Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Upscaling urban data science for global climate solutions
Show others and affiliations
2019 (English)In: Global Sustainability, E-ISSN 2059-4798, Vol. 2, article id e2Article in journal (Refereed) Published
Abstract [en]

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. Technical summary Cities have an increasingly integral role in addressing climate change. To gain a common understanding of solutions, we require adequate and representative data of urban areas, including data on related greenhouse gas emissions, climate threats and of socio-economic contexts. Here, we review the current state of urban data science in the context of climate change, investigating the contribution of urban metabolism studies, remote sensing, big data approaches, urban economics, urban climate and weather studies. We outline three routes for upscaling urban data science for global climate solutions: 1) Mainstreaming and harmonizing data collection in cities worldwide; 2) Exploiting big data and machine learning to scale solutions while maintaining privacy; 3) Applying computational techniques and data science methods to analyse published qualitative information for the systematization and understanding of first-order climate effects and solutions. Collaborative efforts towards a joint data platform and integrated urban services would provide the quantitative foundations of the emerging global urban sustainability science.

Place, publisher, year, edition, pages
2019. Vol. 2, article id e2
Keywords [en]
adaptation and mitigation, policies, politics and governance, urban systems
National Category
Other Social Sciences Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-178201DOI: 10.1017/sus.2018.16Scopus ID: 2-s2.0-85065259536OAI: oai:DiVA.org:su-178201DiVA, id: diva2:1387192
Available from: 2020-01-20 Created: 2020-01-20 Last updated: 2020-01-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
McPhearson, Timon
By organisation
Stockholm Resilience Centre
Other Social SciencesEarth and Related Environmental Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf