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基于POI权重与频率密度的上海城市功能区变化分析 被引量:2

Analysis of Shanghai Urban Functional District Changes Based on POI Weight and Frequency Density
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摘要 城市功能区的动态监测可为城市空间结构分析、公共资源的配置以及城市规划提供决策支持。利用POI数据进行城市功能区的识别,多侧重于城市功能区研究单元的划分,很少涉及POI权重的定量分析和城市功能区的时空变化分析。本文以上海市为例,基于TF-IDF算法提出了一种POI赋权进行城市功能区识别与分析的方法:首先基于网格单元,利用TF-TDF算法计算POI权重,然后通过POI权重与频率密度计算,进行城市功能区的识别,建立城市功能区转移矩阵,进行城市功能区的时空变化分析。研究结果表明:基于公共认知度对各类POI赋权具有不一致性,利用TF-TDF算法计算POI权重克服了传统主观赋值法的过于主观性,对于城市功能区的判别更加精准;基于网格单元的城市功能区识别更加准确,从时间序列角度出发,城市功能区的扩散与演化更加直观;上海市2008—2018年,城市化水平较快,无数据区由51.00%下降到19.52%,工业功能区数量下降,商服和公共功能区数量大幅增加,与上海市实际状况相一致。通过研究可为城市发展规划和产业结构合理布局提供参考依据。 The dynamic monitoring of urban functional areas provides decision support for urban spatial structure analysis,public resource allocation and urban planning.Using POI data to identify urban functional areas mostly focuses on the division of research units of urban functional areas,and rarely involves the quantitative analysis of POI weight and spatial-temporal change analysis of urban functional areas.Taking Shanghai as an example,this paper proposes a method of POI weighting and urban functional area identification and analysis based on the TF-IDF algorithm:Firstly,based on the grid unit,the TF-TDF algorithm is used to calculate the POI weight,and then the POI weight and frequency density are calculated to identify the urban functional area,and establish the urban functional area transfer matrix,and analyze the temporal and spatial changes of the urban functional area.The research results show that:There is inconsistency in the weighting of various POIs based on public recognition.Using the TF-TDF algorithm to calculate the POI weights overcomes the excessive subjectivity of the traditional subjective assignment method,and the identification of urban functional areas is more accurate;The identification of urban functional areas based on grid cells is more accurate.From the perspective of time series,the proliferation and evolution of urban functional areas is more intuitive;From 2008 to 2018,the level of urbanization in Shanghai was relatively rapid,and the area without data dropped from 51.00%to 19.52%,and the number of industrial function zones has declined,and the number of commercial service and public function zones has increased significantly,which is consistent with the actual situation in Shanghai;this research can provide a reference for urban development planning and the rational layout of industrial structure.
作者 马强 王亮绪 吴昊圆 龚鑫 李卓勋 MA Qiang;WANG Liangxu;WU Haoyuan;GONG Xin;LI Zhuoxun(School of Environmental and Geographical Sciences,Shanghai Normal University,Shanghai 200234,China;Institute of Urban Development,Shanghai Normal University,Shanghai 200234,China)
出处 《地理信息世界》 2021年第4期16-22,共7页 Geomatics World
关键词 POI TF-IDF算法 城市功能区 转移矩阵 POI TF-IDF algorithm urban functional area land use transfer matrix
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