该研究方向主要是发展针对不同应用、不同尺度的城市增长模型，来支持对未来多种社会经济和气候变化情景下的城市演化路径的测度及空间形态的模拟。主要研究内容包括：1）探讨城市元胞自动机模型的不确定性测度及归因；2）发展针对不同研究问题的城市元胞自动机模型（包括斑块、同化、多模型耦合等）；3）引入时间信息到城市元胞自动机模型来提高模型的鲁棒性和模拟能力；4）开展全球尺度、跨百年、多情景的城市空间演化模拟。
相关论文：
Li, X.C., Zhou, Y.Y.*, Hejazi, M., Wise, M., Vernon, C., Iyer, G., Chen, W. 2021. Global urban growth between 1870 and 2100 from integrated high resolution mapped data and urban dynamic modelling. Communication Earth & Environment, 2(1), 201. doi:10.1038/s43247-021-00273-w.
Li, X.C.*, Zhang, J., Li, Z.Y., Hu, T.Y., Wu, Q.S., Zhao, Y.Y., Yang, J., Huang, J.X., Zhou, Y.Y., Liu, X.P., Gong, P, & Wang, X. 2021. The critical role of temporal contexts in evaluating urban cellular automata models. GIScience & Remote Sensing, 58(6), 799-811. doi: 10.1080/15481603.2021.1946261.
Li, X.C., Zhou, Y.Y.*, & Chen, W. 2020. An improved urban cellular automata model by using the trend adjusted neighborhood. Ecological Processes, 9, 28. doi: 10.1186/s13717-020-00234-9.
Li, X.C., Zhou, Y.Y.*, Eom, J.Y., Yu, S., & Asrar, G.R. 2019. Projecting global urban area growth through 2100 based on historical time-series data and future Shared Socioeconomic Pathways. Earth’s Future, 7(4), 351-362. doi:10.1029/2019EF001152.
Li, X.C., Lu, H.*, Zhou, Y.Y., Hu, T.Y., Liang, L., Liu, X.P., Hu, G.H., & Yu, L. 2017. Exploring the performance of spatio-temporal assimilation in an urban cellular automata model. International Journal of Geographic Information Science., 31(11), 2195-2215. doi: 10.1080/13658816.2017.1357821.
Li, X.C., Gong, P.*, Yu, L., & Hu, T.Y. 2017. A segment derived patch-based logistic cellular automata for urban growth modeling with heuristic rules. Computers, Environment & Urban Systems, 65, 140-149. doi: 10.1016/j.compenvurbsys.2017.06.001.
Li, X.C., Le, Y.*, Sohl, T., Clinton, N., Li, W.Y., Zhu, Z.L., Liu, X.P., & Gong, P. 2016. A cellular automata downscaling based 1 km global land use datasets (2010–2100). Science Bulletin, 61, 1651-1661. doi:10.1007/s11434-016-1148-1.
Li, X.C. & Gong, P.* 2016. Urban growth models: progress and perspective. Science Bulletin, 61, 1637-1650. doi:10.1007/s11434-016-1111-1.
Li, X.C., Liu, X.P.* & Gong, P. 2015. Integrating ensemble-urban cellular automata model with an uncertainty map to improve the performance of a single model. International Journal of Geographical Information Science, 29, 762-785. doi: 10.1080/13658816.2014.997237.
Li, X.C., Liu, X.P.* & Yu, L. 2014. A systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules. International Journal of Geographical Information Science, 28(7), 1317-1335. doi: 10.1080/13658816.2014.883079.
