遥感水文、陆面过程模拟、数据同化、机器学习

[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.

[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.

[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）

[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）

[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.

[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.

[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

[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

[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. 

[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

[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 

[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. 

[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)