{"title":"微观尺度下建筑环境对地铁客流量的影响——以西安为例","authors":"Siyi Zhang, Yonggang Wang, Zixuan Liu, Jiazhuo Huang","doi":"10.1080/03081060.2023.2261508","DOIUrl":null,"url":null,"abstract":"ABSTRACTFew studies have examined the relationship at the microscopic spatial scale. In this study, multiple sources of data including mobile phone signal data, automatic fare collection system data, geo-information data, and street-view image data are combined to measure metro ridership and built environment at the plot or block scale. The Random Gradient Boosting Decision Tree was used to explore relationship between the built environment and ridership. The results show the following: (1) the relationship between built environment and ridership shows different types of curves. (2) The path distance to the metro station and the visual perception of road space have more significant impacts on ridership than road network density. (3) The location of the grid also affects grid-level metro ridership. The results suggest that planners should consider the locational factors, pay attention to the different effective thresholds of different variables on ridership and the longitudinal landscaping of non-motorized urban roads.KEYWORDS: Built environmentnon-motorized friendly designnon-linear relationshipmicroscopic spatial scale","PeriodicalId":23345,"journal":{"name":"Transportation Planning and Technology","volume":"17 1","pages":"0"},"PeriodicalIF":1.3000,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effects of built environment on metro ridership at a microscopic scale: a case study of Xi’an, China\",\"authors\":\"Siyi Zhang, Yonggang Wang, Zixuan Liu, Jiazhuo Huang\",\"doi\":\"10.1080/03081060.2023.2261508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTFew studies have examined the relationship at the microscopic spatial scale. In this study, multiple sources of data including mobile phone signal data, automatic fare collection system data, geo-information data, and street-view image data are combined to measure metro ridership and built environment at the plot or block scale. The Random Gradient Boosting Decision Tree was used to explore relationship between the built environment and ridership. The results show the following: (1) the relationship between built environment and ridership shows different types of curves. (2) The path distance to the metro station and the visual perception of road space have more significant impacts on ridership than road network density. (3) The location of the grid also affects grid-level metro ridership. The results suggest that planners should consider the locational factors, pay attention to the different effective thresholds of different variables on ridership and the longitudinal landscaping of non-motorized urban roads.KEYWORDS: Built environmentnon-motorized friendly designnon-linear relationshipmicroscopic spatial scale\",\"PeriodicalId\":23345,\"journal\":{\"name\":\"Transportation Planning and Technology\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Planning and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/03081060.2023.2261508\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"TRANSPORTATION SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Planning and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/03081060.2023.2261508","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Effects of built environment on metro ridership at a microscopic scale: a case study of Xi’an, China
ABSTRACTFew studies have examined the relationship at the microscopic spatial scale. In this study, multiple sources of data including mobile phone signal data, automatic fare collection system data, geo-information data, and street-view image data are combined to measure metro ridership and built environment at the plot or block scale. The Random Gradient Boosting Decision Tree was used to explore relationship between the built environment and ridership. The results show the following: (1) the relationship between built environment and ridership shows different types of curves. (2) The path distance to the metro station and the visual perception of road space have more significant impacts on ridership than road network density. (3) The location of the grid also affects grid-level metro ridership. The results suggest that planners should consider the locational factors, pay attention to the different effective thresholds of different variables on ridership and the longitudinal landscaping of non-motorized urban roads.KEYWORDS: Built environmentnon-motorized friendly designnon-linear relationshipmicroscopic spatial scale
期刊介绍:
Transportation Planning and Technology places considerable emphasis on the interface between transportation planning and technology, economics, land use planning and policy.
The Editor welcomes submissions covering, but not limited to, topics such as:
• transport demand
• land use forecasting
• economic evaluation and its relationship to policy in both developed and developing countries
• conventional and possibly unconventional future systems technology
• urban and interurban transport terminals and interchanges
• environmental aspects associated with transport (particularly those relating to climate change resilience and adaptation).
The journal also welcomes technical papers of a more narrow focus as well as in-depth state-of-the-art papers. State-of-the-art papers should address transport topics that have a strong empirical base and contain explanatory research results that fit well with the core aims and scope of the journal.