公交大数据时空特征的分布式计算及分析  

Distributed calculation and analysis of spatio-temporal characteristics of bus big data

作　　者：李卓航 张健钦 李泰增 陆浩 张安 LI Zhuohang;ZHANG Jianqin;LI Taizeng;LU Hao;ZHANG An(School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China;Key Laboratory of Urban Spatial Information, Ministry of Natural Resources, Beijing 102616, China)

机构地区：[1]北京建筑大学测绘与城市空间信息学院,北京102616 [2]自然资源部城市空间信息重点实验室,北京102616

出　　处：《北京测绘》2022年第6期741-745,共5页Beijing Surveying and Mapping

基　　金：国家自然科学基金(41771413);北京市自然科学基金(8202013)。

摘　　要：公交IC卡数据作为一种典型的出行大数据具有海量性、多样性、高速性和易变性的特征,传统数据库无法对其进行有效的存储和计算。该文采用Hadoop分布式技术对公交IC数据进行存储计算,分析了不同公交线路的客流时空特征,提出了基于属性层次模型(AHM)的逼近于理想值的排序方法对不同公交线路进行综合评价,利用网络地理信息系统(WebGIS)技术将计算结果进行集成,快速实时更新公众出行的特征,为公交供给的动态调整提供决策信息。As a typical travel big data,public transport IC card data has the characteristics of mass,diversity,high speed and variability.The traditional database can not effectively store and calculate it.This paper used Hadoop distributed technology to store and calculate the public transport IC data,analyzed the temporal and spatial characteristics of passenger flow of different public transport lines,and put forward TOPSIS method based on attribute AHM to comprehensively evaluate different public transport lines.At last,it integrated the calculation results with WebGIS technology,and updated the characteristics of public travel in real time,so as to provide decision-making information for the dynamic adjustment of public transport supply.

关 键 词：公交大数据 分布式技术 综合评价 属性层次模型 逼近理想值排序 网络地理信息系统 

分 类 号：P208[天文地球—地图制图学与地理信息工程]