Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar
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 m...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-06-01
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| Series: | Climate |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2225-1154/4/2/32 |
| _version_ | 1811231574924984320 |
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| author | Yasuyo Makido Vivek Shandas Salim Ferwati David Sailor |
| author_facet | Yasuyo Makido Vivek Shandas Salim Ferwati David Sailor |
| author_sort | Yasuyo Makido |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T10:47:18Z |
| format | Article |
| id | doaj.art-cd59462e9ae0426c8522dd8f2d096c16 |
| institution | Directory Open Access Journal |
| issn | 2225-1154 |
| language | English |
| last_indexed | 2024-04-12T10:47:18Z |
| publishDate | 2016-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Climate |
| spelling | doaj.art-cd59462e9ae0426c8522dd8f2d096c162022-12-22T03:36:24ZengMDPI AGClimate2225-11542016-06-01423210.3390/cli4020032cli4020032Daytime Variation of Urban Heat Islands: The Case Study of Doha, QatarYasuyo Makido0Vivek Shandas1Salim Ferwati2David Sailor3Toulan School of Urban Studies and Planning, Portland State University, 1825 SW Broadway, Portland, OR 97201, USAToulan School of Urban Studies and Planning, Portland State University, 1825 SW Broadway, Portland, OR 97201, USADepartment of Architecture and Urban Planning, Qatar University, Al Tarfa, Doha 2713, QatarSchool of Geographical Sciences and Urban Planning, Arizona State University, 975 S Myrtle Ave., Tempe, AZ 85281, USARecent 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.http://www.mdpi.com/2225-1154/4/2/32arid climateurban heat islandspatial analysisvehicle temperature traverserandom forest |
| spellingShingle | Yasuyo Makido Vivek Shandas Salim Ferwati David Sailor Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar Climate arid climate urban heat island spatial analysis vehicle temperature traverse random forest |
| title | Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar |
| title_full | Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar |
| title_fullStr | Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar |
| title_full_unstemmed | Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar |
| title_short | Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar |
| title_sort | daytime variation of urban heat islands the case study of doha qatar |
| topic | arid climate urban heat island spatial analysis vehicle temperature traverse random forest |
| url | http://www.mdpi.com/2225-1154/4/2/32 |
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