Publications

2023

• Zhu, D.,* & Cao, G. (2023). Intelligent Spatial Prediction and Interpolation Methods. In Handbook of Geospatial Artificial Intelligence (GeoAI) edited by Song Gao, Yingjie Hu, and Wenwen Li. https://doi.org/10.1201/9781003308423-7
• Wang, Y., & Zhu, D.* (2023). A hypergraph-based hybrid graph convolutional network for intracity human activity intensity prediction and geographic relationship interpretation. Information Fusion, 104, 102149. https://doi.org/10.1016/j.inffus.2023.102149
• Zhu, D., * & Hu, Y. (2023). Artificial Intelligence. In Concise Encyclopedia of Human Geography edited by Loretta Lees and David Demeritt. 32-36. https://www.e-elgar.com/shop/usd/concise-encyclopedia-of-human-geography-9781800883482.html
• Luo, P., Song, Y., Zhu, D., Cheng, J., & Meng, L. (2023). A generalized heterogeneity model for spatial interpolation. International Journal of Geographical Information Science, 37(3), 634-659. https://doi.org/10.1080/13658816.2022.2147530
• Chen, T., Zhu, D., Cheng, T., Gao, X., & Chen, H. (2023). Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic. Plos one, 18(1), e0277913.  https://doi.org/10.1371/journal.pone.0277913
• Liu, Y., Wang, K., Xing, X., Guo, H., Zhang, W., Luo, Q., ... & Zhu, D. (2023). 地理分析中的空间效应. Acta Geographica Sinica, 78(3), 517-531. https://doi.org/10.11821/dlxb202303001

2022

• Wang, Y., & Zhu, D.* (2022, November). SHGCN: a hypergraph-based deep learning model for spatiotemporal traffic flow prediction. In Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (pp. 30-39). https://doi.org/10.1145/3557918.3565866
• Luo, P., & Zhu, D.* (2022, November). Sensing overlapping geospatial communities from human movements using graph affiliation generation models. In Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (pp. 1-9). https://doi.org/10.1145/3557918.3565862
• Zhu, D.*, Gao, S., & Cao, G. (2022, November). Towards the intelligent era of spatial analysis and modeling. In Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (pp. 10-13). https://doi.org/10.1145/3557918.3565863
• Zhang, W., Ma, Y., Zhu, D., Dong, L., & Liu, Y. (2022, August). Metrogan: Simulating urban morphology with generative adversarial network. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2482-2492). https://doi.org/10.1145/3534678.3539239
• Zhang, Y., Yu, W., & Zhu, D. (2022). Terrain feature-aware deep learning network for digital elevation model superresolution. ISPRS Journal of Photogrammetry and Remote Sensing, 189, 143-162. https://doi.org/10.1016/j.isprsjprs.2022.04.028
• Chen, T., Bowers, K., Zhu, D.*, Gao, X., & Cheng, T. (2022). Spatio-temporal stratified associations between urban human activities and crime patterns: a case study in San Francisco around the COVID-19 stay-at-home mandate. Computational urban science, 2(1), 13. https://doi.org/10.1007/s43762-022-00041-2

2021

• Zhu, D.*, Liu, Y., Yao, X., & Fischer, M. M. (2021). Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions. GeoInformatica, 1-32. https://doi.org/10.1007/s10707-021-00454-x
• Zhu, D.*, Ye, X., & Manson, S. (2021). Revealing the spatial shifting pattern of COVID-19 pandemic in the United States. Scientific Reports, 11(1), 8396. https://doi.org/10.1038/s41598-021-87902-8
• Huang, X., Zhu, D., Zhang, F., Liu, T., Li, X., & Zou, L. (2021). Sensing population distribution from satellite imagery via deep learning: Model selection, neighboring effects, and systematic biases. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 5137-5151. https://doi.org/10.1109/JSTARS.2021.3076630
• Sari Aslam, N., Zhu, D., Cheng, T., Ibrahim, M. R., & Zhang, Y. (2021). Semantic enrichment of secondary activities using smart card data and point of interests: A case study in London. Annals of GIS, 27(1), 29-41. https://doi.org/10.1080/19475683.2020.1783359

2020

• Zhu, D., Zhang, F., Wang, S., Wang, Y., Cheng, X., Huang, Z., & Liu, Y. (2020). Understanding place characteristics in geographic contexts through graph convolutional neural networks. Annals of the American Association of Geographers, 110(2), 408-420. https://doi.org/10.1080/24694452.2019.1694403
• Zhu, D., Cheng, X., Zhang, F., Yao, X., Gao, Y., & Liu, Y. (2020). Spatial interpolation using conditional generative adversarial neural networks. International Journal of Geographical Information Science, 34(4), 735-758. https://doi.org/10.1080/13658816.2019.1599122

2019

2018 and Before

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