摘要
利用手机信令数据,借助Python语言编程和GIS对天津市小白楼CBD片区的人员规模变化趋势、分地块人数极值时空分布、驻留与流动人员时空分布进行了分析.结果显示:区域人员规模遵循“平稳降低(0:00-4:00)-快速升高(5:00-8:00)-平稳升高(9:00-17:00)-快速降低(19:00-23:00)”总体变化趋势;在720个时间段内,6:00—18:00时间段出现人数最大值地块的数量占比达到87.91%,超过95%的地块在晚间出现人数最小值,其中在1:00出现的人数最小值地块数量最多;驻留、流动人员数量的变化趋势呈现出白天和夜间的总规模略有变化但相对较平缓,全天的流动人员规模远大于驻留人员规模,白天的流动人员规模远大于夜间流动人员规模,夜间驻留人员规模大于白天驻留人员规模等显著特征。
Based on mobile phone data,the Python language and GIS were used to analyze the trend of total population size,the spatial and temporal distribution of the extreme values of the populationin specific plots,and the spatial and temporal distribution of the residential and floating populations in Xiaobailou CBD area in Tianjin.The results showed that:Firstly,the regional population size followed an overall change trend of“stable reduction(0:00-4:00)-rapid increase(5:00-8:00)-a steady increase(9:00-17:00)-rapid reduction(19=00-23=00)”.Secondly,in the 720 time period,the plots which had the largest population during 6=00-18=00 period account for 87.91%,and over 95%of the plots had the lowest number of people in the evening,and the number of plots that appeared at 1=00 was the largest.Thirdly,the trend of the number of residents and floating population showed the following characteristics:The total size of daytime and nighttime changed slightly but relatively flat,the size of the floating population throughout the day was much larger than the size of the residential population,the size of the floating population during the day was much larger than that of the nighttime,he size of the residential population at night was greater than that of the daytime.
作者
陈伟
翟国方
张义杰
CHEN Wei;ZHAI Guo-fang;ZHANG Yi-jie(School of Geographic and Biologic Information,Nanjing University of Posts and Telecommunications,Nanjing 210046,China;School of Architecture and Urban Planning,Nanjing University,Nanjing 210093 ,China;School of Business Administration,Nanjing University of Finance and Economics,Nanjing 210046,China)
出处
《资源开发与市场》
CAS
2019年第10期1266-1272,共7页
Resource Development & Market
基金
国家自然科学基金项目(编号:41601139)
关键词
手机信令数据
人口时空分布
高精度
PYTHON语言
mobile phone data
spatial and temporal distribution of population
high-precision
Python language
