基于POI大数据的资源型城市功能区识别方法与实证&mdash;&mdash;以辽宁省本溪市为例

薛冰; 赵冰玉; 肖骁; 李京忠; 谢潇; 任婉俠

doi:10.13959/j.issn.1003-2398.2020.04.011

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人文地理 ›› 2020, Vol. 35 ›› Issue (4) : 81-90. DOI: 10.13959/j.issn.1003-2398.2020.04.011

城市

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

薛冰^1,2, 赵冰玉^1,2,3, 肖骁^1,2,3, 李京忠^2,4, 谢潇^1,2, 任婉俠^1,2

作者信息 +

A POI DATA-BASED STUDY ON URBAN FUNCTIONAL AREAS OF THE RESOURCESBASED CITY: A CASE STUDY OF BENXI, LIAONING

XUE Bing^1,2, ZHAO Bing-yu^1,2,3, XIAO Xiao^1,2,3, LI Jing-zhong^2,4, XIE Xiao^1,2, REN Wan-xia^1,2

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文章历史 +

摘要

精准识别城市功能区对于优化协调城市人地系统，完善城市规划及促进城市可持续发展具有重要意义。选取公众认知度和地物一般面积对行业POI数据核密度进行加权，构建城市功能区定量识别方法，以本溪为例，输出城市功能区分布图并开展分析。结果表明：①考虑公众认识度与一般面积的核密度加权方法具有更高的实际性和准确性；②本溪市中心城区受地块大小、交通等因素影响，形成“多中心”组团、“单一—混合”功能区协同发展的空间格局。应进一步完善本溪新城区公共服务体系、优化旅游业产业链条，推进资源型城市转型进程。

Abstract

Accurate identification of urban functional areas is of great significance for optimizing and coordinating urban population and land system, improving urban planning and promoting sustainable urban development. We designed the minimal research unit based on road network and selected the public recognition and feature general area of kernel density weighted POI data of the industry, to create quantitative identification system of urban functional areas, put forward the sustainable development strategy of Benxi city from the optimization of urban industrial structure. The results show that: 1) the full sample POI data can improve the precision of urban functional zoning by providing the spatial location of all kinds of industrial entities in the city; 2) the kernel density weighting method can compensate for the shortcomings of reducing the exposure of POI data as point data in the identification of urban functional areas without geographical entity area and influence range; 3) the downtown area of Benxi is affected by the land parcel size, traffic and other factors, forming a spatial pattern of "multi-center" group and "single-mixed" functional area; 4) the central urban area of Benxi city should further improve the public service system, optimize and extend the tourism industry chain, improve the upgrading efficiency of industrial structure, and promote the transformation process of resource-based cities.

导出引用

薛冰, 赵冰玉, 肖骁, 李京忠, 谢潇, 任婉俠. 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 https://doi.org/10.13959/j.issn.1003-2398.2020.04.011

XUE Bing, ZHAO Bing-yu, XIAO Xiao, LI Jing-zhong, XIE Xiao, REN Wan-xia. A POI DATA-BASED STUDY ON URBAN FUNCTIONAL AREAS OF THE RESOURCESBASED CITY: A CASE STUDY OF BENXI, LIAONING[J]. HUMAN GEOGRAPHY. 2020, 35(4): 81-90 https://doi.org/10.13959/j.issn.1003-2398.2020.04.011

中图分类号： K901

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