Fang Lei
Associate Professor
No Content
Paper Publications
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[1] Jianyu Yao, Xiaoyang Kong, Lei Fang* , Zhaohan Huo, Yanbo Peng, Zile Han, Shilong Ren,Jinyue Chen, Xinfeng Wang，Qiao Wang. Drivers of Structural and Functional Resilience Following Extreme Fires in Boreal Forests of Northeast China. FIRE-SWITZERLAND, 8, 2025.
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[2] Guangyu Lv, Xuan Li, Lei Fang*, Yanbo Peng, Chuanxing Zhang, Jianyu Yao, Shilong Ren, Jinyue Chen, Jilin Men, Qingzhu Zhang, Guoqiang Wang, Qiao Wang. Disentangling the Influential Factors Driving NPP Decrease in Shandong Province: An Analysis from Time Series Evaluation Using MODIS and CASA Model. Remote Sensing, 16, 1:26, 2024.
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[3] Yang Lin, Lei Fang*, Wangming Zhou, Zeyu Qiao, Yu Chang, Xinran Yu, Yuanyuan Li, Ping Ren, Jiangtao Xiao*. Evaluating the long-term effects of near-natural restoration on post-fire forest dynamics in a wildland-urban interface landscape. Ecological Indicators, 160, 2024.
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[4] Wanting Wang, Jinyue Chen, Lei Fang*, Yinglan A, Shilong Ren, Jilin Men, Guoqiang Wang. Remote sensing retrieval and driving analysis of phytoplankton density in the large storage freshwater lake: A study based on random forest and Landsat-8 OLI. Journal of Contaminant Hydrology, 261, 2024.
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[5] Chen Z., Zhang C., Li W., Gao L., Liu L., Fang L.*, Zhang C.*. Fire danger forecasting using machine learning-based models and meteorological observation: a case study in Northeastern China. Multimedia Tools and Applications, 2023.
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[6] Dong X., Zhang C.*, Fang L.*， Yan Y.. A deep learning based framework for remote sensing image ground object segmentation. Applied Soft Computing, 130, 2022.
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[7] Zong X., Tian X.*, Fang L.*. Assessing wildfire risk and mitigation strategies in Qipanshan, China. International Journal of Disaster Risk Reduction, 80, 2022.
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[8] Fang，L.，Y. Yu，G. Fang，X. Zhang，Z. Yu，X. Zhang，E. V. Crocker，and J. Yang*. Effects of meteorological factors on the defoliation dynamics of larch caterpillar (Dendrolimus superans Butler) in the Great Xing’an boreal forests. Journal of Forestry Research, 32, 2683-2697, 2021.
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[9] Fang Lei. Estimating Tree Biomass Combining Allometry and Landsat-derived Disturbance History in Subtropical Planted Forests. Remote Sensing of Environment, 235, 1-16, 2019.
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[10] Fang Lei. Competition and Burn Severity Determine Post-Fire Sapling Recovery in a Nationally Protected Boreal Forest of China: An Analysis from Very High-Resolution Satellite Imagery. Remote Sensing. Remote Sensing, 11, 2019.
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[11] Fang Lei. Predicting potential fire severity using vegetation，topography and surface moisture availability in a Eurasian Boreal Forest Landscape. Forests, 9, 2018.
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[12] Fang，L.，J. Yang*，J. Zu，G. Li，and J. Zhang.. Quantifying influences and relative importance of fire weather，topography，and vegetation on fire size and fire severity in a Chinese boreal forest landscape. Forest Ecology and Management, 2015.
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[13] Fang，L.， J. Yang*. Atmospheric effects on the performance and threshold extrapolation of multi-temporal Landsat derived dNBR for burn severity assessment. International Journal of Applied Earth Observation and Geoinformation, 33, 10-20, 2014.
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[14] Shuping Ji，Shilong Ren，Yann Vitasse，Constantin M. Zohner，Yongshuo H. Fu，Xiaoqiu Chen，Xiaoyang Zhang。Charlotte Grossiord，Huiying Liu，Matthias Peichl，Dailiang Peng，Shuai An， Yating Li，Maihe Li，Lei Fang，Jinyue Chen，Xinfeng Wang，Qingzhu Zhang，Guoqiang Wang，Qiao Wang. Growth Onset Rather Than Photosynthesis Strongly Regulates Autumn Senescence Termination Besides Climate Change. GLOBAL ECOLOGY AND BIOGEOGRAPHY, 34, 2025.
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[15] Xiaohui Bai, Changzhi Yang, Lei Fang , Jinyue Chen, Xinfeng Wang, Ning Gao, Peiming Zheng, Guoqiang Wang, Qiao Wang，Shilong Ren. Identification of Salt Marsh Vegetation in the Yellow River Delta Using UAV Multispectral Imagery and Deep Learning. DRONES, 9, 2025.
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[16] 谢刚. Aquaculture Ponds Identification Based on Multi-Feature Combination Strategy and Machine Learning from Landsat-5/8 in a Typical Inland Lake of China. Remote Sensing, 16, 2024.
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[17] Shuping Ji, Shilong Ren, Lei Fang, Jinyue Chen, Guoqiang Wang， Qiao Wang. Improved CASA-Based Net Ecosystem Productivity Estimation in China by Incorporating Developmental Factors into Autumn Phenology Model. Remote Sensing, 17, 2025.
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[18] Haoji Li, Shilong Ren, Lei Fang, Jinyue Chen, Xinfeng Wang, Guoqiang Wang, Qingzhu Zhang，Qiao Wang. An Improved Method for Human Activity Detection with High-Resolution Images by Fusing Pooling Enhancement and Multi-Task Learning. Remote Sensing, 17, 2025.
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[19] Yuan, Z., A. Ali, A. Sanaei, P. Ruiz-Benito, T. Jucker, L. Fang, E. Bai, J. Ye, F. Lin, S. Fang, Z. Hao, X. Wang*. Few large trees, rather than plant diversity and a composition, drive the above-ground biomass stock and dynamics of temperate forests in northeast China. Forest Ecology and Management, 481, 2021.
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[20] Liu，X.，Yu，L.*, Dong，Q., Peng，D.，Wu，W.，Yu，Q.，Cheng，Y.，Xu，Y.，Huang，X.，Zhou， Z.，Wang，D.，Fang，L., and Gong，P.. Cropland heterogeneity changes on the Northeast China Plain in the last three decades (1980s–2010s). PeerJ, 8, 2020.