全部论文(时间倒序)
  • [1]

    Jin X, Liu K*, Cao Z, et al., Urban-EPR: A universal model for simulating individual human mobility within intra-urban areas[J]. International Journal of Geographical Information Science, 2025. [paper]

  • [2]

    Li X, Yin L*, Liu K, et al. Deep-reinforcement-learning-based optimization for intra-urban epidemic control considering spatiotemporal orderliness[J]. International Journal of Geographical Information Science, 2024: 1-26. [paper]

  • [3]

    Shi Y, Lv Q, Zhu K, Cai J, Kong D, Liu K, Chen Z, Zhang Z, Yin L. Estimating the two consecutive epidemic waves of SARS-CoV-2 Omicron in Shenzhen, China from November 2022 to July 2023: a modeling study based on multi-source surveillance and mobility data[J]. Advances in Continuous and Discrete Models, 2025: 5. [paper]

  • [4]

    尹凌, 刘康, 梅树江, 等. 呼吸道传染病时空传播风险精细化评估系统构建与应用[J]. 中国卫生信息管理杂志, 2024, 21(05): 653-660. [paper]

  • [5]

    Liu K#, Wang F#, He B*, et al., Revisiting the topology of urban road networks with graph embeddings[C]. 2024 China Automation Congress (CAC). IEEE, 2024.

  • [6]

    Liu K#, Shi Y#, Wang S, Zhao X, Yin L. Impact of initial outbreak locations on transmission risk of infectious diseases in an intra-urban area[J]. Computational Urban Science, 2024, 4: 23. [paper]

  • [7]

    Qiu P, Pang L, Luo Y*, Liu Y, Xing H, Liu K, Zhuang G. Earthquake Event Knowledge Graph Construction and Reasoning[J]. Geomatics, Natural Hazards and Risk, 2024, 15(1): 2383768. [paper]

  • [8]

    Cao Z, Liu K*, Jin X, et al. STAGE: A Spatiotemporal-Knowledge Enhanced Multi-Task Generative Adversarial Network (GAN) for Trajectory Generation[J]. International Journal of Geographical Information Science, 2024. [paper]

  • [9]

    Luo Y, Cao Z, Jin X, Liu K*, Yin L*. Deciphering Human Mobility: Inferring Semantics of Trajectories with Large Language Models[C]. 2024 25th IEEE International Conference on Mobile Data Management (MDM), Brussels, Belgium, 2024: 289-294. [paper]

  • [10]

    Zhao Y, Cheng S, Liu K, et al. Intercity freight connections in China under the view of mass truck trajectories[J]. Cities, 2024, 150: 105034. [paper]

  • [11]

    Zhu K, Yin L, Liu K, et al. Generating synthetic population for simulating the spatiotemporal dynamics of epidemics[J]. PLOS Computational Biology, 2024, 20(2): e1011810. [paper]

  • [12]

    刘康. 人类移动数据生成方法:研究进展与趋势探讨[J]. 地球信息科学学报, 2024, 26(4): 831-847. [paper]

  • [13]

    Liu K#*, Jin X#, Cheng S, et al. Act2Loc: a synthetic trajectory generation method by combining machine learning and mechanistic models[J]. International Journal of Geographical Information Science, 2023, 38(3), 407-431. [paper]

  • [14]

    Zeng W, Lin C, Liu K, et al. Modeling Spatial Non-stationarity via Deformable Convolutions for Deep Traffic Flow Prediction[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35 (3): 2796-2808. [paper]

  • [15]

    Jiang J, Xu Z, Zhang Z, Zhang J, Liu K, Kong Hui*. Revealing the fractal and self-similarity of realistic collective human mobility[J]. Physica A: Statistical Mechanics and its Applications, 2023: 129232. [paper]

  • [16]

    陈洁, 周莹菲, 尹凌, 李烨, 苗芬, 裴韬, 刘康, 任倩茹, 李璇, 张浩, 李子垠, 奚桂锴. 2020年初COVID-19出院患者日常生活时空行为分析[J]. 地理学报, 2023, 78(4): 1028-1043.

