Publications

• Hu, H., Jiang, H., Zhong, R., Xu, J., Xu, J., Huang, J., … & Lin, T. (2019). A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level. Global change biology.
• Zhang, Z., Hu, H., Yin, D., Kashem, S., Li, R., Cai, H., … & Wang, S. (2019). A cyberGIS-enabled multi-criteria spatial decision support system: A case study on flood emergency management. International Journal of Digital Earth, 12(11), 1364-1381.
• Hu, H., Yin, D., Liu, Y. Y., Terstriep, J., Hong, X., Wendel, J., & Wang, S. (2019). TopoLens: building a CyberGIS community data service for enhancing the usability of high‐resolution national topographic datasets. Concurrency and Computation: Practice and Experience, 31(16).
• Yin, D., Liu, Y., Hu, H., Terstriep, J., Hong, X., Padmanabhan, A., & Wang, S. (2019). CyberGIS‐Jupyter for reproducible and scalable geospatial analytics. Concurrency and Computation: Practice and Experience, 31(11).
• Hu, H., Lin, T., Wang, S., & Rodriguez, L. F. (2017). A cyberGIS approach to uncertainty and sensitivity analysis in biomass supply chain optimization. Applied energy, 203, 26-40.
• Lin, T., Wang, S., Rodríguez, L. F., Hu, H., & Liu, Y. (2015). CyberGIS-enabled decision support platform for biomass supply chain optimization. Environmental Modelling & Software, 70, 138-148.
• Wang, S., Hu, H., Lin, T., Liu, Y., Padmanabhan, A., & Soltani, K. (2015). CyberGIS for data-intensive knowledge discovery. SIGSPATIAL Special, 6(2), 26-33.