Upscaling urban data science for global climate solutions

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Standard

Upscaling urban data science for global climate solutions. / Creutzig, Felix; Lohrey, Steffen; Bai, Xuemei; Baklanov, Alexander; Dawson, Richard; Dhakal, Shobhakar; Lamb, William F.; McPhearson, Timon; Minx, Jan; Munoz, Esteban; Walsh, Brenna.

I: Global Sustainability, Bind 2, e2, 01.01.2019.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Creutzig, F, Lohrey, S, Bai, X, Baklanov, A, Dawson, R, Dhakal, S, Lamb, WF, McPhearson, T, Minx, J, Munoz, E & Walsh, B 2019, 'Upscaling urban data science for global climate solutions', Global Sustainability, bind 2, e2. https://doi.org/10.1017/sus.2018.16

APA

Creutzig, F., Lohrey, S., Bai, X., Baklanov, A., Dawson, R., Dhakal, S., Lamb, W. F., McPhearson, T., Minx, J., Munoz, E., & Walsh, B. (2019). Upscaling urban data science for global climate solutions. Global Sustainability, 2, [e2]. https://doi.org/10.1017/sus.2018.16

Vancouver

Creutzig F, Lohrey S, Bai X, Baklanov A, Dawson R, Dhakal S o.a. Upscaling urban data science for global climate solutions. Global Sustainability. 2019 jan 1;2. e2. https://doi.org/10.1017/sus.2018.16

Author

Creutzig, Felix ; Lohrey, Steffen ; Bai, Xuemei ; Baklanov, Alexander ; Dawson, Richard ; Dhakal, Shobhakar ; Lamb, William F. ; McPhearson, Timon ; Minx, Jan ; Munoz, Esteban ; Walsh, Brenna. / Upscaling urban data science for global climate solutions. I: Global Sustainability. 2019 ; Bind 2.

Bibtex

@article{6256d3e9a65f41d3b8dcea021a7cb033,
title = "Upscaling urban data science for global climate solutions",
abstract = "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.",
keywords = "adaptation and mitigation, policies, politics and governance, urban systems",
author = "Felix Creutzig and Steffen Lohrey and Xuemei Bai and Alexander Baklanov and Richard Dawson and Shobhakar Dhakal and Lamb, {William F.} and Timon McPhearson and Jan Minx and Esteban Munoz and Brenna Walsh",
year = "2019",
month = jan,
day = "1",
doi = "10.1017/sus.2018.16",
language = "English",
volume = "2",
journal = "Global Sustainability",
issn = "2059-4798",
publisher = "Cambridge University Press",

}

RIS

TY - JOUR

T1 - Upscaling urban data science for global climate solutions

AU - Creutzig, Felix

AU - Lohrey, Steffen

AU - Bai, Xuemei

AU - Baklanov, Alexander

AU - Dawson, Richard

AU - Dhakal, Shobhakar

AU - Lamb, William F.

AU - McPhearson, Timon

AU - Minx, Jan

AU - Munoz, Esteban

AU - Walsh, Brenna

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - adaptation and mitigation

KW - policies

KW - politics and governance

KW - urban systems

UR - http://www.scopus.com/inward/record.url?scp=85065259536&partnerID=8YFLogxK

U2 - 10.1017/sus.2018.16

DO - 10.1017/sus.2018.16

M3 - Journal article

AN - SCOPUS:85065259536

VL - 2

JO - Global Sustainability

JF - Global Sustainability

SN - 2059-4798

M1 - e2

ER -

ID: 230995979