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基于POI数据城市快递自取点的空间特征分析——以郑州菜鸟驿站为例 被引量:8

Analysis on Spatial Characteristics of Urban Express Pickup Points based on POI Data--Take Cainiao Station in Zhengzhou as an Example
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摘要 为了优化郑州市菜鸟驿站的空间布局,进一步提高城市物流配送效率和提升物流服务的满意度.基于ArcGIS工具对郑州市的菜鸟驿站POI数据进行空间分析,解析郑州市菜鸟驿站的分布特征及其影响因素.研究结果表明:郑州市菜鸟驿站的分布受到人口密度、交通网络以及城市居民消费水平等因素的影响,其中77.7%的菜鸟驿站主要集中在人口密集且经济发展较好的金水区、中原区、二七区以及管城回族区等中心城区,并且距离社区和中心城区较远的菜鸟驿站数量逐渐递减且呈分散分布;总体上来说,郑州市菜鸟驿站的空间分布呈现出中间密集四周稀疏的不均衡特征,表现出较强的多核心聚集模式. In order to optimize the space layout of Cainiao courier station in Zhengzhou,we will improve Cainiaocourier station’s urban logistics distribution efficiency and satisfaction with logistics services.Based on ArcGIS tool and POI data,we analyzed spatial distribution characteristics and its influencing factors of Cainiao courier stations in Zhengzhou city.The research results show that in Zhengzhou city,the influencing factors of Cainiao courier station include population density,traffic network and consumption level of urban residents,77.7%of them are mainly concentrated in the densely populated and economically developed central urban areas such as Jinshui,Zhongyuan,Erqi and Guancheng.The farther the Cainiao courier station is from the community and the city center,the fewer the stations are and the stations are dispersed.In general,the spatial distribution of Cainiao courier stations present an unbalanced density in the middle and sparsely around,showing a strong multi-core clustering pattern in Zhengzhou city.
作者 隋晓丽 吕阳阳 张曼 虞亚楠 SUI Xiaoli;LYU Yangyang;ZHANG Man;YU Ya’nan(College of Urban and Environmental Sciences,Xuchang University,Xuchang 461000,China;College of Marine Sciences,Shanghai Ocean University,Shanghai 201306,China;Department of Agricultural Information Engineering,Shanghai Vocational College of Agriculture and Forestry,Shanghai 201699,China)
出处 《许昌学院学报》 CAS 2021年第5期30-34,共5页 Journal of Xuchang University
基金 河南省高校人文社会科学研究一般项目(2021-ZZJH-351,2020-ZZJH-426,21A170019)。
关键词 郑州市 菜鸟驿站 空间分析 POI 影响因素 Zhengzhou Cainiao courier station spatial analysis POI influencing factor
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