热烈欢迎对大气遥感与人工智能研究方向感兴趣的研究生和本科生！

汪源，1995年生，工学博士。研究方向为：机理先验强化的深度学习模型构建；复杂多场景缺失条件下的数据重构与融合；大气环境参数遥感定量反演和预测；全球高分辨率长时序无缝大气环境参数产品研制；大气环境因素人口暴露和健康风险评估等。目前主持或参与多项国家级和省部级项目。共发表学术论文30余篇，EI会议论文3篇；以第一/通讯作者身份在Nature子刊、ESSD和ISPRS P&RS等期刊发表SCI论文10余篇，包括一区TOP论文9篇，二区论文3篇，其中IF>10的论文5篇；全球臭氧健康风险相关研究成果被国家自然科学基金委员会（NSFC科学传播与成果转化中心）和柳叶刀出版社（Lancet Planetary Health）报道；1篇论文入选ESI热点论文；3篇论文入选ESI高被引论文；Google Scholar论文总引用近800次 (h-index: 15)。

奖励荣誉

             

李小文遥感科学青年奖（全国每2年评选5人）；MDPI Remote Sensing Best PhD Thesis Award（全球每年评选1人）；国际大气环境遥感学会中国优秀博士学位论文奖（全国每年评选5人）；武汉大学十大学术之星；王之卓创新人才一等奖；武汉大学研究生学术创新一等奖；国家奖学金；雷军奖学金；光华奖学金；武汉大学优秀毕业生；武汉大学优秀研究生；武汉大学研究生学业奖学金一等奖

社会兼职

             

1. 中国地理学会会员

2. 中国地球物理学会会员

3. 中国环境科学学会会员

4. 中国遥感应用协会会员

5. 江苏省高等学校科学技术协会会员

6. 国际大气环境遥感协会年会分会场召集人（AERSS 2024）

7. IEEE 国际地球科学与遥感论坛气溶胶分会场主席（2019年）

8. ISPRS P&RS、JGR、JES以及AE等多个SCI期刊审稿人

教学工作

             

1. 担任课程：大气探测学（本科生）；气象大数据与人工智能（本科生）

2. 2024年南京信息工程大学“优秀本科毕业论文（设计）支持计划”项目指导教师

3. 2024年省级“大学生创新创业训练计划”项目指导教师（提前结题）

主持或参与项目

                       

1. 国家重点研发计划项目，"热带西太平洋全新世高分辨率气候变化重建、集成和同化研究"（2023YFF0804800），子课题负责人，2023.12-2028.11

2. 南京信息工程大学人才启动经费资助项目，主持，2024.01-2026.12

3. 国家自然科学基金优秀青年项目，"遥感信息处理与应用"，骨干，2020.01-2022.12

4. 湖北省杰出青年科学基金项目，"面向洪涝灾害动态监测的卫星视频数据超分辨率重建"，骨干，2020.01-2022.12

5. 国家自然科学基金面上项目，"耦合变分模型与深度先验的视频遥感图像空谱分辨率增强方法研究"，骨干，2020.01-2023.12

6. 国家重点研发计划项目课题，"多源大数据深度学习的PM2.5浓度反演技术"，骨干，2016.07-2019.06

学生培养

             

硕士研究生

24级

李嘉源、刘多多（武汉大学）

本科生

22级

大气物理学院：苏秋彤

23级

大气物理学院：唐一斐、李娜、韩荞冰、吴超然、肖馨月

龙山书院：钟婷婷、路梓妍、纪天任

网络空间安全学院：张艺宁

金牛湖产教融合园区：沈哲宇

长望学院：张泽武

大气拔尖班：周熹愉

发表论文（*为通讯作者，#为共同一作）

                                                           

2025年

Yuan, Q., Zhong, W., Yang, Q., Peng, Y., Bolch, T., Wang, Y., ... & Zhang, L. (2025). Duration of frozen days show a strong decline in the Northern Hemisphere mainly driven by autumn temperature increase. Innovation Geoscience, 100118-1.

Wang, Y.#, Yang, Y., Yuan, Q., Li, T., Zhou, Y., Zong, L., Wang, M., Xie, Z., Ho, H. C., Gao, M., Tong, S., Lolli, S., & Zhang, L. (2025). Substantially underestimated global health risks of current ozone pollution. Nature Communications (IF=14.7), 16(1), 102. 

NSFC科学传播与成果转化中心科学新闻：https://www.nsfc.gov.cn/csc/20340/20343/69002/index.html

Lancet Planetary Health Newsdesk：https://www.sciencedirect.com/science/article/pii/S2542519625000051

2024年

Hu, D., Wang, Y., Jing, H., Yue, L., Zhang, Q., Fan, L., ... & Zhang, L. (2024). A global daily seamless 9-km Vegetation Optical Depth (VOD) product from 2010 to 2021. Earth System Science Data Discussions, 1-28.

Li, T., Wang, Y., & Wu, J. (2024). Deriving PM2.5 from satellite observations with spatiotemporally weighted tree-based algorithms: enhancing modeling accuracy and interpretability. npj Climate and Atmospheric Science, 7(1), 138.

Wang, M., Wei, T., Lolli, S., Wu, K., Wang, Y., Hu, H., ... & Xia, H. (2024). A long-term Doppler wind LiDAR study of heavy pollution episodes in western Yangtze River Delta region, China. Atmospheric Research, 310, 107616.

Wang, Y., Wang, Y.*, Xiao, Y., Wan, B., Yang, Y., Yuan, Q., Ma, Y., & Wang, G. (2024). Physics-informed multi-temporal ensemble learning for near real-time precipitation estimates from Himawari-8/-9. IEEE Geoscience and Remote Sensing Letters (IF=4.0), 21, 1000805.

