi.org/10.1016/j.rse.2026.115382
Xu, M., Chen, J.M., Liu, Yihong, Wang, R., Shang, R., Leng, J., Shu, L., Liu, J., Liu, R., Liu, Yang, Yang, R., Yan, Y., 2024. Comparative assessment of leaf photosynthetic capacity datasets for estimating terrestrial gross primary productivity. Science of the Total Environment 926. https://doi.org/10.1016/j.scitotenv.2024.171400
Xu, M., Shang, R., Chen, J.M., Zeng, L., 2023. LACC2.0: Improving the LACC Algorithm for Reconstructing Satellite-Derived Time Series of Vegetation Biochemical Parameters. Remote Sensing. 15, 3277. https://doi.org/10.3390/rs15133277
Xu, M., Liu, R., Chen, J.M., Shang, R., Liu, Y., Qi, L., Croft, H., Ju, W., Zhang, Y., He, Y., Qiu, F., Li, J., Lin, Q., 2022. Retrieving global leaf chlorophyll content from MERIS data using a neural network method. ISPRS Journal of Photogrammetry and Remote Sensing. 192, 66–82. https://doi.org/10.1016/J.ISPRSJPRS.2022.08.003
Xu, M., Liu, R., Chen, J.M., Liu, Y., Wolanin, A., Croft, H., He, L., Shang, R., Ju, W., Zhang, Y., He, Y., Wang, R., 2022. A 21-year time-series of global leaf chlorophyll content maps from MODIS imagery. IEEE Transactions on Geoscience and Remote Sensing. 60, 1 – 13. https://doi.org/10.1109/TGRS.2022.3204185
Xu, M., Liu, R., Chen, J.M., Liu, Y., Shang, R., Ju, W., Wu, C., Huang, W., 2019. Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach. Remote Sensing of Environment, 224, 60–73. https://doi.org/10.1016/j.rse.2019.01.039
（2）部分合作者论文
Shu, L., Chen, J. M., Xu, M., Liu, Y., Jiang, F., Ju, W., 2026. Satellite-derived leaf photosynthetic capacity data set improves atmospheric inversion of terrestrial carbon fluxes. Geophysical Research Letters, 53, e2025GL121171. https://doi.org/10.1029/2025GL121171
Yang, R., Liu, R., Liu, Y., Chen, J. M., Xu, M., He, J., 2025. Light Use Efficiency Model Based on Chlorophyll Content Better Captures Seasonal Gross Primary Production Dynamics of Deciduous Broadleaf Forests. Chinese Geographical Science, 35, 55–72. https://doi.org/10.1007/s11769-024-1482-1
Yan, Y., Li, B., Dechant, B., Xu, M., Luo, X., Qu, S., Miao, G., Leng, J., Shang, R., Shu, L. Jiang, C., 2025. Plant traits shape global spatiotemporal variations in photosynthetic efficiency. Nature Plants, 11, 924–934. https://doi.org/10.1038/s41477-025-01958-2
Liu, Y., Chen, J.M., Xu, M., Wang, R., Fan, W., & Li, W., Kammer, L., Prentice, C., Keenan, T.F., Smith,N.G., 2024. Improved global estimation of seasonal variations in c3 photosynthetic capacity based on eco-evolutionary optimality hypotheses and remote sensing. Remote Sensing of Environment, 313, 114338. https://doi.org/10.1016/j.rse.2024.114338
Wang, J., Chen, J.M., Qiu, F., Fan, W., Xu, M., Wang, R., 2024. Simultaneous estimation of leaf directional-hemispherical reflectance and transmittance from multi-angular canopy reflectance. Remote Sensing of Environment, 304, 114025. https://doi.org/10.1016/j.rse.2024.114025
Leng, J., Chen, J. M., Li, W., Luo, X., Xu, M., Liu, J., Wang, R., Rogers, C., Li, B., and Yan, Y., 2024. Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations. Earth System Science Data, 16, 1283–1300. https://doi.org/10.5194/essd-16-1283-2024
Liang, L., Shang, R., Chen, J.M., Xu, M., Zeng, H., 2023. Improved estimation of the underestimated GEDI footprint LAI in dense forests. Geo-spatial Information Science. https://doi.org/10.1080/10095020.2023.2286377
Shang, R., Chen, J.M., Xu, M., Lin, X., Li, P., Yu, G., He, N., Xu, L., Gong, P., Liu, L., Liu, H., Jiao, W., 2023. China’s current forest age structure will lead to weakened carbon sinks in the near future. The Innovation. https://doi.org/10.1016/j.xinn.2023.100515
Li, J., Ju, W., He, W., Wang, H., Zhou, Y., Xu, M., 2019. An Algorithm differentiating sunlit and shaded leaves for improving canopy conductance and evapotranspiration estimates. Journal of Geophysical Research: Biogeosciences. 124, 807–824. https://doi.org/10.1029/2018JG004675
Shang, R., Liu, R., Xu, M., Liu, Y., Zuo, L., Ge, Q., 2017. The relationship between the threshold-based and the inflexion-based approaches in extraction of land surface phenology. Remote Sensing of Environment, 199, 167-170. https://doi.org/10.1016/j.rse.2017.07.020
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数据产品Dataset
MODIS全球叶片叶绿素含量数据产品：
Mingzhu Xu, Ronggao Liu, Jing M. Chen, Yang Liu, & Rong Shang. (2021). Global leaf chlorophyll content (LCC) product from MODIS imagery (2000-2020) (Version V1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5805575
MERIS全球叶片叶绿素含量数据产品：
Mingzhu, X., Liu, R., Chen, J. M., Shang, R., & Liu, Y. (2022). Global leaf chlorophyll content product from MERIS imagery (GLOBMAP MERIS LCC) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10467919
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科研项目Research projects
福建省自然科学基金面上项目，基于高光谱无人机的亚热带阔叶林叶片叶绿素含量遥感反演，2025-2028，主持
国家自然科学基金联合项目课题，海南热带雨林的碳汇稳定性及其调控机制研究，2024-2027，参与
国家自然科学基金青年项目，基于多光谱遥感的落叶阔叶林不同季节叶片叶绿素含量反演研究， 2023-2025，主持
中国博士后科学基金面上资助项目，亚热带阔叶林叶面积指数和叶片叶绿素含量遥感反演研究， 2021-2023，主持
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研究生培养Graduate Student Cultivation
指导或协助指导硕士生6名（已毕业1名），博士生1名。
---数据更新至2026年8月---
