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Monitoring trucks to reveal Belgian geographical structures and dynamics: From GPS traces to spatial interactions

卡车 全球定位系统 互连性 地理 运输工程 区域科学 大数据 运筹学 计算机科学 工程类 数据挖掘 电信 航空航天工程 人工智能
作者
Arnaud Adam,Olivier Finance,Isabelle Thomas
出处
期刊:Journal of Transport Geography [Elsevier BV]
卷期号:91: 102977-102977 被引量:18
标识
DOI:10.1016/j.jtrangeo.2021.102977
摘要

Abstract Despite the fact that freight transport has a huge impact on the economy and the environment, Belgian datasets have always been scarce or restricted to very small a-spatial samples. Spatial data collected in Belgium for toll-paying trucks are here examined, and geographical structures and dynamics are extracted from this massive dataset. The originality of this dataset is its exhaustivity and its real-time approach: the location of all the trucks circulating in Belgium is collected every 30 s. The paper first relates to the methodology applied when using and transforming big data generated by On Board Units GNSS (cleaning, transforming and pre-processing). Second, it maps and comments on the movements (traffic) and stops of trucks within the whole country, providing a clear picture of the Belgian situation, useful for regional planners and logistics companies. Finally, the flows of trucks observed between Belgian locations enable the country to be divided into mathematical communities of places that interact the most. Analyses are performed for sub-categories based on the country of registration, underlining the spatial specificities of freight transit in Belgium. This exploratory spatial data analysis enables to reveal not only multi-level spatial structures associated with urban hierarchies and the transport infrastructure, but also firm locations or political organizations and to consider the complexity and interconnectivity of any measure taken for a more sustainable future. With a clear methodological framework to cope with the data pre-processing, this paper opens the way to various potential applications linked with freight transportation in Belgium.
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