HU Qiushi, LI Rui, WU Huayi, LIU Zhaohui, CAI Jing. Population Analysis Unit Expression Considering Urban Scene Changes[J]. Geomatics and Information Science of Wuhan University, 2024, 49(10): 1788-1799. DOI: 10.13203/j.whugis20220579
Citation: HU Qiushi, LI Rui, WU Huayi, LIU Zhaohui, CAI Jing. Population Analysis Unit Expression Considering Urban Scene Changes[J]. Geomatics and Information Science of Wuhan University, 2024, 49(10): 1788-1799. DOI: 10.13203/j.whugis20220579

Population Analysis Unit Expression Considering Urban Scene Changes

More Information
  • Received Date: November 19, 2022
  • Available Online: December 14, 2023
  • Objectives 

    Population analysis unit is the spatiotemporal object and basic part of geographical analysis in different urban scenes. Aiming at the problem that the current unit expression model pays less attention to the description of specific population analysis features and lacks the correlation method and referen‑ce standard of scene and unit feature expression. We propose a population analysis unit expression model considering urban scene change.

    Methods 

    The model first considers the unit's demand for feature description of population spatiotemporal analysis in two-dimensional space, as well as the dissimilarity of components such as objects and environments of urban scenes, forming a population analysis unit expression model that integrates scene components. Then, based on the content of model expression, the relationship between urban scene and population analysis unit is analyzed. Referring to the geographic scene modeling method, the correlation characteristics and reference standards between scene and population analysis unit are constructed.

    Results 

    In order to verify the rationality of the method, we take the epidemic analysis scenario in Wuhan City, Hubei Province, China as a case to realize the population analysis unit modeling and attribute feature dynamic update considering the scenario change. The results show that the proposed model can correlate urban scene information with population analysis unit characteristics according to standards and help to improve unit description ability.

    Conclusions 

    By associating the information and characteristics of urban scene elements, the proposed model can enhance the expression ability of units and map the information and characteristics of urban scene in a more standard and reasonable way. It can also provide a referen‑

    ce for the geometric construction of the unit and the interpretation of the analysis results.

  • [1]
    刘盛和, 邓羽, 胡章. 中国流动人口地域类型的划分方法及空间分布特征[J]. 地理学报, 2010, 65(10):1187-1197.

    Liu Shenghe, Deng Yu, Hu Zhang. Research on Classification Methods and Spatial Patterns of the Regional Types of China’s Floating Population[J]. Acta Geographica Sinica, 2010, 65(10): 1187-1197.
    [2]
    刘耀林, 方飞国, 王一恒. 基于手机数据的城市内部就业人口流动特征及形成机制分析: 以武汉市为例[J]. 武汉大学学报(信息科学版), 2018, 43(12):2212-2224.

    Liu Yaolin, Fang Feiguo, Wang Yiheng. Characteristics and Formation Mechanism of Intra-urban Employment Flows Based on Mobile Phone Data:Taking Wuhan City as an Example[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2212-2224.
    [3]
    姚尧, 张亚涛, 关庆锋, 等. 使用时序出租车轨迹识别多层次城市功能结构[J]. 武汉大学学报(信息科学版), 2019, 44(6):875-884.

    Yao Yao, Zhang Yatao, Guan Qingfeng, et al. Sensing Multi-level Urban Functional Structures by Using Time Series Taxi Trajectory Data[J]. Geomatics and Information Science of Wuhan University, 2019, 44(6): 875-884.
    [4]
    郑宇. 城市计算概述[J]. 武汉大学学报(信息科学版), 2015,40(1):1-13.

    Zheng Yu. Introduction to Urban Computing[J]. Geomatics and Information Science of Wuhan University, 2015,40(1):1-13.
    [5]
    吴京航, 桂志鹏, 申力, 等. 顾及格网属性分级与空间关联的人口空间化方法[J]. 武汉大学学报(信息科学版), 2022, 47(9):1364-1375.

