Improving the fusion of global soil moisture datasets from SMAP, SMOS, ASCAT, and MERRA2 by considering the non-zero error covariance. - Xiaoxiao Min; Yulin Shangguan; Danlu Li; Zhou Shi (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Relative Strengths Recognition of Nine Mainstream Satellite-Based Soil Moisture Products at the Global Scale. - Xiaoxiao Min; Yulin Shangguan; Jingyi Huang; Hongquan Wang; Zhou Shi (Remote. Sens., 2022)

Gap Filling of the ESA CCI Soil Moisture Data Using a Spatiotemporal Attention-Based Residual Deep Network. - Yulin Shangguan; Xiaoxiao Min; Zhou Shi (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

Tracking hourly PM2.5 using geostationary satellite sensor images and multiscale spatiotemporal deep learning. - Zhige Wang; Ce Zhang 005; Su Ye; Rui Lu; Yulin Shangguan; Tingyuan Zhou; Peter M. Atkinson; Zhou Shi (Int. J. Appl. Earth Obs. Geoinformation, 2024)

A Novel Merging Framework for Generating High-Accuracy Global Soil Moisture by Error Decomposition Through Multiple Collocation Analysis. - Xiaoxiao Min; Yulin Shangguan; Zhou Shi (IEEE Trans. Geosci. Remote. Sens., 2024)

Estimation of Non-Optically Active Water Quality Parameters in Zhejiang Province Based on Machine Learning. - Lingfang Gao; Yulin Shangguan; Zhong Sun; Qiaohui Shen; Zhou Shi (Remote. Sens., 2024)

Comparison of different downscaling schemes for obtaining regional high-resolution soil moisture data. - Yulin Shangguan; Cheng Tong; Zhou Shi; Hongquan Wang; Xiaodong Deng (Int. J. Appl. Earth Obs. Geoinformation, 2025)

A novel algal bloom risk assessment framework by integrating environmental factors based on explainable machine learning. - Lingfang Gao; Yulin Shangguan; Zhong Sun; Qiaohui Shen; Lianqing Zhou (Ecol. Informatics, 2025)