[16] Yan, X., Xie, K., Bian, J., Park, J, & Yin, G*. (2026). Improving Multi-Source Merging of Daily Gridded Precipitation Through Realistic Error Structure Representation in Northeast China. Stochastic Environmental Research and Risk Assessment. (Accepted; 中科院二区)

[15] Mao, J., Gao, Y., Bian, J., ..., & Yin, G*. (2026). Scale-Dependent Agreement of Hydrological Loading Displacements from GNSS, GRACE, and a Land Surface Model in the Heihe River Basin. Remote Sensing, 18(21), 3673. （中科院二区）

[14] Yin, G.*, Zhang, Z., Wan, Y., Park, J., Ahmad, J. A., & Bian, J. (2026). Hydrologic implications of GNSS vertical displacements in cold regions: Insights from Northeast China. Water Resources Research, 62(9), e2026WR043628. （中科院一区，吉大C刊）

[13] Wang, J., Fan, X., Yan, X., Sun, Z., & Yin, G.* (2025). Multi-Source Daily Precipitation Merging over the Yangtze River Basin Using Triple Collocation. Geosciences, 15(9), 360.（中科院三区）

[12] Yin, G.*, Park, J., & Kei, Y. (2025). Spatial Downscaling of GRACE Terrestrial Water Storage Anomalies for Drought and Flood Potential Assessment. Journal of Hydrology. 685, 133144.（中科院一区）

[11] Hua, X., Bian, J., & Yin, G.* (2025). Satellite-Based Assessment of Snow Dynamics and Climatic Drivers in the Changbai Mountain Region (2001–2022). Remote Sensing, 17(3), 442. （本科生毕业论文成果；中科院二区）

[10] Yin, G., Zhang, Y., Cao, Y., Park, J*. (2024). Improving Daily Precipitation Estimates by Merging Satellite and Reanalysis Data in Northeast China. Remote Sensing , 16(24), 4703. （本科生毕业论文成果；中科院二区）

[9] Yin, G.*, Yoshikane, T., Kaneko, R., Yoshimura, K. (2023). Improving Global Subseasonal to Seasonal Precipitation Forecasts Using a Support Vector Machine-Based Method. Journal of Geophysical Research: Atmospheres, 128(17), e2023JD038929. （中科院二区）

[8] Yin, G.*, Yoshikane, T., Yamamoto K., Kubota, T., Yoshimura, K*. (2022). A support vector machine-based method for improving real-time hourly precipitation forecast in Japan. Journal of Hydrology. 612, 128125.（中科院一区）

[7] Yin, G., Baik, J., Park, J*. (2022). Comprehensive analysis of GEO-KOMPSAT-2A and FengYun satellite-based precipitation estimates across Northeast Asia. GIScience & Remote Sensing, 59(1), 782-800. https://doi.org/10.1080/15481603.2022.2067970（中科院一区）

[6] Yin, G., Park, J*. (2021). The use of triple collocation approach to merge satellite- and model-based terrestrial water storage for flood potential analysis. Journal of Hydrology, 603, 127197. https://doi.org/10.1016/j.jhydrol.2021.127197（中科院一区）

[5] Yin, G.*, Forman, B. A., Wang, J. (2021).  Assimilation of ground-based GPS observations of vertical displacement into a land surface model to improve terrestrial water storage estimates. Water Resources Research, 57(2), e2020WR028763. （中科院一区，吉大C刊）

[4] Yin, G.*, Forman, B. A., Loomis, B. D., Luthcke, S. B. (2020). Comparison of vertical surface deformation estimates derived from space-based gravimetry, ground-based GPS, and model-based hydrologic loading over snow-dominated watersheds in the United States. Journal of Geophysical Research: Solid Earth, 125, e2020JB019432. https://doi.org/10.1029/2020JB019432（中科院一区，吉大C刊）

[3] Yin, G.*, Mariethoz, G, Sun, Y., McCabe, M. F. (2017).  A comparison of gap-filling approaches for Landsat 7 satellite data.  International Journal of Remote Sensing, 38(23), 6653-6679. https://doi.org/10.1080/01431161.2017.1363432 （中科院三区）

[2] Yin, G.*, McCabe, M. F., Mariethoz, G. (2017). Gap-filling of Landsat 7 imagery using the Direct Sampling method. Remote Sensing, 9(1), 12. https://doi.org/10.3390/rs9010012. （中科院二区）

[1] Yin, G.*, Mariethoz, G., McCabe, M. F. (2015). A Multiple-point Geostatistics Method for filling gaps in Landsat ETM+ SLC-off images. In Weber, T., McPhee, M.J. and Anderssen, R.S. (eds) MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2015, pp. 180-186. (invited 邀请会议论文)