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遥感技术与应用  2022, Vol. 37 Issue (6): 1482-1491    DOI: 10.11873/j.issn.1004-0323.2022.6.1482
遥感应用     
基于POI数据的城市功能区识别与分布特征研究
李娜(),吴凯萍()
天津城建大学 经济与管理学院,天津 300384
A POI Data-based Study of Identification and Distribution Characteristics of Urban Functional Districts
Na Li(),Kaiping Wu()
School of Economics and Management,Tianjin Chengjian University,Tianjin 300384,China
 全文: PDF(6163 KB)   HTML
摘要:

以天津市中心城区为研究对象,基于丰富的OSM道路网数据、POI大数据在精细化尺度下进行功能区识别:利用OSM道路网数据生成道路空间将天津市中心城区划分成1 960个研究单元,结合权重赋分的POI数据分析其密度分布以及功能区分布特征。研究结果表明:①在城市功能密度分布中,除工业功能在中心城区外围有集中分布以外,其他城市功能的分布都呈现出从中心向外围逐渐分散的特征;②单一功能区中,商业区和公共管理与公共服务区所占比重较大,其他4个单一功能区所占比重较小;③混合功能区中,以商业—公共管理与公共服务为主的混合功能区所占比重最大;④将功能区识别结果与高德地图对比分析,发现识别结果准确性较高。

关键词: POI大数据城市功能区分布特征OSM道路网数据    
Abstract:

The central urban area of Tianjin is taken as the research object. Based on the abundant OSM road network data and POI big data, functional area identification is carried out at the fine scale. The road space generated by OSM road network data is used to divide the central urban area of Tianjin into 1960 research units. The density distribution and functional area distribution characteristics are analyzed by combining the POI data with weight assignment. The research results show that: (1) In the distribution of urban function density, except for the concentrated distribution of industrial functions in the periphery of the central city, the distribution of other urban functions shows the characteristics of gradual dispersion from the center to the periphery; (2) In a single functional area, commercial areas and public management and public service areas account for a relatively large proportion, while the other four single functional areas account for a small proportion; (3) Among the mixed functional areas, the mixed functional area mainly composed of business-public management and public services has the largest proportion; (4) Comparing the recognition results of functional areas with the Amap, it is found that the accuracy of the recognition results of urban functional areas is relatively high.

Key words: POI big data    Urban functional area    Distribution characteristics    OSM road network data
收稿日期: 2021-07-22 出版日期: 2023-02-15
ZTFLH:  TU984  
基金资助: 天津市艺术科学规划项目“天津市乡村文化旅游空间布局特征测度及优化路径研究”(B22024)
通讯作者: 吴凯萍     E-mail: llnn49@126.com;17865593885@163.com
作者简介: 李 娜(1980-),女,河南淅川人,副教授,硕士生导师,主要从事城市大数据研究。E?mail: llnn49@126.com
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引用本文:

李娜,吴凯萍. 基于POI数据的城市功能区识别与分布特征研究[J]. 遥感技术与应用, 2022, 37(6): 1482-1491.

Na Li,Kaiping Wu. A POI Data-based Study of Identification and Distribution Characteristics of Urban Functional Districts. Remote Sensing Technology and Application, 2022, 37(6): 1482-1491.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.6.1482        http://www.rsta.ac.cn/CN/Y2022/V37/I6/1482

图1  研究区域示意图 审图号:GS(2020)4619
功能区分类POI数据一级分类POI数据二级分类POI数据数量/条
居住区住宅区、住宅附属设施商用住宅、别墅、小区、社区服务中心等5 435
商业区

餐饮购物、住宿服务

体育休闲、商务设施

餐馆、商场、购物中心、酒店、民宿、青旅、体育馆、游乐场、俱乐部、棋牌室、网吧、银行、保险、证券公司等22 594
绿地与广场区公园绿地、风景名胜公园、动物园、植物园、街边绿地、旅游景区、名胜古迹等379
工业区工厂企业工业园、产业园区、生产车间、公司等6 902
公共管理与公共服务区

医疗卫生、文化设施

教育科研、行政办公

医院、诊所、卫生防疫站、博物馆、图书馆、少年宫、职业院校、大学、小学、中学、党政机关、社会团体、事业单位等18 482
交通设施区交通服务设施、交通附属设施汽车站、火车站、地铁站、公交站、飞机场、停车场等10 112
表1  天津市中心城区POI数据采集结果
图2  城市功能区识别流程图
重分类POI居住商业绿地与广场工业公共管理与公共服务交通设施
权重0.210.050.320.180.110.13
表2  天津市中心城区重分类POI权重
图3  功能区判定流程图
图4  天津市中心城区功能密度分布图
图5  单一功能区
图6  混合功能区具体分布
图7  区域识别对比结果
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