基于GIS平台的上海市菜鸟驿站空间特征分析

Spatial characteristics of Shanghai Cainiao station based on GIS

随着互联网经济和电商时代的到来,线下物流快速发展,但城镇“最后一公里”配送问题依旧存在,菜鸟驿站便应运而生。上海作为我国大型物流枢纽城市,探究其菜鸟驿站的空间特征及影响因素更具有代表性。研究基于上海市的菜鸟驿站POI(Point of Interest,兴趣点)数据,利用ArcGIS技术,综合运用空间自相关分析、缓冲区分析、核密度分析、标准差椭圆、近邻分析等空间分析与文本分析等方法,解析上海市菜鸟驿站的空间分布格局及影响因素。研究结果表明:上海市90%的菜鸟驿站分布于距离服务对象150 m的范围内,数量与服务对象设施最近出入点的距离成反比;受城市经济发展水平、人口数量、交通设施、生态环境、城市规划等因素影响,菜鸟驿站站点分布极其不均衡,大致呈南—北走向;菜鸟驿站站点在主城区和郊区分布呈现“多核心集聚模式”,两者分布差异较大;驿站站点的分布不均衡,与城市规划布局高度重合,其数量与城区人口数量、城市经济发展水平呈正相关。此研究结果可为上海市菜鸟驿站布局优化提供一定的参考。

With the advent of the internet economy and E-commerce era,offline logistics has developed rapidly,but the problem of"last kilometer"distribution in cities and towns still exists,and Cainiao station has emerged.As a large-scale logistics hub city in China,Shanghai is more representative to explore the spatial characteristics and influencing factors of the Cainiao station as the research object.Based on the POI(point of interest)data of Shanghai Cainiao station,this paper analyzes the spatial distribution pattern and influencing factors of Shanghai Cainiao station by using ArcGIS technology,spatial autocorrelation analysis,buffer analysis,kernel density analysis,standard deviation ellipse,nearest neighbor analysis and text analysis.In the whole study area,90%of Cainiao station in Shanghai is located within 150 m of the service objects,and the number is inversely proportional to the distance between the nearest entry and exit points of the service objects.Affected by the level of urban economic development,population,transportation facilities,ecological environment,urban planning and other factors,the distribution of Cainiao station is extremely uneven,roughly setting up in the south-north direction.The distribution of Cainiao station in the main urban area and the suburbs presents a"multi-core agglomeration mode",and there is a big difference between them.The distribution of Cainiao station is not balanced and highly coincides with the layout of urban planning.The number of Cainiao station is positively correlated with the urban population and urban economic development level.This research results can provide some reference for the layout optimization of Cainiao station in Shanghai.