基于手机信令数据的城市人群时空行为密度算法研究
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摘要
手机信令数据可以量化反映城市不同地段人群的时空分布状态,具有高取样率和高更新率的特点,对认知城市空间环境与人群行为模式的互动关系具有突出优势。针对手机信令既有处理计算的方法在数据结构和精确性方面的局限,将手机信令数据与城市空间形态数据相关联,提出基于三维活动空间的行为密度计算方法。以上海为案例,分别从时间维度和空间维度对上海公园绿地的手机用户时空分布进行计算,并结合调研实测对计算结果进行检验。结果表明该算法不仅可以实现城市绿地等具体景观地段的时空行为密度计算,同时也提升了中小尺度下基于手机数据进行个体行为密度计算的精确性,对于城市大数据应用于城市景观设计的方法创新具有一定的借鉴作用。
The mobile phone signaling data can quantify the spatial and temporal distribution of urban population, with high sampling rate and high update rate. It has outstanding advantages in the interaction between cognitive urban space environment and crowd behavior pattern. In response to the limitations of mobile phone signaling algorithms, in terms of data structure and accuracy, this study proposes a behavioral density calculation method based on three-dimensional active space, which associates mobile phone signaling data with urban spatial form data. Taking Shanghai as an example, the spatial and temporal distribution of mobile phone users in Shanghai park green space is calculated from the time dimension and the spatial dimension respectively, and the calculation results are tested in combination with the survey. The results show that the algorithm can not only calculate the temporal and spatial behavior density of specific landscape sections such as urban green space,but also improve the accuracy of individual behavioral density calculation based on mobile phone data at small and medium scales.This study has certain reference for the method innovation of urban big data applied to urban landscape design.
The mobile phone signaling data can quantify the spatial and temporal distribution of urban population, with high sampling rate and high update rate. It has outstanding advantages in the interaction between cognitive urban space environment and crowd behavior pattern. In response to the limitations of mobile phone signaling algorithms, in terms of data structure and accuracy, this study proposes a behavioral density calculation method based on three-dimensional active space, which associates mobile phone signaling data with urban spatial form data. Taking Shanghai as an example, the spatial and temporal distribution of mobile phone users in Shanghai park green space is calculated from the time dimension and the spatial dimension respectively, and the calculation results are tested in combination with the survey. The results show that the algorithm can not only calculate the temporal and spatial behavior density of specific landscape sections such as urban green space,but also improve the accuracy of individual behavioral density calculation based on mobile phone data at small and medium scales.This study has certain reference for the method innovation of urban big data applied to urban landscape design.
引文
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[2]Pulselli R,Ramono P,Ratti C,et al.Computing urban mobile landscapes through monitoring population density based on cellphone chatting[J].Int.J.of Design and Nature and Ecodynamics,2008,3(2):121-134.
[3]Reades J,Calabrese F,Sevtsuk A,et al.Cellular census:Explorations in urban data collection[J].IEEE Pervasive Computing,2007,6(3):32-38.
[4]Girardin F,Calabrese F,Fiore F D,et al.Digital footprinting:Uncovering tourists with usergenerated content[J].IEEE Pervasive Computing,2008,7(4):36-43.
[5]Girardin F,Vaccari A,Gerber A,et al.Quantifying urban attractiveness from the distribution and density of digital footprints[J].International Journal of Spatial Data Infrastructures Research,2009,4:175-200.
[6]Calabrese F,Pereira F C,Di Lorenzo G,et al.The geography of taste:analyzing cell-phone mobility and social events[C]//Floréen P,et al.International conference on pervasive computing.Berlin,Heidelberg:Springer,2010:22-37.
[7]Isaacman S,Becker R,Cáceres R,et al.Ranges of human mobility in Los Angeles and New York[C]//2011 IEEE International Conference on Pervasive Computing and Communications Workshops(PERCOM Workshops).IEEE,2011:88-93.
[8]钮心毅,丁亮,宋小冬.基于手机数据识别上海中心城的城市空间结构[J].城市规划学刊,2014(6):61-67.
[9]王德,王灿,谢栋灿,等.基于手机信令数据的上海市不同等级商业中心商圈的比较:以南京东路、五角场、鞍山路为例[J].城市规划学刊,2015(3):50-60.
[10]Louail T,Lenormand M,Ros O G C,et al.From mobile phone data to the spatial structure of cities[J].Scientific reports,2014,4:1-12.
[11]王德,钟炜菁,谢栋灿,等.手机信令数据在城市建成环境评价中的应用:以上海市宝山区为例[J].城市规划学刊,2015(5):82-90.
[12]杜国明,张树文,张有全.城市人口分布的空间自相关分析:以沈阳市为例[J].地理研究,2007,26(2):383-390.