Stephan Winter, Monika Sester, M. Tomko, Alexandra Millonig
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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.
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.