Correlation or causality between land cover patterns and the urban heat island effect? Evidence from Brisbane, Australia

Deilami, Kaveh, Kamruzzaman, Md., & Hayes, John F. (2016) Correlation or causality between land cover patterns and the urban heat island effect? Evidence from Brisbane, Australia. Remote Sensing, 8(9), Article Number-716.

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Abstract

Numerous studies have identified associations between the surface urban heat island (SUHI) effect (i.e., SUHI, hereinafter is referred to as UHI) and urban growth, particularly changes in land cover patterns. This research questions their causal links to answer a key policy question: If cities restrict urban expansion and encourage people to live within existing urban areas, will that help in controlling UHI? The question has been answered by estimating four models using data from Brisbane, Australia:

  • Model 1cross-sectional ordinary least square (OLS) regression—to examine the association between the UHI effect and land cover patterns in 2013;

  • Model 2cross-sectional geographically weighted regression (GWR)—to examine whether the outputs generated from Model 1 possess significant spatial variations;

  • Model 3longitudinal OLS—to examine whether changes in land cover patterns led to changes in UHI effects between 2004 and 2013, and;

  • Model 4longitudinal GWR—to examine whether the outputs generated from Model 3 vary significantly over space.

All estimations were controlled for potential confounding effects (e.g., population, employment and dwelling densities). Results from the cross-sectional OLS and GWR models were consistent with previous findings and showed that porosity is negatively associated with the UHI effect in 2013. In contrast, population density has a positive association. Results from the longitudinal OLS and GWR models confirm their causal linkages and showed that an increase in porosity level reduced the UHI effect, whereas an increase in population density increased the UHI effect. The findings suggest that even a containment of population growth within existing urban areas will lead to the UHI effect. However, this can be significantly minimized through proper land use planning, by creating a balance between urban and non-urban uses of existing urban areas.

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ID Code: 98528
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: urban heat island, land surface temperature, geographically weighted regression, landsat OLI, landsat TM, cross-sectional analysis, longitudinal analysis
DOI: 10.3390/rs8090716
ISSN: 2072-4292
Subjects: Australian and New Zealand Standard Research Classification > BUILT ENVIRONMENT AND DESIGN (120000) > URBAN AND REGIONAL PLANNING (120500) > Land Use and Environmental Planning (120504)
Australian and New Zealand Standard Research Classification > BUILT ENVIRONMENT AND DESIGN (120000) > URBAN AND REGIONAL PLANNING (120500) > Urban Analysis and Development (120507)
Australian and New Zealand Standard Research Classification > BUILT ENVIRONMENT AND DESIGN (120000) > URBAN AND REGIONAL PLANNING (120500) > Urban and Regional Planning not elsewhere classified (120599)
Divisions: Current > Schools > School of Civil Engineering & Built Environment
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 The Author(s)
Deposited On: 31 Aug 2016 23:10
Last Modified: 01 Sep 2016 22:32

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