以青岛市中心城区为例,基于动态的百度热力图和静态的POI数据,借助ArcGIS技术平台,采用栅格计算、核密度分析、耦合协调模型等方法,探究时空两个维度下人群集聚度、集聚位置、活动重心、与POI分布的耦合关系以及城市公共中心等特征。结果表明:工作日人群活动在时空上均受制于通勤节奏,高热力持续时间久;休息日在出行时间上存在滞后特征,空间位置主要集中在商业综合体;人口活动重心迁移在休息日时呈逆时针环形轨迹特征,工作日时轨迹范围更广,反映出就业和商业重心位于居住重心的东北方向;青岛市中心城区人口聚集与POI密度耦合协调关系良好,空间分布上具有“大集聚、小分散”的城市中心体系,存在各级中心发展不平衡、一强多弱等现象。
Taking the central urban area of Qingdao City as an example, this study uses the dynamic Baidu heat map and static POI data and the ArcGIS technology platform to explore the indicators of people aggregation intensity, clustering location, activity centre of gravity, coupling relationship with POI distribution and urban public centre in both spatial and temporal dimensions by using vectorisation, raster calculation, kernel density analysis and construction of coupled coordination model. The results are as follows: Weekdays are constrained by commuting rhythms in both space and time, and the high heat lasts for a long time. There are lagging characteristics at event time on rest days, and the spatial location is mainly concentrated in commercial complexes. The migration of population activity centre of gravity is characterised by a counter-clockwise circular trajectory on rest days, and a wider trajectory range on weekdays, which also reflects that the employment and commercial centre of gravity is located in the northeast of the residential centre of gravity. The central city of Qingdao has a good relationship between population concentration and POI density coupling, and the spatial distribution has a “large concentration, small scattered” urban centre system, but there is also the phenomenon of unbalanced development of centres at all levels, such as one strong, many weak, etc., which suggests consideration for further rational allocation of urban public services.
[1]LIU Y,LIU X,GAO S,et al.Social Sensing:A New Approach to Understanding Our Socioeconomic Environments[J].Annals of the Association of American Geographers,2015,105(3):512-530.
[2]裴韬,刘亚溪,郭思慧,等.地理大数据挖掘的本质[J].地理学报,2019,74(3):586-598.
[3]塔娜,申悦.基于共享度的上海郊区社区居民活动空间隔离及其影响因素[J].地理学报,2020,75(4):849-859.
[4]TA N,CHAI Y,ZHANG Y,et al.Understanding Job-housing Relationship and Commuting Pattern in Chinese Cities:Past,Present and Future[J].Transportation Research Part D:Transport and Environment,2017,52(5):562-573.
[5]赵利利,孟芬,马才学.基于多源遥感数据的武汉市人口空间分布格局演化[J].地域研究与开发,2016,35(3):165-169.
[6]GONG Y,LIN Y,DUAN Z.Exploring the Spatiotemporal Structure of Dynamic Urban Space Using Metro Smart Card Records[J].Computers,Environment and Urban Systems,2017,64(7):169-183.
[7]黄伟力.基于POI的城市空间结构分析:以北京市为例[J].现代城市研究,2017(12):87-95.
[8]柴彦威,张雪,孙道胜.基于时空间行为的城市生活圈规划研究:以北京市为例[J].城市规划学刊,2015(3):61-69.
[9]淳锦,张新长,黄健锋,等.基于POI数据的人口分布格网化方法研究[J].地理与地理信息科学,2018,34(4):83-89.
[10]王振坡,牛家威,王丽艳.基于POI大数据的天津市居民居住就业空间特征及其影响因素研究[J].地域研究与开发,2020,39(2):58-63.
[11]吴志强,叶锺楠.基于百度地图热力图的城市空间结构研究:以上海中心城区为例[J].城市规划,2016,40(4):33-40.
[12]王录仓.基于百度热力图的武汉市主城区城市人群聚集时空特征[J].西部人居环境学刊,2018,33(2):52-56.
[13]郭翰,郭永沛,崔娜娜.基于多元数据的北京市六环路内昼夜人口流动与人口聚集区研究[J].城市发展研究,2018,25(12):107-121.
[14]林勋媛,王广兴,胡月明.基于开放大数据的广州市中心城区职住平衡特征研究[J].热带地理,2020,40(2):254-265.
[15]李娟,李苗裔,龙瀛,等.基于百度热力图的中国多中心城市分析[J].上海城市规划,2016(3):30-36.
[16]郑至键,郑荣宝,徐嘉源,等.基于POI数据和Place2vec模型的城市功能区识别研究[J].地理与地理信息科学,2020,36(4):48-56.
[17]钟炜菁,王德,谢栋灿,等.上海市人口分布与空间活动的动态特征研究:基于手机信令数据的探索[J].地理研究,2017,36(5):972-984.
[18]海晓东,刘云舒,赵鹏军,等.基于手机信令数据的特大城市人口时空分布及其社会经济属性估测:以北京市为例[J].北京大学学报(自然科学版),2020,56(3):518-530.
[19]赵静,宣国富,朱莹.南京都市区社会空间结构与演化:基于第六次人口普查数据的分析[J].地域研究与开发,2021,40(2):56-61.
[20]LI J,LI J,YUAN Y,et al.Spatiotemporal Distribution Characteristics and Mechanism Analysis of Urban Population Density:A Case of Xi’an,Shaanxi,China[J].Cities,2019,86(3):62-70.
[21]吕安民,李成名,林宗坚,等.人口密度的空间连续分布模型[J].测绘学报,2003(4):344-348.
[22]王淑佳,孔伟,任亮,等.国内耦合协调度模型的误区及修正[J].自然资源学报,2021,36(3):793-810.
[23]GAO S,JANOWICZ K,MONTELLO D R,et al.A Data-synthesis-driven Method for Detecting and Extracting Vague Cognitive Regions[J].International Journal of Geographical Information Science,2017,31(6):1245-1271.
[24]HUANG D,LIU Z,ZHAO X,et al.Emerging Polycentric Megacity in China:An Examination of Employment Subcenters and Their Influence on Population Distribution in Beijing[J].Cities,2017,69(9):36-45.
[25]晁恒,马学广,李贵才.珠江三角洲地区多中心空间结构的特征及演变[J].地域研究与开发,2014,33(6):12-18.
[26]晏龙旭,王德,张尚武.城市中心体系研究的理论基础与分析框架[J].地理科学进展,2020,39(9):1576-1586.