李同文

测绘科学与技术学院 助理教授



电子邮件
litw8@mail.sysu.edu.cn



个人简介
李同文，中山大学测绘科学与技术学院助理教授、硕导，从事资源环境遥感与应用研究工作。
近五年发表SCI论文20余篇，其中70%为中科院TOP期刊论文；以第一/通讯作者在GRL、ISPRS P&RS、IEEE TGRS、JAG等国际著名期刊发表SCI论文9篇。论文总被引764次，单篇最高引用175次（google学术，截至2021年5月）。曾作为技术骨干参与国家重点研发、自然科学基金、湖北省技术创新重大项目等多个项目/课题。申请/授权发明专利2项，登记软件著作权1项；应邀担任10余个国际学术期刊审稿人。
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个人主页
https://tongwenli.github.io/
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教育经历
2011.09~2015.06，武汉大学，地理信息系统，理学学士
2015.09~2020.06，武汉大学，地图制图学与地理信息工程，工学博士
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工作经历
2020.09~今，中山大学测绘科学与技术学院，助理教授
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科研成果
Li, T., Shen, H.*, Yuan, Q., Zhang, L., 2021. A Locally Weighted Neural Network Constrained by Global Training for Remote Sensing Estimation of PM2.5. IEEE Transactions on Geoscience and Remote Sensing.
Li, T.*, Cheng, X., 2021. Estimating daily full-coverage surface ozone concentration using satellite observations and a spatiotemporally embedded deep learning approach. International Journal of Applied Earth Observation and Geoinformation, 101, 102356.
Li, T., Shen, H.*, Yuan, Q., Zhang, X., Zhang, L., 2017. Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach. Geophysical Research Letters 44, 11,985-11,993.
Li, T., Shen, H.*, Yuan, Q., Zhang, L., 2020. Geographically and temporally weighted neural networks for satellite-based mapping of ground-level PM2.5. ISPRS Journal of Photogrammetry and Remote Sensing 167, 178-188.
Li, T., Shen, H.*, Zeng, C., Yuan, Q., Zhang, L., 2017. Point-surface fusion of station measurements and satellite observations for mapping PM2.5 distribution in China: Methods and assessment. Atmospheric Environment 152, 477-489.
Li, T., Shen, H.*, Zeng, C., Yuan, Q., 2020. A Validation Approach Considering the Uneven Distribution of Ground Stations for Satellite-Based PM2.5 Estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13, 1312-1321.
Li, T., Wang, Y., Yuan, Q.*, 2020. Remote Sensing Estimation of Regional NO2 via Space-Time Neural Networks. Remote Sensing 12.
Shen, H., Li, T., Yuan, Q.*, Zhang, L., 2018. Estimating Regional Ground-Level PM2.5 Directly From Satellite Top-Of-Atmosphere Reflectance Using Deep Belief Networks. Journal of Geophysical Research: Atmospheres 123, 13,875-813,886.
Yang, Q., Yuan, Q.*, Yue, L., Li, T.*, Shen, H., Zhang, L., 2020. Mapping PM2.5 concentration at a sub-km level resolution: A dual-scale retrieval approach. ISPRS Journal of Photogrammetry and Remote Sensing 165, 140-151. （共同通讯）
Wang, Y., Yuan, Q.*, Li, T.*, Shen, H., Zheng, L., Zhang, L., 2019. Large-scale MODIS AOD products recovery: Spatial-temporal hybrid fusion considering aerosol variation mitigation. ISPRS Journal of Photogrammetry and Remote Sensing 157, 1-12.（共同通讯）
沈焕锋, 李同文*, 2019. 大气PM2.5遥感制图研究进展. 测绘学报 48, 1624.（通讯作者）
Yuan, Q., Shen, H.*, Li, T., Li, Z., Li, S., Jiang, Y., Xu, H., Tan, W., Yang, Q., Wang, J., Gao, J., Zhang, L., 2020. Deep learning in environmental remote sensing: Achievements and challenges. Remote Sensing of Environment 241, 111716. （ESI高被引、ESI Hot Paper）
Wang, Y., Yuan, Q.*, Li, T., Zhu, L., Zhang, L., 2021. Estimating daily full-coverage near surface O3, CO, and NO2 concentrations at a high spatial resolution over China based on S5P-TROPOMI and GEOS-FP. ISPRS Journal of Photogrammetry and Remote Sensing, 175, 311-325.
Yang, Q., Yuan, Q.*, Li, T., Yue, L., 2020. Mapping PM2.5 concentration at high resolution using a cascade random forest based downscaling model: Evaluation and application. Journal of Cleaner Production 277, 123887.
Shen, H., Jiang, Y., Li, T., Cheng, Q., Zeng, C.*, Zhang, L., 2020. Deep learning-based air temperature mapping by fusing remote sensing, station, simulation and socioeconomic data. Remote Sensing of Environment 240, 111692.
Wang, Y., Yuan, Q.*, Li, T., Shen, H., Zheng, L., Zhang, L., 2019. Evaluation and comparison of MODIS Collection 6.1 aerosol optical depth against AERONET over regions in China with multifarious underlying surfaces. Atmospheric Environment 200, 280-301.（ESI高被引）
沈焕锋，李同文. 一种结合卫星和站点观测反演时空连续PM2.5浓度的方法，授权号：ZL7.0. 授权时间：2018.01
沈焕锋，李同文，徐少良，袁强强. 大气PM2.5实时无缝监测发布系统，软件著作权登记号：2019SR**.
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科研项目
中山大学“****”人才启动经费项目，2021-2023，主持
资源与环境信息系统国家重点实验室开放基金，静止与极轨卫星联合的高分辨率大气PM2.5反演技术，2020.12-2022.12，主持
湖北省技术创新专项（重大项目），2019AAA046，时空大数据支持的长江经济带大气PM2.5连续动态监测技术，2019.12-2021.12，参加
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奖励荣誉
[1] 武汉大学“优秀博士毕业生”，2020
[2] 武汉大学学术创新二等奖，2019
[3] 武汉大学王之卓创新人才奖，2017
[4] 湖北省优秀学士论文，2015