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Upscaling urban data science for global climate solutions

  • Felix Creutzig (a1) (a2), Steffen Lohrey (a2), Xuemei Bai (a3), Alexander Baklanov (a4), Richard Dawson (a5), Shobhakar Dhakal (a6), William F. Lamb (a1), Timon McPhearson (a7) (a8) (a9), Jan Minx (a1), Esteban Munoz (a10) and Brenna Walsh (a11)...
Non-technical summary

Manhattan, Berlin and New Delhi all need to take action to adapt to climate change and to reduce greenhouse gas emissions. While case studies on these cities provide valuable insights, comparability and scalability remain sidelined. It is therefore timely to review the state-of-the-art in data infrastructures, including earth observations, social media data, and how they could be better integrated to advance climate change science in cities and urban areas. We present three routes for expanding knowledge on global urban areas: mainstreaming data collections, amplifying the use of big data and taking further advantage of computational methods to analyse qualitative data to gain new insights. These data-based approaches have the potential to upscale urban climate solutions and effect change at the global scale.

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Corresponding author
Author for correspondence: F. Creutzig, E-mail: creutzig@mcc-berlin.net
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