2023年

Xiao, Y., Yuan, Q., Jiang, K., He, J., Wang, Y., & Zhang, L. (2023). From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution. Information Fusion, 96, 297-311. ESI热点论文，ESI高被引论文

Wang, Y., Yuan, Q., Li, T., Yang, Y., Zhou, S., & Zhang, L. (2023). Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method. Earth System Science Data (IF=11.2), 15(8), 3597-3622.

Li, T., Yang, Q., Wang, Y., & Wu, J. (2023). Joint estimation of PM2. 5 and O3 over China using a knowledge-informed neural network. Geoscience Frontiers, 14(2), 101499.

Jin, C., Yuan, Q., Li, T., Wang, Y., & Zhang, L. (2023). An optimized semi-empirical physical approach for satellite-based PM 2.5 retrieval: embedding machine learning to simulate complex physical parameters. Geoscientific Model Development, 16(14), 4137-4154.

刘多多, 袁强强, & 汪源. (2023). 基于自适应时空张量补全的甲醛浓度时间序列重建. 测绘工程, 32, 4.

2022年

Wang, Y., Yuan, Q., Zhou, S., & Zhang, L. (2022). Global spatiotemporal completion of daily high-resolution TCCO from TROPOMI over land using a swath-based local ensemble learning method. ISPRS Journal of Photogrammetry and Remote Sensing (IF=10.6), 194, 167-180.

Wang, Y., Yuan, Q., Li, T., & Zhu, L. (2022). Global spatiotemporal estimation of daily high-resolution surface carbon monoxide concentrations using Deep Forest. Journal of Cleaner Production (IF=9.7), 350, 131500.

Wang, Y., Yuan, Q., Zhu, L., & Zhang, L. (2022). Spatiotemporal estimation of hourly 2-km ground-level ozone over China based on Himawari-8 using a self-adaptive geospatially local model. Geoscience Frontiers (IF=8.5), 13(1), 101286. ESI高被引论文

Xiao, Y., Wang, Y.#, Yuan, Q., He, J., & Zhang, L. (2022). Generating a long-term (2003− 2020) hourly 0.25° global PM2.5 dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS). Science of The Total Environment (IF=8.2), 848, 157747.

Zhou, S., Wang, Y., Yuan, Q., Yue, L., & Zhang, L. (2022). Spatiotemporal estimation of 6-hour high-resolution precipitation across China based on Himawari-8 using a stacking ensemble machine learning model. Journal of Hydrology, 609, 127718.

Jin, C., Wang, Y., Li, T., & Yuan, Q. (2022). Global validation and hybrid calibration of CAMS and MERRA-2 PM2.5 reanalysis products based on OpenAQ platform. Atmospheric Environment, 274, 118972.

Tan, S., Wang, Y., Yuan, Q., Zheng, L., Li, T., Shen, H., & Zhang, L. (2022). Reconstructing global PM2.5 monitoring dataset from OpenAQ using a two-step spatio-temporal model based on SES-IDW and LSTM. Environmental Research Letters, 17(3), 034014.

Zhou, S., Wang, Y., & Yuan, Q. (2022, July). Estimation of Hourly Air Temperature in China Based on LightGBM and Himawari-8. In IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 6558-6561). IEEE.

2021年

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 (IF=10.6), 175, 311-325.

Wang, Y., Yuan, Q., Li, T., Tan, S., & Zhang, L. (2021). Full-coverage spatiotemporal mapping of ambient PM2. 5 and PM10 over China from Sentinel-5P and assimilated datasets: Considering the precursors and chemical compositions. Science of The Total Environment (IF=8.2), 793, 148535.

Yang, Q., Wang, B., Wang, Y.#, Yuan, Q., Jin, C., Wang, J., ... & Zhang, L. (2021). Global air quality change during COVID-19: a synthetic analysis of satellite, reanalysis and ground station data. Environmental Research Letters (IF=6.7), 16(7), 074052.

王浩天, 汪源, & 袁强强. (2021). 2008~ 2016 年 MODIS 多角度大气校正气溶胶产品在中国的时空分布及变化趋势. 遥感技术与应用, 36(1), 217-228.

Zhang, Q., Yuan, Q., Li, J., Wang, Y., Sun, F., & Zhang, L. (2021). Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013–2019. Earth System Science Data, 13(3), 1385-1401.

2020年

Wang, Y., Yuan, Q., Shen, H., Zheng, L., & Zhang, L. (2020). Investigating multiple aerosol optical depth products from MODIS and VIIRS over Asia: Evaluation, comparison, and merging. Atmospheric Environment (IF=5), 230, 117548.

Li, T., Wang, Y., & Yuan, Q. (2020). Remote sensing estimation of regional NO2 via space-time neural networks. Remote Sensing, 12(16), 2514.

Wang, Y., Yuan, Q., Xiao, R., Li, T., & Zhang, L. (2020, September). Recovery of the Carbon Monoxide Product from S5P-TROPOMI by Fusing Multiple Datasets: A Case Study in Hubei Province, China. In IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium (pp. 5529-5532). IEEE.

2019年

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 (IF=10.6), 157, 1-12.

Wang, Y., Yuan, Q., Wang, H., Li, T., Shen, H., & Zhang, L. (2019, July). Validation of MODIS 1-Km MAIAC Aerosol Products with AERONET in China During 2008-2016. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 7610-7613). IEEE.

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 (IF=5), 200, 280-301. ESI高被引论文