    Wu Jinghang, Gui Zhipeng, Shen Li, et al. Population Spatialization by Considering Pixel-Level Attribute Grading and Spatial Association[J]. Geomatics and Information Science of Wuhan University, 2022, 47(9): 1364-1375.
    [6]
    Séguin A M, Apparicio P, Riva M. The Impact of Geographical Scale in Identifying Areas as Possible Sites for Area-Based Interventions to Tackle Poverty: The Case of Montréal[J]. Applied Spatial Analysis and Policy, 2012, 5(3): 231-251.
    [7]
    Zhou X G, Liu J Z, Yeh A G O, et al. The Uncertain Geographic Context Problem in Identifying Activity Centers Using Mobile Phone Positioning Data and Point of Interest Data[M]//Harvey F, Leung Y. AdvancesinSpatial Data Handling and Analysis. New York: Springer, 2015.
    [8]
    Wang J, Kwan M P. An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship Between Food Environment Exposures and Body Weight[J]. International Journal of Environmental Research and Public Health, 2018, 15(9): 2022.
    [9]
    Kwan M P. The Uncertain Geographic Context Problem[J]. Annals of the Association of American Geographers, 2012, 102(5): 958-968.
    [10]
    Brown D G, Riolo R, Robinson D T, et al. Spatial Process and Data Models: Toward Integration of Agent-Based Models and GIS[J]. Journal of Geographical Systems, 2005, 7(1): 25-47.
    [11]
    Worboys M F, Hearnshaw H M, Maguire D J. Object-Oriented Data Modelling for Spatial Databases[J]. International Journal of Geographical Information Systems, 1990, 4(4): 369-383.
    [12]
    Worboys M F. A Unified Model for Spatial and Temporal Information[J]. The Computer Journal, 1994, 37(1): 26-34.
    [13]
    宋玮. 时空数据模型及其在土地管理中的应用研究[D]. 郑州: 信息工程大学, 2005.

    Song Wei. Spatio-Temporal Data Model and Its Application in Land Management[D].Zhengzhou: Information Engineering University, 2005.
    [14]
    宋玮, 王家耀, 郭金华. 面向对象时空数据模型的研究[J]. 测绘科学技术学报, 2006, 23(4):235-238.

    Song Wei, Wang Jiayao, Guo Jinhua. An Object-Oriented Spatial-Temporal Data Model[J]. Journal of Geomatics Science and Technology, 2006, 23(4): 235-238.
    [15]
    朱杰, 张宏军. 面向仿真事件的战场地理环境时空过程建模[J]. 武汉大学学报(信息科学版), 2020, 45(9): 1367-1377.

    Zhu Jie, Zhang Hongjun. Battlefield Geographic Environment Spatiotemporal Process Model Based on Simulation Event[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1367-1377.
    [16]
    吴长彬, 闾国年. 一种改进的基于事件-过程的时态模型研究[J]. 武汉大学学报(信息科学版), 2008, 33(12): 1250-1253.

    Wu Changbin, Guonian Lü. Improved Event-Process Based on Spatiotemporal Model[J].Geomatics and Information Science of Wuhan University, 2008, 33(12): 1250-1253.
    [17]
    孟令奎, 赵春宇, 林志勇, 等. 基于地理事件时变序列的时空数据模型研究与实现[J]. 武汉大学学报(信息科学版), 2003, 28(2): 202-207.

    Meng Lingkui, Zhao Chunyu, Lin Zhiyong, et al. Research and Implementation of Spatiotemporal Data Model Based on Time-Varying Sequence of Geographical Events[J]. Geomatics and Information Science of Wuhan University, 2003, 28(2): 202-207.
    [18]
    苏奋振, 周成虎. 过程地理信息系统框架基础与原型构建[J]. 地理研究, 2006, 25(3): 477-484.

    Su Fenzhen, Zhou Chenghu. A Framework for Process Geographical Information System[J].Geographical Research, 2006, 25(3): 477-484.
    [19]
    朱杰, 游雄, 夏青. 基于任务过程的战场环境对象时空数据组织模型[J]. 武汉大学学报(信息科学版), 2018, 43(11): 1739-1745.

    Zhu Jie, You Xiong, Xia Qing. Battlefield Environment Object Spatiotemporal Data Organizing Model Based on Task-Process[J].Geomatics and Information Science of Wuhan University, 2018, 43(11): 1739-1745.
    [20]
    Chen B Y, Yuan H, Li Q Q, et al. Spatiotemporal Data Model for Network Time Geographic Analysis in the Era of Big Data[J]. International Journal of Geographical Information Science, 2016, 30(6): 1041-1071.
    [21]
    Camossi E, Bertolotto M, Bertino E, et al. A Multigranular Spatiotemporal Data Model[C]//The 11th ACM International Symposium on Advances in Geographic Information Systems, New Orleans Louisiana, USA, 2003.
    [22]
    Camossi E, Bertolotto M, Bertino E. A Multigranular Object-Oriented Framework Supporting Spatiotemporal Granularity Conversions[J]. International Journal of Geographical Information Science, 2006, 20(5): 511-534.
    [23]
    华一新, 周成虎. 面向全空间信息系统的多粒度时空对象数据模型描述框架[J]. 地球信息科学学报, 2017, 19(9):1142-1149.

