燕玉超，波兰vs阿根廷波胆分析 地理科学与规划学院副教授、博士生导师。主要研究方向包括植被遥感，植被扰动和树木死亡，植被韧性，自然灾害事件，土地利用/覆被变化，陆地生态系统碳循环，全球变化。目前主要关注各种自然灾害事件(干旱、洪涝、火灾、飓风等)和土地利用/覆被变化导致的植被扰动(树木死亡等)，并探究扰动前后生态系统的抵抗力和恢复力。以第一作者在Nature子刊Nature Ecology & Evolution、Nature Plants，以及遥感和生态类TOP期刊发表论文10多篇。获得过波兰vs阿根廷波胆分析 校级优秀毕业生 (导师：刘小平教授，国家杰出青年基金获得者)、北京大学第九届优秀博雅博士后 (合作导师：朴世龙 院士；科罗拉多州立大学：陈安平 教授) 等奖励。目前担任Remote sensing专刊“全球变化与生态系统韧性的遥感研究”客座编辑。受国际著名遥感专家Jean-Pierre Wigneron教授邀请，担任Frontiers in Remote Sensing期刊“土地利用/覆被变化”副主编。与北京大学、清华大学、中国科学院植物所、中国科学院青藏所、中国农业大学、科罗拉多州立大学、哥本哈根大学、波士顿大学、新墨西哥大学、佛罗里达大学、美国地质调查局、瑞典隆德大学、瑞典农业大学、巴塞罗那自治大学生态研究与森林应用中心、奥地利-国际应用系统分析研究所、法国国家农业食品与环境研究院波尔多遥感实验室、法国环境与气候变化实验室等国内和国际顶尖专家有广泛合作关系。开拓国际视野，助推学术进步。
研究主题包括但不限于：
（1）植被生态遥感；
（2）植被对气候变化的响应与反馈；
（3）土地利用/覆被变化的生态环境响应；
（4）自然灾害事件研究（干旱、洪涝、火灾、飓风等）。
目前主要学术贡献：Our studies resolve a central paradox in global change ecology—the coexistence of widespread forest mortality and large-scale vegetation greening—by demonstrating that ecological responses to climate extremes are fundamentally scale dependent and functionally asynchronous. First, we reveal that severe tree mortality pulses generate strong negative greenness anomalies at fine spatial scales (30 m), but these signals vanish at coarse resolutions (≥250 m) and are overwhelmed by long term greening trends, establishing that broad scale stability can mask fine scale instability—a buffering effect mediated by topographic and biotic heterogeneity (e.g., species richness, forest height). Second, we add a critical temporal and functional dimension: canopy water content (NDII) recovers much more slowly than greenness (NDVI), and global forest recovery rates have declined significantly since the 1990s, driven primarily by post disturbance warming and drying rather than by mortality severity. Together, our studies shift ecological theory from a focus on resistance to a framework of scale dependent, climate limited recovery. They challenge single scale or single indicator assessments of ecosystem health, show that heterogeneous landscapes and biodiversity enhance cross scale stability, and demonstrate that climate during recovery can outweigh disturbance intensity in determining post disturbance trajectories. These findings fundamentally revise how we detect, interpret, and predict forest responses to climate change, with profound implications for carbon cycle models and conservation planning.
欢迎对植被遥感、植被扰动和树木死亡、植被韧性、植被生态模型、植被生态生理、自然灾害事件、土地利用/覆被变化、遥感大数据、深度学习、全球气候变化感兴趣的本科生、硕士生、博士生、博士后报考！我期待和您共同学习、共同进步！做有意义的研究，做有挑战性的研究！！！
科研理念：科研重在讨论，交流，合作以及思维的碰撞，而不是一个人埋头苦干。对每个科研细节，每个步骤，有自己深刻的理解，有自己独特的观点。做科研不仅仅是发paper，更多的是学会科学的思维方式，激发自己的科研热情，探索未知。
目前主要代表作如下：
Yuchao Yan, Shilong Piao, William M. Hammond, Anping Chen, Songbai Hong, Hao Xu, Seth M. Munson, Ranga B. Myneni & Craig D. Allen (2024). Climate-induced tree-mortality pulses are obscured by broad-scale and long-term greening. Nature Ecology & Evolution, 8(5), 912-923. (Nature子刊，中科院TOP期刊)
Yuchao Yan#, Songbai Hong#, Anping Chen, Josep Peñuelas, Craig D. Allen, William M. Hammond, Seth M. Munson, Ranga B. Myneni, Shilong Piao (2025). Satellite-based evidence of recent decline in global forest recovery rate from tree mortality events. Nature Plants,11,731-742 (Nature子刊，中科院TOP期刊)
Yan, Y., Liu, X., Ou, J., Li, X., & Wen, Y., 2018. Assimilating multi-source remotely sensed data into a light use efficiency model for net primary productivity estimation. International Journal of Applied Earth Observation and Geoinformation, 72, 11-25. (中科院TOP期刊)
Yan, Y., Liu, X., Wang, F., Li, X., Ou, J., & Wen, Y., et al., 2018. Assessing the impacts of urban sprawl on net primary productivity using fusion of Landsat and MODIS data. Science of the Total Environment, 613, 1417-1429. (中科院TOP期刊)
Yan, Y., Liu, X., Wen, Y., & Ou, J., 2019. Quantitative analysis of the contributions of climatic and human factors to grassland productivity in northern China. Ecological indicators, 103, 542-553. (中科院TOP期刊)
Yan, Y., Wu, C., & Wen, Y., 2021. Determining the impacts of climate change and urban expansion on net primary productivity using the spatio-temporal fusion of remote sensing data. Ecological Indicators, 127, 107737. (中科院TOP期刊)
Yan, Y., Xu, X., Liu, X., Wen, Y., & Ou, J., 2020. Assessing the contributions of climate change and human activities to cropland productivity by means of remote sensing. International Journal of Remote Sensing, 41(5), 2004-2021. (遥感类旗舰刊)
Yan, Y., Liu, X., & Wen, Y., 2020. Quantification of the Relationship Among Cropland Area, Cropland Management Measures, and Cropland Productivity Using Panel Data Model. International Journal of Plant Production, 14, 689-702. (农业类旗舰刊)
主持项目：
1. 北京大学博雅博士后项目：“全球变暖背景下极端干旱对森林生态系统碳循环的影响“(经费：67.2万)。
2. 波兰vs阿根廷波胆分析 人才引进项目：”全球变暖背景下的植被恢复力变化和树木死亡”(经费：100 万)。
3. 广东省自然科学基金面上项目（经费：10万）。
参与发表的论文如下：
Pei, X., Luo, Y., Hong, S., Yan, Y., Chen, R., Wang, Q., ... & Piao, S. (2026). Natural Forests Have Longer Drought Recovery Times than Planted Forests across China. Agricultural and Forest Meteorology, 380, 111025.
