基于多源数据的郑州市城市功能区分布与人口活动规律的研究
A Study on the Distribution of Urban Functional Zones and Population Activity Patterns in Zhengzhou City Based on Multi-Source Data
DOI: 10.12677/gser.2025.145093, PDF,    科研立项经费支持
作者: 马汝鑫, 李 俊, 化明星, 赵广岭, 王德生*:郑州师范学院地理与旅游学院,河南 郑州
关键词: 多源数据城市功能区人口活动规律郑州市Multi-Source Data Urban Functional Zones Population Activity Patterns Zhengzhou City
摘要: 城市功能区与人口活动的时空特征是城市规划领域的重要研究内容,从精细尺度识别城市功能区并揭示其人口活动规律,对于城市规划和资源配置具有重要意义。本研究以郑州市主城区为研究区,基于兴趣点、路网、多时相百度热力图等多源数据,采用核密度分析法识别城市功能区分布,并通过空间关联分析探讨城市功能区人口活动的时空聚散模式。研究结果表明:1) 郑州市主城区城市功能区呈现圈层式多中心结构,分布不均衡且类型特征显著;2) 城市人口活动在工作日与周末呈现系统性差异,具有明显的时空波动特征;3) 城市功能区与人口活动之间存在显著空间相关性,商业区是人口集聚与流动的主要载体。本研究为理解城市空间结构提供了数据支持与方法参考,对优化城市空间布局和促进职住平衡具有重要实践价值。
Abstract: The spatiotemporal characteristics of urban functional zones and population activities are important topics in the field of urban planning. Identifying functional zones and revealing population activity patterns at a fine scale are of great significance for urban planning and resource allocation. This study takes the main urban area of Zhengzhou City as the research area, using multi-source data such as points of interest (POI), road networks, and multi-temporal Baidu heat maps. Kernel density estimation was employed to identify the distribution of urban functional zones, and spatial correlation analysis was applied to explore the spatiotemporal aggregation and dispersion patterns of population activities within these zones. The results show that: 1) The urban functional zones in Zhengzhou’s main urban area exhibit a multi-centric ring structure with uneven distribution and distinct zonal characteristics; 2) Urban population activities show systematic differences between weekdays and weekends, with significant spatiotemporal fluctuations; 3) There is a strong spatial correlation between urban functional zones and population activities, with commercial districts serving as the main hubs of population gathering and mobility. This study provides data support and methodological references for understanding urban spatial structure and offers practical insights for optimizing urban layout and promoting jobs-housing balance.
文章引用:马汝鑫, 李俊, 化明星, 赵广岭, 王德生. 基于多源数据的郑州市城市功能区分布与人口活动规律的研究[J]. 地理科学研究, 2025, 14(5): 967-973. https://doi.org/10.12677/gser.2025.145093

参考文献

[1] 顾朝林, 王颖, 邵园, 等. 基于功能区的行政区划调整研究——以绍兴城市群为例[J]. 地理学报, 2015, 70(8): 1187-1201.
[2] Zhang, X., Hua, Q. and Zhang, L. (2016) Development and Application of a Planning Support System for Regional Spatial Functional Zoning Based on GIS. Sustainability, 8, Article 909. [Google Scholar] [CrossRef
[3] 薛冰, 赵冰玉, 肖骁, 等. 基于POI大数据的资源型城市功能区识别方法与实证——以辽宁省本溪市为例[J]. 人文地理, 2020, 35(4): 81-90.
[4] 朱守杰, 杜世宏, 李军, 等. 融合多源空间数据的城镇人口分布估算[J]. 地球信息科学学报, 2020, 22(8): 1607-1616.
[5] 刘彤, 周伟, 曹银贵. 沈阳市城市功能区分布与人口活动研究[J]. 地球信息科学学报, 2018, 20(7): 988-995.
[6] 李岳, 邓志杰, 王毓乾. 基于兴趣点数据的南昌城市功能区识别[J]. 江西科学, 2022, 40(3): 508-513.
[7] 王俊珏, 叶亚琴, 方芳. 基于核密度与融合数据的城市功能分区研究[J]. 地理与地理信息科学, 2019, 35(3): 66-71.
[8] 李欣. 基于POI要素空间聚集特征的城市多中心结构识别——以郑州市为例[J]. 北京大学学报(自然科学版), 2020, 56(4): 692-702.
[9] 王润泽, 周鹏, 潘悦, 等. 基于大数据的城市功能区人口时空聚散模式研究[J]. 地理与地理信息科学, 2022, 38(1): 45-50.
[10] 邱喜兰, 钮晓颖, 徐强. 住房和城乡建设部绿色生态示范城区——上海南桥新城引领郊区新城绿色生态城建设[J]. 建设科技, 2014(15): 46-48.
[11] Liu, X. and Long, Y. (2015) Automated Identification and Characterization of Parcels with OpenStreetMap and Points of Interest. Environment and Planning B: Planning and Design, 43, 341-360. [Google Scholar] [CrossRef
[12] 禹文豪, 艾廷华. 核密度估计法支持下的网络空间POI点可视化与分析[J]. 测绘学报, 2015, 44(1): 82-90.