    Hua Yixin, Zhou Chenghu. Description Frame of Data Model of Multi-granularity Spatiotemporal Object for Pan-Spatial Information System[J]. Journal of Geo-Information Science, 2017, 19(9): 1142-1149.
    [24]
    刘朝辉, 李锐, 王璟琦. 顾及语义尺度的时空对象属性特征动态表达[J]. 地球信息科学学报, 2017, 19(9):1185-1194.

    Liu Zhaohui, Li Rui, Wang Jingqi. A Dynamic Representation Method of Considering Semantic Scales of Attributes of Spatiotemporal Object[J]. Journal of Geo-Information Science, 2017, 19(9): 1185-1194.
    [25]
    李锐, 石佳豪, 董广胜, 等. 多粒度时空对象组成结构表达研究[J]. 地球信息科学学报, 2021, 23(1): 113-123.

    Li Rui, Shi Jiahao, Dong Guangsheng, et al. Research on Expression of Multi-granularity Spatio-Temporal Object Composition Structure[J].Journal of Geo-Information Science, 2021, 23(1): 113-123.
    [26]
    刘凯, 毋河海, 艾廷华, 等. 地理信息尺度的三重概念及其变换[J]. 武汉大学学报 ( 信息科学版), 2008, 33(11): 1178-1181.

    Liu Kai, Wu Hehai, Ai Tinghua, et al. Three-Tiered Concepts of Scale of Geographical Information and Its Transformation[J].Geomatics and Information Science of Wuhan University, 2008, 33(11): 1178-1181.
    [27]
    Lü G, Batty M, Strobl J, et al. Reflections and Speculations on the Progress in Geographic Information Systems (GIS): A Geographic Perspective[J]. International Journal of Geographical Information Science, 2019, 33(2): 346-367.
    [28]
    Lü G, Chen M, Yuan L W, et al. Geographic Scenario: A Possible Foundation for Further Development of Virtual Geographic Environments[J]. International Journal of Digital Earth, 2018, 11(4): 356-368.
    [29]
    Biehl A, Ermagun A, Stathopoulos A. Community Mobility MAUPing: A Socio-spatial Investigation of Bikeshare Demand in Chicago[J]. Journal of Transport Geography, 2018, 66: 80-90.
    [30]
    边馥苓, 杜江毅, 孟小亮. 时空大数据处理的需求、应用与挑战[J]. 测绘地理信息, 2016, 41(6):1-4.

    Bian Fuling, Du Jiangyi, Meng Xiaoliang. Requirements,Applications and Challenges of Spatiotemporal Big Data Processing[J]. Journal of Geomatics, 2016, 41(6): 1-4.
    [31]
    Wu C S, Murray A T. A Cokriging Method for Estimating Population Density in Urban Areas[J]. Computers,Environment and Urban Systems, 2005, 29(5): 558-579.
    [32]
    Wong D W S. The Modifiable Areal Unit Problem (MAUP)[M]//Janelle D G, Warf B, Hansen K. WorldMinds: Geographical Perspectives on 100 Problems. Dordrecht: Springer, 2004.
    [33]
    段世江.论人口社会化[J].人口与经济,2004(S1):24-26.

    Duan Shijiang. On Population Socialization[J]. Population & Economics,2004(S1):24-26.
    [34]
    崔珂瑾, 程昌秀. 空间数据模型研究综述[J]. 地理信息世界, 2013,20(3): 31-38.

    Cui Kejin, Cheng Changxiu. Research Review on Spatial Data Models[J].Geomatics World, 2013, 20(3): 31-38.
    [35]
    周成虎. 全空间地理信息系统展望[J]. 地理科学进展, 2015,34(2):129-131.

    Zhou Chenghu. Prospects on Pan-Spatial Information System[J]. Progress in Geography, 2015,34(2):129-131.
    [36]
    华一新. 全空间信息系统的核心问题和关键技术[J]. 测绘科学技术学报, 2016, 33(4):331-335.

    Hua Yixin. The Core Problems and Key Technologies of Pan-Spatial Information System[J]. Journal of Geomatics Science and Technology, 2016, 33(4): 331-335.
    [37]
    杨超, 杨柳松, 杜阳,等.融合图像和时空信息的社交媒体用户活动分类方法[J]. 武汉大学学报(信息科学版),2023,48(3):463-470.

