教育(访问)经历：
2014年9月-2018年12月：南京大学 生态学 博士
2015年9月-2017年10月：美国海洋生物实验室 生态学 博士联合培养
2011年9月-2014年6月：南京林业大学 环境科学专业 硕士
2007年9月-2011年6月：南京林业大学 环境科学专业 学士
工作经历：
2019年3月-2022年9月：西北农林科技大学，农业资源与环境博士后
2022年9月-2024年12月：西北农林科技大学水土保持研究所，副研究员
2025年1月-至今：西北农林科技大学水土保持科学与工程学院，教授
植被定量遥感，日光诱导叶绿素荧光、生态系统碳水循环
1. 国家自然科学基金面上项目（42471420） SIF直接估算GPP过程中关键参数建模研究2025/01–2028/12 主持
2. 国家自然科学基金青年科学基金项目(41901293) 日光诱导叶绿素荧光和旱地作物生产力关联机制研2020/01–2022/12 主持
3. 中国博士后科学基金面上项目(2019M663828) 干旱胁迫下日光诱导叶绿素荧光和作物生产力关联机制 2019/11至2022/09 主持
4. 国家自然科学基金面上项目（42071328） 作物日光诱导叶绿素荧光与光合作用对环境胁迫的协同响应及多尺度关联机制估算2021/01–2024/12 参与
5. 国家自然科学基金面上项目（41971132） 黄土高原刺槐人工林对干旱胁迫的生理生态响应及其模拟 2020/01–2023/12 参与
1. Guo, C., Liu, Z., Lu, X., 2025. Application of Simultaneous Active and Passive Fluorescence Observations: Extending a Fluorescence-Based q L Estimation Model. Sensors 25, 1700.
2. Wang, Y., Yu, Q., Liu, Z., Ren, W., Lu, X., 2025. A practical SIF-based crop model for predicting crop yields by quantifying the fraction of open PSII reaction centers (qL). Remote Sensing of Environment 320, 114658.
3. Xue, J., Huete, A., Liu, Z., Gao, S., Lu, X., 2025. A lightweight SIF-based crop yield estimation model: A case study of Australian wheat. Agricultural and Forest Meteorology 364, 110439.
4. Xue, J., Huete, A., Liu, Z., Wang, Y., Lu, X., 2024. Estimation of global ecosystem isohydricity from solar-induced chlorophyll fluorescence and meteorological datasets. Remote Sensing of Environment 307, 114168.
5. Guo, C.#, Liu, Z.#, Jin, X., Lu, X., 2024. Improved estimation of gross primary productivity (GPP) using solar-induced chlorophyll fluorescence (SIF) from photosystem II. Agricultural and Forest Meteorology 354, 110090.
6. Liu, Z., Guo, C., Yu, Q., Zhu, P., Peng, X., Dong, M., Cai, H., Lu, X., 2024. A SIF-based approach for quantifying canopy photosynthesis by simulating the fraction of open PSII reaction centers (qL). Remote Sensing of Environment 305, 114111.
7. Yang, J., Liu, Z., Yu, Q., Lu, X., 2024. Estimation of global transpiration from remotely sensed solar-induced chlorophyll fluorescence. Remote Sensing of Environment 303, 113998.
8. Zhao, F., Li, Z., Verhoef, W., Fan, C., Luan, H., Yin, T., Zhang, J., Liu, Z., Tong, C., Bao, Y., 2022. Simulation of solar-induced chlorophyll fluorescence by modeling radiative coupling between vegetation and atmosphere with WPS. Remote Sensing of Environment 277, 113075.
9. Liu, Z., Zhao, F., Liu, X., Yu, Q., Wang, Y., Peng, X., Cai, H., & Lu, X. (2022). Direct estimation of photosynthetic CO2 assimilation from solar-induced chlorophyll fluorescence (SIF). Remote Sensing of Environment, 271, 112893-112893
10. Wang, Y., Liu, Z., Yu, Q., Liu, L., Liu, X., Li, L., Jia, Q., Guo, C., Lu, X., 2022. Simulations of solar-induced chlorophyll fluorescence over crop canopies using the integrated APSIM model. Computers and Electronics in Agriculture 203, 107494.
11. Liu, Z., Guo, C., Bai, Y., Zhang, N., Yu, Q., Zhao, F., & Lu, X. (2021). Far-Red Chlorophyll Fluorescence Radiance Tracks Photosynthetic Carbon Assimilation Efficiency of Dark Reactions. Applied Sciences, 11, 10821
12. Liu, X., Liu, Z., Liu, L., Lu, X., Chen, J., Du, S., & Zou, C. (2021). Modelling the influence of incident radiation on the SIF-based GPP estimation for maize. Agricultural and Forest Meteorology, 307
13. Lu, X., Liu, Z., Zhao, F., & Tang, J. (2020). Comparison of total emitted solar-induced chlorophyll fluorescence (SIF) and top-of-canopy (TOC) SIF in estimating photosynthesis. Remote Sensing of Environment, 251, 112083-112083
14. Liu, Z., Lu, X., An, S., Heskel, M., Yang, H., & Tang, J. (2019). Advantage of multi-band solar-induced chlorophyll fluorescence to derive canopy photosynthesis in a temperate forest. Agricultural and Forest Meteorology, 279, 107691
15. Lu#, X., Liu #, Z.,An, S., Miralles, D.G., Maes, W., Liu, Y., & Tang, J. (2018a). Potential of solar-induced chlorophyll fluorescence to estimate transpiration in a temperate forest. Agricultural and Forest Meteorology, 252, 75-87
16. Liu, Z., An, S., Lu, X., Hu, H., & Tang, J. (2018). Using canopy greenness index to identify leaf ecophysiological traits during the foliar senescence in an oak forest. Ecosphere, 9
17. Lu, X., Liu, Z., Zhou, Y., Liu, Y., An, S., & Tang, J. (2018). Comparison of Phenology Estimated from Reflectance-Based Indices and Solar-Induced Chlorophyll Fluorescence (SIF) Observations in a Temperate Forest Using GPP-Based Phenology as the Standard. Remote Sensing, 10
18. Lu, X., Liu, Z.,Zhou, Y., Liu, Y., & Tang, J. (2018). Performance of Solar-Induced Chlorophyll Fluorescence in Estimating Water-Use Efficiency in a Temperate Forest. Remote Sensing, 10
19. Liu, Z., Hu, H., Yu, H., Yang, X., Yang, H., Ruan, C., Wang, Y., & Tang, J. (2015). Relationship between leaf physiologic traits and canopy color indices during the leaf expansion period in an oak forest. Ecosphere, 6
