基于大数据的零售业空间热点识别及人口分布特征分析——以厦门市为例

Analysis on Hotspots Identification and Population Distribution Characteristics of Retails Spatial Based on Big Data--A Case Study of Xiamen,China

城市零售业的布局对合理配置资源、满足居民的消费需求、提高城市活力起着重要作用,它也是城乡规划学等学科的重点关注领域。本文以厦门市为例,首先基于POI大数据,采用ArcGIS空间分析对零售业进行空间热点识别,分析厦门市零售业空间热点集聚特征;再基于人口数据分析常住人口分布特征,基于宜出行大数据采用核密度分析与栅格计算获得人群集聚特征,并通过对比分析厦门市零售业空间冷热点与人口分布特征的匹配程度,发现厦门市零售业设施配置不足的情况,以期优化厦门市零售业布局。

The layout of urban retail industry plays an important role in the rational allocation of resources,meeting the consumer demands of residents,and improving the vitality of the city.It is also the focus of urban and rural planning and other disciplines.This paper takes Xiamen as an example.Firstly,based on POI big data,ArcGIS spatial analysis is used to identify the retail’s spatial hotspots and analyze the clustering characteristics of the retail’s spatial hotspots in Xiamen.Then,based on the population data,analyze the distribution characteristics of permanent residents,and adopt nuclear density analysis and raster calculation to analyze the clustering characteristics of the population based on the Easygo big data.In addition,the matching degree between the retail’s spatial cold hot spot and the population distribution characteristics is compared and analyzed to find out the insufficiency of the retail facilities configuration in Xiamen,so as to optimize the retail layout of Xiamen.