Wang, H., Yan, Y., Li, D., Li, X., Liu, X., Fan, L., ... & Wigneron, J. P. (2025). Terrestrial ecosystems are in transition. Frontiers in Remote Sensing, 6, 1705386.
Shaojian Wang, Xiangjie Chen, Rui Xie, Kangyao Liu, Jieyu Wang, Xiaoping Liu, Klaus Hubacek, Changjiang Wu, Kuishuang Feng, Yuchao Yan, Zhu Liu, Laixiang Sun and Chuanglin Fang (2024). Demand-side insights for steering human appropriation of net primary productivity within planetary boundaries. One Earth, 7(4), 650-662. (Cell 子刊)
Liu, X., Ou, J., Wang, S., Li, X., Yan, Y., Jiao, L., & Liu, Y. (2018). Estimating spatiotemporal variations of city-level energy-related CO2 emissions: An improved disaggregating model based on vegetation adjusted nighttime light data. Journal of Cleaner Production, 177, 101-114.
Wen, Y., Liu, X., Bai, Y., Sun, Y., Yang, J., Lin, K., ... & Yan, Y. (2019). Determining the impacts of climate change and urban expansion on terrestrial net primary production in China. Journal of environmental management, 240, 75-83.
Zhuang, H., Chen, G., Yan, Y., Li, B., Zeng, L., Ou, J., ... & Liu, X. (2022). Simulation of urban land expansion in China at 30 m resolution through 2050 under shared socioeconomic pathways. GIScience & Remote Sensing, 59(1), 1301-1320.
Zhuang, H., Liu, X., Yan, Y., Ou, J., He, J., & Wu, C. (2021). Mapping multi-temporal population distribution in China from 1985 to 2010 using landsat images via deep learning. Remote Sensing, 13(17), 3533.
Liu, X., Li, X., Shi, H., Yan, Y., & Wen, X. (2021). Effect of economic growth on environmental quality: Evidence from tropical countries with different income levels. Science of the Total Environment, 774, 145180.
Zhuang, H., Liu, X., Yan, Y., Zhang, D., He, J., He, J., ... & Li, M. (2022). Integrating a deep forest algorithm with vector‐based cellular automata for urban land change simulation. Transactions in GIS, 26(4), 2056-2080.
Jin, Y., Zhang, H., Yan, Y., & Cong, P. (2020). A semi-parametric geographically weighted regression approach to exploring driving factors of fractional vegetation cover: A case study of guangdong. Sustainability, 12(18), 7512.
Zhuang, H., Liu, X., Liang, X., Yan, Y., He, J., Cai, Y., ... & Zhang, H. (2022). Tensor‐CA: A high‐performance cellular automata model for land use simulation based on vectorization and GPU. Transactions in GIS, 26(2), 755-778.
Huang, Y., Liu, X., Li, X., Yan, Y., & Ou, J. (2018). Comparing the effects of temporal features derived from synthetic time-series NDVI on fine land cover classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(12), 4618-4629.
Shi, H., Li, X., Wang, S., Fang, C., Li, T., Liu, X., Zhang H., Zhang Q., Yan, Y., Tang D., Hubacek, K. (2022). Future climate change will decrease the carbon stock in three-quarters of global protected areas.
Zhuang, H., Liu, X., Li, B., Wu, C., Yan, Y., Zeng, L., & Zheng, C. (2024). Mapping high-resolution global gridded population distribution from 1870 to 2100. Science of The Total Environment, 955, 176867.
Zhuang, H., Liu, X., Yan, Y., Li, B., Wu, C., & Liu, W. (2024). Multiple Land-Use Simulations and Driving Factor Analysis by Integrating a Deep Cascade Forest Model and Cellular Automata: A Case Study in the Pearl River Delta, China. Remote Sensing, 16(15), 2750.
温宥越，孙强，燕玉超，等。粤港澳大湾区陆地生态系统演变对固碳释氧服务的影响[J]。生态学报，2020，40(23)：8482-8493。
目前课题组成员：
在读博士生
- 郭岩—硕士期间以第一作者发表2篇中科院一区TOP论文
- 李荣华—硕士期间以第一作者发表2篇中科院一区TOP论文
在站博士后
- 蔡艺玲—波兰vs阿根廷波胆分析
直博生毕业
- 潘耀—中国科学院地理科学与资源研究所硕博连读毕业
