Portrait Analysis of Rail Transit Stations Based on PAM Clustering
Based on multi-source data fusion,this paper extracts and constructs the characteristics of rail stations from four dimensions:passenger flow level,resident demand,connection characteristics,and surrounding facilities.The PAM algorithm was used to study the clustering of the sites,and finally the labels of six types of site portraits were formed.On this basis,the internal relationship between the functional positioning of stations and passenger flow patterns is explored,and the phased contradictions faced by different types of stations in the process of urbanization are sorted out,so as to provide guidance for follow-up research such as passenger flow prediction and drainage measures.
multi-source dataportrait analysis of rail transit stationsPAM clustering
NETL
NSTL
万方数据