    Yang Chao, Yang Liusong, Du Yang, et al. Social Media User’s Activity Classification Integrating Image and Spatiotemporal Information[J]. Geomatics and Information Science of Wuhan University, 2023, 48(3): 463-470.
    [38]
    张颖. 略谈戏剧和影视艺术中的叙事性场景[J]. 新世纪剧坛, 2018(5):54-58.

    Zhang Yin. A Brief Discussion of Narrative Scenes in Drama and Film Art[J]. New Century Theatre, 2018(5):54-58.
    [39]
    方志祥, 倪雅倩, 黄守倩. 融合Markov与多类机器学习模型的个体出行位置预测模型[J]. 武汉大学学报(信息科学版), 2021, 46(6): 799-806.

    Fang Zhixiang, Ni Yaqian, Huang Shouqian. A Multi-model Fusion Model of Individual Travel Location Prediction Using Markov and Machine Learning Methods[J]. Geomatics and Information Science of Wuhan University, 2021, 46(6): 799-806.
    [40]
    吕峥, 孙群, 赵国成, 等. 顾及方向关系的农村居民地聚类方法[J]. 武汉大学学报(信息科学版), 2023, 48(4): 631-638.

    Zheng Lü, Sun Qun, Zhao Guocheng, et al. A Clustering Method of Rural Settlement Considering Direction Relation[J]. Geomatics and Information Science of Wuhan University, 2023, 48(4): 631-638.
    [41]
    黄毅. 地理场景数据模型构建与本体表达[D]. 南京: 南京师范大学, 2020.

    Huang Yi. Construction of Geographic Scene Data Model and Ontology Representation[D].Nanjing: Nanjing Normal University, 2020.
    [42]
    曹天邦. 南京市主城区住宅地价时空演变及其影响因素研究[D]. 南京: 南京师范大学, 2013.

    Cao Tianbang. Spatial-Temporal Evolution of Residential Land Price in Nanjing Urban Area and Its Influencing Factors[D].Nanjing: Nanjing Normal University, 2013.
    [43]
    邓楚雄, 李晓青, 向云波, 等. 长株潭城市群地区耕地数量时空变化及其驱动力分析[J]. 经济地理, 2013,33(6):142-147.

    Deng Chuxiong, Li Xiaoqing, Xiang Yunbo, et al. The Spatiotemporal Change and Driving Forces of Cultivated Land Quantity in Chang-Zhu-Tan Urban Agglomeration[J]. Economic Geography, 2013,33(6):142-147.
    [44]
    魏迪, 厉旭宏. 我国“两级政府、三级管理”体制的法理质疑与完善选择[J]. 上海城市管理职业技术学院学报, 2007, 16(2): 71-74.

    Wei Di, Li Xuhong. Jurisprudence Query and Perfect Choice of China's “Two-Level Government and Three-Level Management” System[J].Shanghai Urban Management, 2007, 16(2): 71-74.
    [45]
    胡玲玲. “陌人社会”中社区共同体的重建[J]. 淮海工学院学报(人文社会科学版), 2015, 13(9): 105-107.

    Hu Lingling. Community Reconstruction in a “Strangers’ Society”[J].Journal of Jiangsu Ocean University (Humanities & Social Sciences Edition), 2015, 13(9): 105-107.
    [46]
    周国磊, 李诚固, 张婧, 等. 2003年以来长春市城市功能用地演替[J]. 地理学报, 2015, 70(4):539-550.

    Zhou Guolei, Li Chenggu, Zhang Jing, et al. Transition of Urban Functional Land in Changchun from 2003 to 2012[J]. Acta Geographica Sinica, 2015, 70(4): 539-550.
    [47]
    Jendryke M. Inferring Shanghai’s Urban Vibrancy Using Microwave Remote Sensing and Big Social Sensing Data[D].Wuhan:Wuhan University, 2016.
    [48]
    许小可, 文成, 张光耀, 等. 新冠肺炎暴发前期武汉外流人口的地理去向分布及影响[J]. 电子科技大学学报, 2020,49(3):324-329.

    Xu Xiaoke, Wen Cheng, Zhang Guangyao, et al. The Geographical Destination Distribution and Effect of Outflow Population of Wuhan When the Outbreak of COVID-19[J]. Journal of University of Electronic Science and Technology of China, 2020,49(3):324-329.
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