Zhou, M.*, Yang M., Ai, T., et al. (2024). Rethinking the null hypothesis in significant colocation pattern mining of spatial flows. Journal of Geographical Systems, 26:375-405.
Fu, Q., Zhou, M.*, Li, Y., et al. (2024). Flow Spatiotemporal Moran’I: Measuring Spatiaotemporal Autocorrelation of Flow Data. Geographical Analysis.
周梦杰, 阳孟杰, 陈慧颖, 田雨萌, 万义良, 夏吉喆. 面向地理流的时空交叉K函数方法. 测绘学报, 2024, 53(8): 1644-1655.
王钰辉, 阳孟杰, 周梦杰,等.面向地理流的双变量时空扫描统计方法. 测绘科学, 2024, 49(1):204-215.
Zhou M.*, Yang M.*, Chen Zhe. (2023) Flow colocation quotient: Measuring bivariate spatial association for flow data. Computers, Environment and Urban Systems. 99, 101916.
Zhou, Mengjie; Fu, Qingyang; Li, Yige; Wang, Yixin; Wang, Xiaomi; Hu, Wenqing; Discovering spatiotemporal flow patterns: where the origin–destination map meets empirical orthogonal function decomposition, Cartography and Geographic Information Science, 2023, 50(2), 113-129.
Wu, C., Zhou, M.*, Liu, P., & Yang, M. (2021). Analyzing COVID-19 using multisource data: An integrated approach of visualization, spatial regression, and machine learning. GeoHealth, 5, e2021GH000439.
Yang, M.; Chen, Z.; Zhou, M.*; Liang, X.; Bai, Z. (2021) The Impact of COVID-19 on Crime: A Spatial Temporal Analysis in Chicago. ISPRS Int. J. Geo-Inf. 10, 152.
Zhou, M., Ai, T.*, Wu, C., Gu, Y., & Wang, N. (2019). A visualization approach for discovering colocation patterns. International Journal of Geographical Information Science, 33(3), 567-592.
Zhou, M., Tian, J., Xiong, F., & Wang, R. (2017). Point grid map: a new type of thematic map for statistical data associated with geographic points. Cartography and Geographic Information Science, 44(5): 374-389.
Zhou, M., Wang, R., Mai, S., & Tian, J. (2016). Spatial and temporal patterns of air quality in the three economic zones of China. Journal of Maps, 12: 156-162.
Ai, T., Zhou, M., Tian, J., & Ye, N. (2016). Origin-destination (OD) of the interprovincial floating population of China. Journal of Maps, 12: 577-583.
Zhou, M., Ai, T., Zhou, G., & Hu, W. (2020). A Visualization Method for Mining Colocation Patterns Constrained by a Road Network. IEEE Access, 8:51933- 51944.
Yu, Q., Gu, Y., Yang, S. Zhou, M.*. (2021). Discovering Spatiotemporal Patterns and Urban Facilities Determinants of Cycling Activities in Beijing. Journal of Geovisualization and Spatial Analysis, 5, 16.
Zhou, M., Hu, W. & Ai, T. (2020). Multi-level thematic map visualization using the Treemap hierarchical representation model. Journal of Geovisualization and Spatial Analysis, 4, 12.
Wu, C., Hu, W., Zhou, M., Li, S., & Jia, Y. (2019). Data-driven regionalization for analyzing the spatiotemporal characteristics of air quality in China. Atmospheric Environment, 203, 172-182.
Zhou, M.,Cheng, Y., Ye, N., & Tian, J. (2017). Effectiveness and Efficiency of Using Different Types of Rectangular Treemap as Diagrams in Cartography. In Advances in Cartography and GIScience. Springer.
Zhou, M., Wang, R., Tian, J., Ye, N., & Mai, S. (2016). A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public. PloS one, 11(4), e0152881.
Ai, T., Zhou, Q., Zhang, X., Huang, Y., & Zhou, M. (2014). A simplification of Ria coastline with geomorphologic characteristics preserved. Marine Geodesy, 37(2): 167-186.
艾廷华, 周梦杰 & 陈亚婕. (2014). 专题地图属性信息的 LOD 表达与 TreeMap 可视化. 测绘学报, 42(3): 453-460.
艾廷华, 周梦杰 & 李晓明. (2017). 网络空间同位模式的加色混合可视化挖掘方法. 测绘学报, 46(6): 753-759.