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This perspective paper highlights the potentials, limitations, and combinations of openly available Earth observation (EO) data and big data in the context of environmental research in urban areas. The aim is to build the resilience of informal settlements to climate change impacts. In particular, it highlights the types, categories, spatial and temporal scales of publicly available big data. The benefits of publicly available big data become clear when looking at issues such as the development and quality of life in informal settlements within and around major African cities. Sub-Saharan African (SSA) cities are among the fastest growing urban areas in the world. However, they lack spatial information to guide urban planning towards climate-adapted cities and fair living conditions for disadvantaged residents who mostly reside in informal settlements. Therefore, this study collected key information on freely available data such as data on land cover, land use, and environmental hazards and pressures, demographic and socio-economic indicators for urban areas. They serve as a vital resource for success of many other related local studies, such as the transdisciplinary research project “DREAMS—Developing REsilient African cities and their urban environMent facing the provision of essential urban SDGs”. In the era of exponential growth of big data analytics, especially geospatial data, their utility in SSA is hampered by the disparate nature of these datasets due to the lack of a comprehensive overview of where and how to access them. This paper aims to provide transparency in this regard as well as a resource to access such datasets. Although the limitations of such big data are also discussed, their usefulness in assessing environmental hazards and human exposure, especially to climate change impacts, are emphasised.
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Upscaling urban data science for global climate solutions
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.
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- Award ID(s):
- 1737626
- PAR ID:
- 10110651
- Date Published:
- Journal Name:
- Global Sustainability
- Volume:
- 2
- ISSN:
- 2059-4798
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1017/sus.2018.16
