摘要
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.
作者
闫夏
马安青
王云霞
罗元
施树来
马斌
YAN Xia;MA Anqing;WANG Yunxia;LUO Yuan;SHI Shulai;MA Bin(Shandong Provincial Key Laboratory of Marine Environment and Geological Engineering,Ocean University of China,Qingdao 266100,China;College of Environmental Science and Engineering,Ocean University of China,Qingdao 266100,China)
出处
《地域研究与开发》
北大核心
2023年第2期67-72,79,共7页
Areal Research and Development
基金
国家留学基金委资助项目(201806335032)
山东省重点研发计划(重大科技创新工程)(2019JZZY020105)
中国海洋大学本科生研究发展计划(202210423419X)。
关键词
人口行为
百度热力图
POI数据
耦合协调模型
青岛市中心城区
demographic behaviour
Baidu heat map
POI data
coupled coordination model
central urban area of Qingdao City
