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TypeJournal Article
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Published in
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Year2019
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Author(s)
Creutzig, Felix; Lohrey, Steffen; Bai, Xuemei; Baklanov, Alexander; Dawson, Richard; Dhakal, Shobhakar; Lamb, William F.; McPhearson, Timon; Minx, Jan; Munoz, Esteban; Walsh, Brenna -
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ID
2793
Upscaling urban data science for global climate solutions
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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