引用本文:顾梦瑶, 李娟, 赵晓峰.基于POI数据的贵阳市服务业空间格局及其影响因素[J].西南师范大学学报(自然科学版),2019,44(12):59~69
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基于POI数据的贵阳市服务业空间格局及其影响因素
顾梦瑶, 李娟, 赵晓峰
贵州师范大学 地理与环境科学学院, 贵阳 550025
摘要:
基于贵阳市中心城区178 749条POI数据,采用核密度分析、平均最近邻分析和区位熵分析,从服务业整体和分行业方面,探讨贵阳市服务业空间分布格局及其影响因素.研究发现:①贵阳市中心城区服务业已基本形成“双核多组团”的结构,极化成核现象显著,呈现出核心—边缘的空间结构;空间上整体呈“Y”型分布形态,主要分布在交通网络中心性好和地势低平的地区;②服务业分行业视角下,不同类型服务业的数量和集聚程度差异有统计学意义;存在明显的核心—边缘空间结构,具体分布模式呈现3种类型;专业化功能区差异明显,在城市边缘更易于形成专业化集聚区;③交通、地形、人口、城市规划是影响服务业布局的主要因素.最后从规划视角提出城市服务业布局优化的策略,对山地城市规划具有指导意义.
关键词:  POI数据  核密度分析  服务业  空间格局  贵阳市
DOI:10.13718/j.cnki.xsxb.2019.12.011
分类号:K901
基金项目:贵州省科技计划项目(黔科合基础[2019]1238号);国家自然科学基金项目(71864008).
Spatial Pattern of Service Industries and Its Influencing Factors in Guiyang Based on POI Data
GU Meng-yao, LI Juan, ZHAO Xiao-feng
School of Geography and Environmental Science, Guizhou Normal University, Guiyang 550025, China
Abstract:
Based on the POI data of 178749 of Guiyang central city, by kernel density analysis, average nearest neighbor analysis and location entropy analysis, the spatial distribution pattern and influencing factors of service industries in Guiyang from the overall and sub-industry of service industries have been explored in this paper. It has been found in the research that, 1) The service industries in Guiyang has basically formed a "dual-nuclear multi-group" structure. The polarization nucleation phenomenon is remarkable, showing a core-edge spatial structure. The space is generally in a "Y"-shaped distribution pattern, mainly distributed in the center of the transportation network and low-lying areas. 2) Sub-industry of service industries showed that the number and concentration of different types are significantly different. There is obvious core-edge space structure, and the specific distribution pattern presents three types. Specialized functional areas have obvious differences, and it is easier to form specialized agglomeration areas at the edge of the city. 3) The main factors affecting the spatial distribution of the service industries are transportation, terrain, population, and urban planning. Finally, proposing the strategy of optimizing the layout of urban service industries from the perspective of planning, which has guiding significance for mountain city planning.
Key words:  POI data  kernel density analysis  service industry  spatial pattern  Guiyang
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