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Nat. Commun.、Earth Syst. Sci. Data和ISPRS J. Photogramm.等期刊发表SCI论文10余篇，包括一区TOP论文7篇，二区TOP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）、柳叶刀出版社（Lancet Planetary Health）和多家国内外媒体相继报道；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800余次 (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. 承担课程：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，论文投稿于ISPRS J. Photogramm.，在审）

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

Li, T., Wu, J., Wang, Y., & Su, Y. (2025). Improved seamless mapping of surface O3 concentrations using an integrated deep learning framework. npj Climate and Atmospheric Science, 8(1), 124.

Hu, D., Wang, Y., Jing, H., Yue, L., Zhang, Q., Fan, L., ... & Zhang, L. (2025). A global daily seamless 9-km Vegetation Optical Depth (VOD) product from 2010 to 2021. Earth System Science Data, 1-28.

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

Eco Business：https://news.mongabay.com/2025/04/ground-level-ozone-pollution-poses-growing-threat-to-planetary-health/

Mongabay：https://www.eco-business.com/news/rising-ground-level-ozone-pollution-endangers-planetary-health/

South Africa Today：https://southafricatoday.net/environment/ground-level-ozone-pollution-poses-growing-threat-to-planetary-health/

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