Sustainable city planning: a data-driven approach for mitigating urban heat
Sustainable city planning: a data-driven approach for mitigating urban heat
Urban areas are expected to triple by 2030 in order to accommodate 60% of the global population. Anthropogenic landscape modifications expand coverage of impervious surfaces inducing the urban heat island (UHI) effect, a critical twenty first century challenge associated with increased economic expenditure, energy consumption, and adverse health impacts. Yet, omission of UHI measures from global climate models and metropolitan planning methodologies precludes effective sustainable development governance. We present an approach that integrates Earth observation and climate data with three-dimensional urban models to determine optimal tree placement (per square meter) within proposed urban developments to enable more effective localized UHI mitigation. Such data-driven planning decisions will enhance the future sustainability of our cities to align with current global urban development agendas.
REMOTE SENSING, urban heat island
MacLachlan, Andrew Charles
7256882c-d3c7-4bd9-99e7-e2a5e4b5ed75
Biggs, Eloise
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Roberts, Gareth
fa1fc728-44bf-4dc2-8a66-166034093ef2
Boruff, Brian
33d82cd5-8ad6-4ac1-b05f-3fa43ed78d0e
26 January 2021
MacLachlan, Andrew Charles
7256882c-d3c7-4bd9-99e7-e2a5e4b5ed75
Biggs, Eloise
f0afed06-18ac-4a4d-841c-36ea4ff8a3b4
Roberts, Gareth
fa1fc728-44bf-4dc2-8a66-166034093ef2
Boruff, Brian
33d82cd5-8ad6-4ac1-b05f-3fa43ed78d0e
MacLachlan, Andrew Charles, Biggs, Eloise, Roberts, Gareth and Boruff, Brian
(2021)
Sustainable city planning: a data-driven approach for mitigating urban heat.
Frontiers in Built Environment, 6, [519599].
(doi:10.3389/fbuil.2020.519599).
Abstract
Urban areas are expected to triple by 2030 in order to accommodate 60% of the global population. Anthropogenic landscape modifications expand coverage of impervious surfaces inducing the urban heat island (UHI) effect, a critical twenty first century challenge associated with increased economic expenditure, energy consumption, and adverse health impacts. Yet, omission of UHI measures from global climate models and metropolitan planning methodologies precludes effective sustainable development governance. We present an approach that integrates Earth observation and climate data with three-dimensional urban models to determine optimal tree placement (per square meter) within proposed urban developments to enable more effective localized UHI mitigation. Such data-driven planning decisions will enhance the future sustainability of our cities to align with current global urban development agendas.
Text
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- Accepted Manuscript
More information
Accepted/In Press date: 3 November 2020
e-pub ahead of print date: 26 December 2020
Published date: 26 January 2021
Additional Information:
Funding Information:
We would like to thank Mayor Brad Pettitt, Paul Garbett, Marcel Maron, and Gavin Giles from the City of Fremantle for operational planning insights. Access to Urban Monitor high-resolution data was provided in part through the National Environmental Science Program, Clean Air, and Urban Landscapes Hub. Funding. This work was supported by the Economic and Social Research Council (grant number ES/J500161/1) with funding support from the University of Southampton via the World University Network (WUN) researcher mobility programme.
Publisher Copyright:
© Copyright © 2021 MacLachlan, Biggs, Roberts and Boruff.
Keywords:
REMOTE SENSING, urban heat island
Identifiers
Local EPrints ID: 447717
URI: http://eprints.soton.ac.uk/id/eprint/447717
PURE UUID: 65deb5a9-c1ae-424a-8761-3db38c245a78
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Date deposited: 18 Mar 2021 17:54
Last modified: 17 Mar 2024 03:24
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Contributors
Author:
Andrew Charles MacLachlan
Author:
Brian Boruff
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