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武汉市主城区餐饮业空间特征及与动态人口的耦合分析
引用本文:张莹,李全.武汉市主城区餐饮业空间特征及与动态人口的耦合分析[J].华中师范大学学报(自然科学版),2019,53(1):121-129.
作者姓名:张莹  李全
作者单位:1.武汉大学 资源与环境科学学院, 武汉 430079;2.武汉大学 教育部地理信息系统重点实验室, 武汉 430079
摘    要:城市餐饮业空间格局研究对城市规划及城市可持续发展具有重要意义.针对现有研究中方法单调,衍生研究以对影响因素定性分析为主的不足,采用POI数据,运用基于核密度的热点指数方法对武汉市主城区的餐饮热点进行识别,并结合工作日和休息日的百度地图热力图数据构建人口活动强度模型,对动态人口与餐饮业空间分布进行耦合分析.分析发现,武汉市主城区餐饮业可显著识别出1个一级中心、3个二级中心和9个三级中心;餐饮业分布与动态人口的空间匹配程度总体较好,工作日时匹配程度高的区域占比稍高于休息日.匹配程度为较差和差的区域依具体类型不同而散布在大型商圈外围、传统中小型商圈、旅游点、复兴街区和新兴街区.

关 键 词:餐饮业    POI    人口活动强度模型    热点识别    耦合分析  
收稿时间:2019-01-25

The spatial characteristics of catering industry and its coupling analysis with dynamic population in the main city of Wuhan
ZHANG Ying,LI Quan.The spatial characteristics of catering industry and its coupling analysis with dynamic population in the main city of Wuhan[J].Journal of Central China Normal University(Natural Sciences),2019,53(1):121-129.
Authors:ZHANG Ying  LI Quan
Institution:1.School of Resource and Environmental Science, Wuhan University, Wuhan 430079,China;2.Key Laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan 430079,China
Abstract:The research on spatial pattern of urban catering industry is of great importance for urban planning and urban sustainable development. This paper focuses on the simplicity of the existing research methods and insufficiency on the qualitative analysis of influencing factors in the derivative studies. Coupling analysis between dynamic population and the spatial distribution of the catering industry is carried out through identifying the hot spots of catering in the main city of Wuhan using POI data and the hot spot index method based on nuclear density, and establishing the model of population activity intensity by combining the heat map of weekday with weekend from Baidu Map. The analysis shows that there are 1 primary center, 3 secondary centers and 9 tertiary centers of the catering industry in the Wuhan main city. The spatial distribution of catering industry generally matches the dynamic population with the matching degree of weekday slightly higher than that of weekend The regions with poor and even worse matching degree are scattered on the periphery of the large-scale commercial circles, the traditional small and medium-sized shopping districts, tourist spots, renewed blocks and emerging blocks depending on their specific types.
Keywords:catering industry  POI  the model of population activity intensity  hot spot recognition  coupling analysis  
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