Upscaling urban data science for global climate solutions
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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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The advent of big data, robotics, and augmented computer capabilities offer the unprecedented ability to collect, analyze, and synthesize vast amounts of environmental, social, and climatic data to drive context appropriate urban NbS applications.
“The advent of big data, robotics, and augmented computer capabilities offer the unprecedented ability to collect, analyze, and synthesize vast amounts of environmental, social, and climatic data to drive context appropriate urban NbS applications (127, 128).”
From Global synthesis and regional insights for mainstreaming urban nature-based solutions (2025) · cites this paper as [127]
Section 2.3 describes combining social, biophysical and climate-related urban data to improve city-scale decisions. The “Applications include” section discusses advanced analytics for planning and names urban greening among potential applications. The copy does not support the claim about robotics or specifically establish that these capabilities drive context-appropriate urban nature-based solutions. (LLM, conf=0.86)
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Frantzeskaki, N., McPhearson, T., Collier, M. J., Kendal, D., Bulkeley, H., Dumitru, A., Walsh, C., Noble, K., van Wyk, E., Ordóñez, C., et al. (2019) · BioScience · doi:10.1093/biosci/biz042 · Cited by 559 · see citing works
Self-citationArtificial intelligence, systemic risks, and sustainability
Galaz, V., Centeno, M. A., Callahan, P. W., Causevic, A., Patterson, T., Brass, I., Baum, S., Farber, D., Fischer, J., Garcia, D., et al. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101741 · Cited by 497 · see citing works
Self-citationLearning about urban climate solutions from case studies
Lamb, W. F., Creutzig, F., Callaghan, M. W., & Minx, J. C. (2019) · Nature Climate Change · doi:10.1038/s41558-019-0440-x · Cited by 163 · see citing works
Self-citationDigitalization and the Anthropocene
Creutzig, F., Acemoglu, D., Bai, X., Edwards, P. N., Hintz, M. J., Kaack, L. H., Kilkis, S., Kunkel, S., Luers, A., Milojevic-Dupont, N., et al. (2022) · Annual Review of Environment and Resources · doi:10.1146/annurev-environ-120920-100056 · Cited by 112 · see citing works
Self-citationLearning from urban form to predict building heights
Milojevic-Dupont, N., Hans, N., Kaack, L. H., Zumwald, M., Andrieux, F., de Barros Soares, D., Lohrey, S., Pichler, P.-P., & Creutzig, F. (2020) · PLOS ONE · doi:10.1371/journal.pone.0242010 · Cited by 93 · see citing works
Self-citationGlobal synthesis and regional insights for mainstreaming urban nature-based solutions
McPhearson, T., Frantzeskaki, N., Ossola, A., Diep, L., Anderson, P. M. L., Blatch, T., Collier, M. J., Cook, E. M., Culwick Fatti, C., Grabowski, Z. J., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2315910121 · Cited by 47 · see citing works
Self-citation
- Authors
- Creutzig, F., Lohrey, S., Bai, X., Baklanov, A., Dawson, R., Dhakal, S., Lamb, W. F., McPhearson, T., Minx, J., Munoz, E., & Walsh, B.
- Affiliations
- Mercator Research Institute on Global Commons and Climate Change (DE)
- Technische Universität Berlin (DE)
- Australian National University (AU)
- World Meteorological Organization (CH)
- Newcastle University (GB)
- Asian Institute of Technology (TH)
- The New School (US)
- Future Earth (CA)
- Corresponding author
- Creutzig, Felix
- ORCID
- Venue
- Global Sustainability
- Publisher
- Cambridge University Press (CUP)
- Published
- 2019
- Volume
- 2
- ISSN
- 2059-4798 (ISSN-L)
- OpenAlex
- W2912140230
- Cited by
- 137
- References
- 218
- Citations by year
- 2026: 14 · 2025: 16 · 2024: 17 · 2023: 15 · 2022: 20 · 2021: 22 · 2020: 19 · 2019: 12 · 2018: 2
- FWCI
- 12.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Global Sustainability (publishedVersion, cc-by-nc-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Publication Database PIK (Potsdam Institute for Climate Impact Research (PIK)) (submittedVersion)
- Funders
- Engineering and Physical Sciences Research Council (EP/H003630/1, EP/P016782/1)
- Topics
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Sustainable Development
- Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
- Keywords
- urban climate adaptation, greenhouse gas emissions reduction, data infrastructure, Earth observation data, social media data, big data, qualitative data analysis, scalability, global cities, data integration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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