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Climate 2016, 4(2), 32; doi:10.3390/cli4020032

Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar

1,†
,
1,†,* , 2,†
and
3,†
1
Toulan School of Urban Studies and Planning, Portland State University, 1825 SW Broadway, Portland, OR 97201, USA
2
Department of Architecture and Urban Planning, Qatar University, Al Tarfa, Doha 2713, Qatar
3
School of Geographical Sciences and Urban Planning, Arizona State University, 975 S Myrtle Ave., Tempe, AZ 85281, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Nir Y. Krakauer, Tarendra Lakhankar, Ajay K. Jha and Vishnu Pandey
Received: 30 April 2016 / Revised: 6 June 2016 / Accepted: 8 June 2016 / Published: 16 June 2016
(This article belongs to the Special Issue Climate Impacts and Resilience in the Developing World)
View Full-Text   |   Download PDF [2653 KB, uploaded 16 June 2016]   |  

Abstract

Recent evidence suggests that urban forms and materials can help to mediate temporal variation of microclimates and that landscape modifications can potentially reduce temperatures and increase accessibility to outdoor environments. To understand the relationship between urban form and temperature moderation, we examined the spatial and temporal variation of air temperature throughout one desert city—Doha, Qatar—by conducting vehicle traverses using highly resolved temperature and GPS data logs to determine spatial differences in summertime air temperatures. To help explain near-surface air temperatures using land cover variables, we employed three statistical approaches: Ordinary Least Squares (OLS), Regression Tree Analysis (RTA), and Random Forest (RF). We validated the predictions of the statistical models by computing the Root Mean Square Error (RMSE) and discovered that temporal variations in urban heat are mediated by different factors throughout the day. The average RMSE for OLS, RTA and RF is 1.25, 0.96, and 0.65 (in Celsius), respectively, suggesting that the RF is the best model for predicting near-surface air temperatures at this study site. We conclude by recommending the features of the landscape that have the greatest potential for reducing extreme heat in arid climates. View Full-Text
Keywords: arid climate; urban heat island; spatial analysis; vehicle temperature traverse; random forest arid climate; urban heat island; spatial analysis; vehicle temperature traverse; random forest
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Makido, Y.; Shandas, V.; Ferwati, S.; Sailor, D. Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar. Climate 2016, 4, 32.

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