位置: 
研究方向：
1. 植被定量遥感建模，核心为三维辐射传输模型（http://lessrt.org/）；
2. 激光雷达三维信息处理 (https://github.com/jianboqi/CSF)；
3. 地表异常遥感即时探测；
4. 遥感信号仿真等。
招生：
欢迎勤奋好学、积极向上、对以上研究方向具有浓厚兴趣的同学报考，具有较好数理和编程基础者优先。
2016.10-2018.10 法国图卢兹第三大学, 联合培养博士
2013.09-2019.07 北京师范大学，硕博连读
2008.09-2012.07 北京师范大学，本科
2023.5-至今 北京师范大学
2019.7-2023.4 北京林业大学
北京市科学技术委员会，北京市科技新星计划，2024，主持
国家自然科学基金面上项目，可微分三维辐射传输建模与高分辨率冠层参数反演，2024.1-2027.12，主持
国家自然科学基金青年项目，植被-大气混合场景的三维辐射传输一体化模拟方法，2021.1-2023.12，主持
国家自然科学基金重点项目，遥感实验场数字孪生体构建理论及关键技术研究，参与
Jin, D., Qi, J.*, BorgesGonçalves, N., Wei, J., Huang, H., Pan, Y., 2024. Automated tree crown labelingwith 3D radiative transfer modelling achieves human comparable performances fortree segmentation in semi-arid landscapes. International Journal of AppliedEarth Observation and Geoinformation 134, 104235.
He, S., Qi, J.*, Wang, D., Yan, K., Huang, H., 2024.Estimation of canopy photon recollision probability from airborne laserscanning. Remote Sensing of Environment 311, 114264.https://doi.org/10.1016/j.rse.2024.114264
Zhao, X., Qi, J.*, Jiang,J., Liu, S., Xu, H., Lin, S., Yu, Z., Li, L., Huang, H., 2024a. Fine-scaleretrieval of leaf chlorophyll content using a semi-empirically accelerated 3Dradiative transfer model. International Journal of Applied Earth Observationand Geoinformation 135, 104285.
Zhao, X., Qi, J.*, Xu, H., Yu, Z., Yuan, L., Chen, Y., Huang, H.*, 2023.Evaluating the potential of airborne hyperspectral LiDAR for assessing forestinsects and diseases with 3D Radiative Transfer Modeling. Remote Sensing of Environment 297, 113759.
Qi, J., Jiang, J., Zhou, K., Xie, D., Huang, H., 2023. Fast and AccurateSimulation of Canopy Reflectance under Wavelength-Dependent Optical PropertiesUsing a Semi-Empirical 3D Radiative Transfer Model. Journal of Remote Sensing 3,0017.
Gao, G., Qi,J.*, Lin, S., Hu, R., Huang, H., 2023. Estimating plant area density ofindividual trees from discrete airborne laser scanning data using intensityinformation and path length distribution. International Journal of Applied Earth Observation and Geoinformation 118, 103281.
叶雨洋, 漆建波*, 曹颖, 蒋靖怡, 2023. 基于LESS模型的异质植被冠层光合有效辐射吸收比与植被指数的关系研究. 遥感技术与应用 38, 51–65.
Qi,J.*,Xie,D., Jiang, J., Huang, H., 2022. 3D radiative transfer modeling of structurallycomplex forest canopies through a lightweight boundary-based description ofleaf clusters. Remote Sensing of Environment 283, 113301.
Jin, D., Qi, J.*, Huang, H., Li, L., 2021. Combining3D Radiative Transfer Model and Convolutional Neural Network to AccuratelyEstimate Forest Canopy Cover From Very High-Resolution Satellite Images. IEEEJournal of Selected Topics in Applied Earth Observations and Remote Sensing 14,10953–10963.
Qi, J., Xie, D., Yin, T., Yan, G., Gastellu-Etchegorry, J.-P.,Li, L.,Zhang, W., Mu, X., Norford, L.K., 2019. LESS: LargE-Scale remote sensing dataand image simulation framework over heterogeneous 3D scenes. Remote Sensingof Environment. 221, 695–706.
Qi,J.*, Yin,T., Xie, D., Gastellu-Etchegorry, J.-P.,2019. Hybrid Scene Structuring forAccelerating 3D Radiative Transfer Simulations. Remote Sensing 11,2637
Su,A., Qi, J*., Huang, H., 2020. Indirect Measurement of Forest CanopyTemperature by Handheld Thermal Infrared Imager through Upward Observation. Remote Sensing 12, 3559.
Qi, J., Xie, D., Guo, D. and Yan, G., 2017. A Large-Scale Emulation System for Realistic Three-Dimensional (3-D) ForestSimulation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,10(11), pp.4834-4843.
