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手机信令数据在职住空间、出行行为和交通碳排放研究中的应用进展与前景

高瑜堃 赵鹏军

热带地理2024,Vol.44Issue(5):877-890,14.
热带地理2024,Vol.44Issue(5):877-890,14.DOI:10.13284/j.cnki.rddl.003872

手机信令数据在职住空间、出行行为和交通碳排放研究中的应用进展与前景

A Review on the Application Progress and Prospect of Mobile Phone Signaling Data in Jobs-Housing Relationship,Travel Behavior and Transportation Carbon Emissions Research

高瑜堃 1赵鹏军2

作者信息

  • 1. 北京大学 城市与环境学院,北京 100871
  • 2. 北京大学 城市与环境学院,北京 100871||北京大学深圳研究生院 城市规划与设计学院,广东 深圳 518055
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摘要

Abstract

The rapid development of information technology has triggered an explosion of data,marking the era of big data.A wide range of transportation big data has been used in urban space and travel behavior studies since the beginning of this century.Mobile phone signaling data in particular have many advantages:they have prevalent spatial and temporal coverage,high tracking stability,satisfactory resolution,and low cost.The description of urban phenomena and the analysis of their forming mechanisms using mobile phone signaling data are thoroughly studied by previous research.The next course of action is to tackle specific urban problems.This study summarizes the application progress of mobile phone signaling data in job-housing relationships and travel behavior studies,discusses the application prospects of mobile phone signaling data in transportation carbon emissions research based on past applications and the existing literature on low-carbon transportation,and proposes a research framework and several future directions for studies using mobile phone big data to examine job-housing relationships,travel behavior,and transportation carbon emissions.We first provide a brief introduction to the features of mobile phone signaling data in comparison with other commonly used data types,including their type,content,and spatial-temporal resolution.We then review the existing applications in job housing and travel research.Regarding the jobs-housing relationship,prior studies employ mobile phone signaling data to detect the spatial distribution of workplaces and residences of urban dwellers,analyze jobs-housing relationship features and urban spatial structure characteristics,and examine the factors influencing jobs-housing relationships.Regarding travel behavior,studies employ mobile phone signaling data to identify stays and trips,infer trip modes,detect trip routes,and explore the universal laws of human mobility.Next,we also discuss how mobile phone signaling data can be applied to transportation carbon emissions research.Indeed,mobile phone signaling data can be used in the calculation of transportation carbon emissions and analysis of the relationships between urban spatial structure,individual travel behavior,and transportation carbon emissions,and its wide coverage and large sample size can be exploited to fill research gaps and problems that have yet to be resolved using traditional traffic datasets.Finally,we present a research framework underlining the indirect and direct effects of the jobs-housing relationship and travel behavior on transportation carbon emissions.We also propose future directions in study contents and methodological innovations by recommending long time-series longitudinal studies,large-scale comparative studies,and new population and transportation phenomena.We further recommend fusing multi-source big and small data,incorporating machine learning algorithms into traditional statistical analyses,and constructing digital twin models.Examining the jobs-housing relationship,travel behavior,and transport carbon emissions using mobile phone signaling data is essential for clarifying the interactions between urban and regional structures,travel behavior characteristics,and transport carbon emissions.It has important implications for emissions reduction and sustainable development in the context of proposing carbon peaking and carbon neutrality goals.

关键词

手机信令数据/职住空间关系/交通出行行为/交通碳排放

Key words

mobile phone signaling data/jobs-housing relationship/travel behavior/transportation carbon emissions

分类

交通工程

引用本文复制引用

高瑜堃,赵鹏军..手机信令数据在职住空间、出行行为和交通碳排放研究中的应用进展与前景[J].热带地理,2024,44(5):877-890,14.

基金项目

国家自然科学基金项目(41925003、42130402) (41925003、42130402)

深圳市科技计划资助项目(JCYJ20220818100810024) (JCYJ20220818100810024)

热带地理

OA北大核心CSTPCD

1001-5221

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