摘要
手机数据为人流视角下区域联系特征研究提供了重要的数据支撑。本文采用工作日、周末、节假日的中国联通手机数据,从联系类别和联系强度两个维度构建特征指标,通过机器学习算法探析区域联系特征。从联系类别来看,在重庆38个区县中,与环渝地区联系类别为游憩型的区县占比为66%,商务型占比为26%,混合型占比为8%;在环渝地区25个地级市中,与重庆联系类别为游憩型的区域占比为48%,商务型占比为32%,混合型占比为20%。从联系强度来看,重庆的门户城市和支点城市(渝北、合川、永川等)与四川的广安、泸州、达州等地级市与重庆均保持频繁人流联系。建议从推动重庆和成都优势互补、错位发展,加快建设成渝发展主轴,促进毗邻地区一体化融合发展等方面作出规划响应。
Mobile data provides important support for the study of regional connectivity characteristics from the perspective of human mobility.In this paper,the mobile phone data of China Unicom on weekdays,weekends and holidays are used to construct characteristic indicators in two dimensions:connectivity category and connectivity intensity,and to explore the characteristics of regional connectivity through machine learning algorithm.From the perspective of connectivity category,among the 38 districts and counties in Chongqing,66%of the connection category between Chongqing and the Chongqing Circle Area are categorized as leisure-oriented,26%as busniessoriented,and 8%as mixed-type.Among the 25 prefecture-level cities in the Chongqing Circle Area,48%of the areas with connectivity to Chongqing are leisure-oriented,32%are business-oriented,and 20%are mixed-type.From the perspective of connectivity intensity,gateway cities and pivot cities such as Yubei,Hechuan and Yongchuan in Chongqing,and prefecture-level cities such as Guang'an,Luzhou and Dazhou in Sichuan maintain frequent flow of people.It is suggested to make planning response in promoting the complementary and misplaced development of Chongqing and Chengdu,speeding up the construction of Chengdu-Chongqing development axis,and encouraging the integrated development of adjacent areas.
作者
李继珍
彭震宇
冷炳荣
王英
LI Jizhen;PENG Zhenyu;LENG Bingrong;WANG Ying
出处
《城乡规划》
2023年第1期85-95,共11页
Urban and Rural Planning
关键词
人流视角
手机信令数据
区域联系特征
机器学习
perspective of human mobility
mobile phone signaling data
regional connectivity characteristics
machine learning