  • [17]

    He B, Wu X, Liu K, et al. Trends in Forest Greening and Its Spatial Correlation with Bioclimatic and Environmental Factors in the Greater Mekong Subregion from 2001 to 2020[J]. Remote Sensing, 2022, 14(23): 5982. [paper]

  • [18]

    He B, Huang D, Kong B, Liu K, Zhou C, Sun L, Ning L. Spatial Variations in Vegetation Greening in 439 Chinese Cities From 2001 to 2020 Based on Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index Data[J]. Frontiers in Ecology and Evolution, 2022, 10: 859542. [paper]

  • [19]

    Zhang, H., Yin, L., Mao, L., Mei, S., Chen, T., Liu K., & Feng, S. Combinational recommendation of vaccinations, mask-wearing, and home-quarantine to control influenza in megacities: An agent-based modeling study with large-scale trajectory data[J]. Frontiers in Public Health, 2022, 10: 883624. [paper]

  • [20]

    He B, Hu J, Liu K*, Xue J, Ning L, Fan J. Exploring Park Visit Variability Using Cell Phone Data in Shenzhen, China[J]. Remote Sensing, 2022, 14(3): 499. [paper]

  • [21]

    Xi G, Yin L, Liu K. Intra-urban Region-based Traffic Flow Prediction Based on Spatial-Temporal Graph Convolutional Network Enhanced by Spatial Context[C]. The 10th International Workshop on Urban Computing (UrbComp 2021), held in conjunction with the 29th ACM SIGSPATIAL, 2021. (Best Paper Award) [paper]

  • [22]

    尹凌,刘康,张浩等. 耦合人群移动的COVID-19传染病模型研究进展[J]. 地球信息科学学报, 2021, 23(11): 1894-1909.

  • [23]

    张浩, 尹凌, 刘康等. 深圳市快速抑制COVID-19疫情的非药物干预措施效果评估:基于智能体的建模研究[J]. 地球信息科学学报, 2021, 23(11): 1936-1945. [paper]

  • [24]

    He B, Liu K*, Xue Z, et al. Spatial and Temporal Characteristics of Urban Tourism Travel by Taxi—A Case Study of Shenzhen[J]. ISPRS International Journal of Geo-Information, 2021, 10(7): 445. [paper]

  • [25]

    Yin L, Zhang H, Li Y, Liu K, et al. A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacities. Journal of the Royal Society Interface, 2021, 18(181): 20210112. [paper]

  • [26]

    Li M, Gao S, Lu F, Liu K, et al. Prediction of human activity intensity using the interactions in physical and social spaces through graph convolutional networks[J]. International Journal of Geographical Information Science, 2021, 35:12, 2489-2516. [paper]

  • [27]

    Liu K, Yin L, Zhang M, et al. Facilitating fine-grained intra-urban dengue forecasting by integrating urban environments measured from street-view images[J]. Infectious Diseases of Poverty, 2021, 10: 40. [paper]

  • [28]

    Liu K, Zhang M, Xi G, et al. Enhancing fine-grained intra-urban dengue forecasting by integrating spatial interactions of human movements between urban regions[J]. PLOS Neglected Tropical Diseases, 2020, 14(12): e0008924. [paper]

  • [29]

    Liu K, Yin L, Lu F, et al. Visualizing and exploring POI configurations of urban regions on POI-type semantic space[J]. Cities, 2020, 99: 102610. [paper]

  • [30]

    Liu K, Qiu P, Gao S, et al. Investigating urban metro stations as cognitive places in cities using points of interest[J]. Cities, 2020, 97: 102561. [paper]

  • [31]

    Liu K, Yin L, Ma Z, et al. Investigating physical encounters of individuals in urban metro systems with large-scale smart card data[J]. Physica A: Statistical Mechanics and its Applications, 2020: 123398. [paper]