Zhang,W.; Qi,J.*; Wan, P.; Wang, H.; Xie, D.; Wang, X.; Yan,G. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 2016, 8, 501. [ESI highly cited]
Qi, J., Xie, D., Li, L., Zhang, W., Mu, X., Yan,G.,2019. Estimating Leaf Angle Distribution From Smartphone Photographs. IEEEGeoscience and Remote Sensing Letters 1–5.
漆建波*, 谢东辉, 许月,阎广建, 2019. 三维辐射传输模型LESS原理及其应用. 遥感技术与应用 Issue 5. [邀稿]
Yin, T., Qi, J., Cook, B.D., Morton, D.C., Wei, S., Gastellu-Etchegorry,J.-P., 2020. Modeling Small-Footprint Airborne Lidar-Derived Estimates of GapProbability and Leaf Area Index. Remote Sensing 12, 4.
Sun,T., Qi, J., Huang, H., 2020. Discovering forest height changesbasedon spaceborne lidar data of ICESat-1 in 2005 and ICESat-2 in 2019: a casestudyin the Beijing-Tianjin-Hebei region of China. Forest Ecosystem. 7,53.
Cao,B., Qi, J., Chen, E., Xiao, Q., Liu, Q., Li, Z., 2021. Fine scaleoptical remote sensing experiment of mixed stand over complex terrain(FOREST)in the Gen he Reserve Area: objective, observation and a case study. InternationalJournal of Digital Earth 14, 1411–1432.
Song,J., Zhu, X., Qi,J., Pang, Y., Yang, L., Yu, L., 2021. A Method forQuantifying Understory Leaf Area Index in a Temperate Forest through CombiningSmall Footprint Full-Waveform and Point Cloud LiDAR Data. RemoteSensing 13, 3036.
Tian,L., Qu, Y., Qi, J.,2021. Estimation of Forest LAI Using DiscreteAirborne LiDAR: A Review. Remote Sensing 13, 2408.
Cheng,J., Yang, H., Qi, J., Sun, Z., Han, S., Feng, H., Jiang, J.,Xu, W.,Li, Z., Yang, G., Zhao, C., 2022. Estimating canopy-scale chlorophyll contentin apple orchards using a 3D radiative transfer model and UAV multispectralimagery. Computers and Electronics in Agriculture 202,107401.
Cai,S., Zhang, W., Qi,J., Wan, P., Shao, J., Shen, A., 2018.APPLICABILITY ANALYSIS OF CLOTHSIMULATION FILTERING ALGORITHM FOR MOBILE LIDARPOINT CLOUD. International Archives of the Photogrammetry, RemoteSensing & Spatial Information Sciences 42.
Chu,Q., Yan, G., Qi, J.,Mu, X., Li, L., Tong, Y., Zhou, Y., Liu, Y.,Xie, D., Wild, M., 2021.Quantitative Analysis of Terrain Reflected SolarRadiation in Snow-Covered Mountains: A Case Study in Southeastern Tibetan Plateau. Journal of Geophysical Research: Atmospheres 126,e2020JD034294.
Li, C.,Yu, Z., Wang, S.*,Wu, F., Wen, K., Qi, J.*, Huang, H., 2022. CrownStructure Metrics to Generalize Aboveground Biomass Estimation Model UsingAirborne Laser Scanning Data in National Park of Hainan Tropical Rainforest,China. Forests 13,1142.
Li, L.,Mu, X., Qi, J.,Pisek, J., Roosjen, P., Yan, G., Huang, H., Liu, S.,Baret, F., 2021a.Characterizing reflectance anisotropy of background soil inopen-canopy plantations using UAV-based multiangular images. ISPRS Journalof Photogrammetry and Remote Sensing 177, 263–278.
Xie,D., Wang, X., Qi,J., Chen, Y., Mu, X., Zhang, W., Yan, G., 2018.Reconstruction of Single Tree with Leaves Based on Terrestrial LiDAR PointCloud Data. Remote Sensing10, 686.
Li, B.,Lu, H., Wang, H., Qi,J., Yang, G., Pang, Y., Dong, H., Lian, Y.,2022. Terrain-Net: A Highly-Efficient, Parameter-Free, and Easy-to-Use DeepNeural Network forGround Filtering of UAV LiDAR Data in Forested Environments. Remote Sensing 14, 5798.
Li, L.,Mu, X., Soma, M.,Wan, P., Qi, J., Hu, R., Zhang, W., Tong, Y., Yan,G., 2021b. An Iterative-Mode Scan Design of Terrestrial Laser Scanning inForests for Minimizing Occlusion Effects. IEEE Transactions on Geoscienceand Remote Sensing 59,3547–3566.
2023，北京市自然科学奖二等奖
2021，梁希林业科学技术奖，科技进步二等奖
2019，第四届全国定量遥感学术论坛，优秀报告奖
2015，2nd International Symposium on Computer Vison in Remote Sensing， 最佳学生论文奖
