Satellite-derived estimates of surface ozone by LESO: Extended application and performance evaluation. - Songyan Zhu; Jian Xu 008; Jingya Zeng; Chao Yu; Yapeng Wang; Huanhuan Yan (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Investigating Impacts of Ambient Air Pollution on the Terrestrial Gross Primary Productivity (GPP) From Remote Sensing. - Songyan Zhu; Jian Xu 008; Hao Zhu; Jingya Zeng; Yapeng Wang; Qiaolin Zeng; Dejun Zhang; Xiaoran Liu; Shiqi Yang (IEEE Geosci. Remote. Sens. Lett., 2022)

Explainable Machine Learning Confirms the Global Terrestrial CO2 Fertilization Effect From Space. - Songyan Zhu; Jian Xu 008; Jingya Zeng; Xianbang Feng; Yapeng Wang; Shanning Bao; Jiancheng Shi 001 (IEEE Geosci. Remote. Sens. Lett., 2023)

UFLUX v2.0: A Process-Informed Machine Learning Framework for Efficient and Explainable Modelling of Terrestrial Carbon Uptake. - Wenquan Dong; Songyan Zhu; Jian Xu 008; Casey M. Ryan; Man Chen; Jingya Zeng; Hao Yu; Congfeng Cao; Jiancheng Shi 001 (CoRR, 2024)

UFLUX-GPP: A Cost-Effective Framework for Quantifying Daily Terrestrial Ecosystem Carbon Uptake Using Satellite Data. - Songyan Zhu; Jian Xu 008; Jingya Zeng; Panxing He; Yapeng Wang; Shanning Bao; Jun Ma; Jiancheng Shi 001 (IEEE Trans. Geosci. Remote. Sens., 2024)

UFLUX v2.0: A Process-Informed Machine Learning Framework for Efficient and Explainable Modeling of Terrestrial Carbon Uptake. - Wenquan Dong; Songyan Zhu; Jian Xu 008; Casey M. Ryan; Man Chen; Jingya Zeng; Hao Yu; Congfeng Cao; Jiancheng Shi 001 (IEEE Geosci. Remote. Sens. Lett., 2025)