  • [32]

    Liu K, Gao S, Lu F. Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling[J]. Computers, Environment and Urban Systems, 2019, 74: 50-61. [paper]

  • [33]

    Zhang F, Liu K, Yin L. Investigating Evolutions of Metro Station Functions in Shenzhen with Long-Term Smart Card Data[M]. Geoinformatics in Sustainable Ecosystem and Society. Springer, Singapore, 2019: 33-53. [paper]

  • [34]

    Wan Q, Yin L, Mao L, Wang L, Mei S, Li Q, Liu K. Simulating Human Host Interventions to Control Intra-urban Dengue Outbreaks with a Spatially Individual-based Model[C]. 2019 IEEE International Conference on Real-time Computing and Robotics (RCAR). IEEE, 2019: 537-542. [paper]

  • [35]

    Lu F, Liu K, Duan Y, et al. Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach[J]. Physica A: Statistical Mechanics and its Applications, 2018, 501: 227-237. [paper]

  • [36]

    Liu X, Yu L, Liu K, et al. ST-PF: Spatio-Temporal Particle Filter for Floating Car Data Pre-processing[M]. Information Fusion and Intelligent Geographic Information Systems (IF&IGIS’17). Cham: Springer, 2018: 197-211. [paper]

  • [37]

    Liu K, Gao S, Qiu P, et al. Road2vec: Measuring traffic interactions in urban road system from massive travel routes[J]. ISPRS International Journal of Geo-Information, 2017, 6(11): 321. [paper]

  • [38]

    刘康, 仇培元, 刘希亮, 等. 利用词向量模型分析城市道路交通空间相关性[J]. 测绘学报, 2017, 46(12):2032-2040. [paper]

  • [39]

    李明晓, 陈洁, 张恒才, 仇培元, 刘康, 陆锋. 上海市精细时空尺度人口分布估计与特征分析[J]. 地球信息科学学报, 2017, 19(6): 800-807. [paper]

  • [40]

    Liu X, Liu K, Li M, et al. SHE: Stepwise Heterogeneous Ensemble Method for Citywide Traffic Analysis[C]. Proceedings of the 1st ACM SIGSPATIAL Workshop on Prediction of Human Mobility. 2017: 1-10. [paper]

  • [41]

    Liu X, Liu K, Li M, et al. A ST-CRF map-matching method for low-frequency floating car data[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 18(5): 1241-1254. [paper]

  • [42]

    Liu K, Qiu P, Li M, et al. Exploring urban travel routes’ characteristics from a geometric perspective[C]. 24th International Conference on Geoinformatics. IEEE, 2016: 1-6. [paper]

  • [43]

    Liu X, Lu F, Liu K, et al. A Principal Curve-based method for Geospatial Data Smoothing[C]. The 9th International Conference on Geographic Information Science (GIScience 2016), 2016: 352–355. [paper]

  • [44]

    刘希亮, 程诗奋, 余丽, 刘康, 陆锋. 架起 GIS 与计算机科学的桥梁: ACM SIGSPATIAL 2015会议综述[J]. 地球信息科学学报, 2016, 18(11): 1448-1455. [paper]

  • [45]

    刘康, 段滢滢, 张恒才. 基于路网拓扑层次性表达的驾车路径规划方法[J]. 地球信息科学学报, 2015, 17(9): 1039-1046. [paper]

  • [46]

    刘康, 段滢滢, 陆锋. 基于拓扑与形态特征的城市道路交通状态空间自相关分析[J]. 地球信息科学学报, 2014, 16(3): 390-395. [paper]

  • [47]

    陆锋, 刘康, 陈洁. 大数据时代的人类移动性研究[J]. 地球信息科学学报, 2014, 16(5): 665-672. [paper]

  • [48]

    刘康, 王枫, 翟旭. 全球电离层TEC数据统计分析与全局趋势分析[J]. 测绘通报, 2013 (1): 29-32. [paper]