利用时序手机通话数据识别城市用地功能

Urban Land Use Function Recognition Method Using Sequential Mobile Phone Data

  • 摘要: 城市土地利用是人的活动与城市物质空间交互所表现出的综合结果,因此人的活动与城市土地利用功能密切相关;具有不同时间段人的活动的空间聚集与分散规律的区域,其所属的社会功能属性亦不相同。随着大数据时代的到来,以居民手机数据为代表的基于位置的服务数据(local basic service,LBS)大量出现,使得实现时空全覆盖和精细化地监测城市人的活动成为可能。因此,利用手机数据的优势,能够实现从人的角度来区分识别城市用地功能类型。利用手机通话详单数据(call detail records,CDRs)提取面向地块尺度的居民通话聚合时序特征,提出了一种城市土地利用类型谱聚类识别方法。以武汉市为例进行实验分析,结果表明,该方法识别城市土地利用的平均精度为54.6%,为探知城市土地利用空间分布提供了一个有效的方法。

     

    Abstract: The spatial and temporal characteristics of human activities are closely related to the function of urban land use, so the social-economic function of the urban parcel can be inferred by the spatial aggregation and dispersion of human activities. Cell phone is the most popular communication terminal equipment and the distribution of cell phone users is able to reflect the distribution of population accurately. Local basic service (LBS), which is acquired from residents' cell mobile data, is constantly emerging and make it possible to achieve spatial and temporal coverage and meticulous monitoring of urban people's activities. Therefore, the mobility data of cell phone users have the potential to infer the land use function of the urban parcels. In this paper, the call detail records(CDRs), will be adopted to cluster the urban land use patterns. Firstly, the clustering characteristics of call aggregation for local scale are extracted, then a spectral clustering recognition method for urban land use is proposed. Taking Wuhan as an experimental area, the average accuracy of the method for urban land use identification is 54.6%, and the results show that this method has advantages in urban land use identification.

     

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