{"title":"通过公交乘客的轨迹绘制城市地图:以澳大利亚布里斯班为例","authors":"Jiangping Zhou, J. Corcoran, Rosabella Borsellino","doi":"10.1177/0308518X17702647","DOIUrl":null,"url":null,"abstract":"Emerging non-traditional data (NTD) such as transit agencies' smartcard data and Google's General Transit Feed Specifications (GTFS) have made it easier to unveil the way in which public transit remains relevant, reveal how it facilitates daily mobility, and highlight the way in which different locales across a metropolitan area are connected by public transit. Based on a 24-h period of smartcard data for Brisbane (4 March 2014) allied with GTFS data, we retrieved 205,560 distinct transit riders' trip trajectories by direction (AM/inbound vs. PM/outbound) in Brisbane, Australia. It visualises the trajectories using a waterpark metaphor, in that, like water, people flow downhill.","PeriodicalId":11906,"journal":{"name":"Environment and Planning A","volume":"109 1","pages":"1707 - 1709"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Mapping cities by transit riders’ trajectories: The case of Brisbane, Australia\",\"authors\":\"Jiangping Zhou, J. Corcoran, Rosabella Borsellino\",\"doi\":\"10.1177/0308518X17702647\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emerging non-traditional data (NTD) such as transit agencies' smartcard data and Google's General Transit Feed Specifications (GTFS) have made it easier to unveil the way in which public transit remains relevant, reveal how it facilitates daily mobility, and highlight the way in which different locales across a metropolitan area are connected by public transit. Based on a 24-h period of smartcard data for Brisbane (4 March 2014) allied with GTFS data, we retrieved 205,560 distinct transit riders' trip trajectories by direction (AM/inbound vs. PM/outbound) in Brisbane, Australia. It visualises the trajectories using a waterpark metaphor, in that, like water, people flow downhill.\",\"PeriodicalId\":11906,\"journal\":{\"name\":\"Environment and Planning A\",\"volume\":\"109 1\",\"pages\":\"1707 - 1709\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environment and Planning A\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/0308518X17702647\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environment and Planning A","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/0308518X17702647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mapping cities by transit riders’ trajectories: The case of Brisbane, Australia
Emerging non-traditional data (NTD) such as transit agencies' smartcard data and Google's General Transit Feed Specifications (GTFS) have made it easier to unveil the way in which public transit remains relevant, reveal how it facilitates daily mobility, and highlight the way in which different locales across a metropolitan area are connected by public transit. Based on a 24-h period of smartcard data for Brisbane (4 March 2014) allied with GTFS data, we retrieved 205,560 distinct transit riders' trip trajectories by direction (AM/inbound vs. PM/outbound) in Brisbane, Australia. It visualises the trajectories using a waterpark metaphor, in that, like water, people flow downhill.
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