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Remote Sensing Technology and Application  2022, Vol. 37 Issue (6): 1482-1491    DOI: 10.11873/j.issn.1004-0323.2022.6.1482
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
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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     
Received:  22 July 2021      Published:  15 February 2023
ZTFLH:  TU984  
Corresponding Authors:  Kaiping Wu     E-mail:;
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Na Li
Kaiping Wu

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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.

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Fig. 1  Schematic diagram of the study area
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



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
工业区工厂企业工业园、产业园区、生产车间、公司等6 902



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
Table 1  POI data collection results in the central urban area of Tianjin
Fig. 2  Flow chart of urban functional area identification
Table 2  The POI weight was reclassified in the central city of Tianjin
Fig.3  Decision flow chart of the functional area
Fig. 4  Functional density distribution diagram of the central urban area of Tianjin
Fig.5  A Single Ribbon
Fig.6  Specific distribution of mixed function zones
Fig.7  Area identification comparison results
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