气候中和城市交通数据分析的挑战(远景规划论文)

IF 1.2 Q4 REMOTE SENSING ACM Transactions on Spatial Algorithms and Systems Pub Date : 2024-02-23 DOI:10.1145/3649312
Stephan Winter, Monika Sester, M. Tomko, Alexandra Millonig
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引用次数: 0

摘要

城市交通是人类引起气候变化的主要因素,城市与交通规划和空间计算学术界一直在积极应对这一挑战。然而,我们在本文中认为,对原本不可持续的城市交通系统进行增量效率改进的普通数据分析研究永远无法帮助实现气候中和--《巴黎协定》规定我们必须在 2050 年之前实现的目标。数据分析在城市交通某一环节的改进通常会给其他环节带来意想不到的、往往是不利的后果,这一观察结果加剧了这一必要性。在这份愿景文件中,我们主张将数据分析议程作为城市交通研究的核心,以推进气候行动。这一议程必须颠覆我们的思维和运作方式,就像它正在颠覆城市中的社会无障碍问题一样。
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The Challenge of Data Analytics with Climate-Neutral Urban Mobility (Vision Paper)
Urban mobility is a major contributor to human-induced climate change, a challenge that urban and transport planning and spatial computing academic communities have been actively addressing. In this paper we argue, however, that the common data analytics research into incremental efficiency improvements of originally non-sustainable urban mobility systems will never be able to help reach climate neutrality – the goal we must achieve by 2050 as per the Paris Agreement. This imperative is exacerbated by the observation that improvements, by data analytics, in one segment of urban mobility typically have unintended and often adverse consequences in other segments. In this vision paper we argue for a data analytics agenda to advance climate action at the core of urban mobility research. This agenda must disrupt the way we think and operate, as much as it is disrupting the accessibility issues of society in cities.
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来源期刊
CiteScore
4.40
自引率
5.30%
发文量
43
期刊介绍: ACM Transactions on Spatial Algorithms and Systems (TSAS) is a scholarly journal that publishes the highest quality papers on all aspects of spatial algorithms and systems and closely related disciplines. It has a multi-disciplinary perspective in that it spans a large number of areas where spatial data is manipulated or visualized (regardless of how it is specified - i.e., geometrically or textually) such as geography, geographic information systems (GIS), geospatial and spatiotemporal databases, spatial and metric indexing, location-based services, web-based spatial applications, geographic information retrieval (GIR), spatial reasoning and mining, security and privacy, as well as the related visual computing areas of computer graphics, computer vision, geometric modeling, and visualization where the spatial, geospatial, and spatiotemporal data is central.
期刊最新文献
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