{"title":"OD-Wheel: Visual design to explore OD patterns of a central region","authors":"Min Lu, Zuchao Wang, Jie Liang, Xiaoru Yuan","doi":"10.1109/PACIFICVIS.2015.7156361","DOIUrl":null,"url":null,"abstract":"Understanding the Origin-Destination (OD) patterns between different regions of a city is important in urban planning. In this work, based on taxi GPS data, we propose OD-Wheel, a novel visual design and associated analysis tool, to explore OD patterns. Once users define a region, all taxi trips starting from or ending to that region are selected and grouped into OD clusters. With a hybrid circular-linear visual design, OD-Wheel allows users to explore the dynamic patterns of each OD cluster, including the variation of traffic flow volume and traveling time. The proposed tool supports convenient interactions and allows users to compare and correlate the patterns between different OD clusters. A use study with real data sets demonstrates the effectiveness of the proposed OD-Wheel.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Pacific Visualization Symposium (PacificVis)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIFICVIS.2015.7156361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24
Abstract
Understanding the Origin-Destination (OD) patterns between different regions of a city is important in urban planning. In this work, based on taxi GPS data, we propose OD-Wheel, a novel visual design and associated analysis tool, to explore OD patterns. Once users define a region, all taxi trips starting from or ending to that region are selected and grouped into OD clusters. With a hybrid circular-linear visual design, OD-Wheel allows users to explore the dynamic patterns of each OD cluster, including the variation of traffic flow volume and traveling time. The proposed tool supports convenient interactions and allows users to compare and correlate the patterns between different OD clusters. A use study with real data sets demonstrates the effectiveness of the proposed OD-Wheel.