Hadoop-based spatio-temporal analysis of urban public transportation big data

被引：0
|
作者：
Ni, Yan [1 ]
Huang, Yijie [1 ]
Li, Aidi [2 ]
Zhang, Jianqin [2 ]
Ding, Ying [2 ]
Zhao, Ming [2 ]
机构：
[1] Minist Transport PRC, Highway Monitoring & Response Ctr, Beijing 100088, Peoples R China
[2] Beijing Univ Civil Engn & Architecture, Sch Geomat & Urban Spatial Informat, Beijing, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON INTELLIGENT TRAFFIC SYSTEMS AND SMART CITY (ITSSC 2021) | 2022年 / 12165卷
关键词：
Urban traffic big data; Hadoop; WebGIS; spatio-temporal big data mining;
D O I：
10.1117/12.2627788
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Big data of urban public transportation contains rich spatial and temporal information, which is the data basis for passenger travel characteristics analysis and evaluation of urban transportation service capacity. In this paper, we take the big data of Beijing bus swipe card and taxi track as the research object, store and calculate these two types of big data based on Hadoop distributed system, build the calculation model of passenger flow extraction, extract the hot ride areas and establish the visualization system based on WebGIS for the visual expression of data analysis results.
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页数：7
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