Investigating the Spatial Autocorrelation of Surface-Air Temperature for Different Ground Materials in Hot Desert Climate | ||
| The Egyptian International Journal of Engineering Sciences and Technology | ||
| Article 31, Volume 39, Issue 1, September 2022, Pages 49-59 PDF (1.34 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/eijest.2022.114803.1123 | ||
| Authors | ||
| Mohamed Gomaa* 1; Ayman Ragab2 | ||
| 11 Department of Architecture Engineering, Faculty of Engineering, Aswan University, Aswan, Egypt. 2 Hekma School of Design and Architecture, Dar Al-Hekma University, Jeddah, Saudi Arabia. | ||
| 2Department of Architecture Engineering, Faculty of Engineering, Aswan University, Aswan, Egypt | ||
| Abstract | ||
| This paper examines and quantifies the micro-scale influence of various ground surface materials on the microclimate conditions in a hot desert climate, like Aswan City. This study applied several methods and techniques such as; on-site measurements, a statistical analysis of variance (ANOVA), multivariate regression models, and advanced spatial statistics techniques that control for spatial autocorrelation. The key findings of this research reveal that the mean values differed significantly from one material to another. The mean air temperatures ranged from 25.47°C to 41.4°C at the grass and the asphalt respectively, while the highest mean value for surface temperature was recorded above the asphalt (50.27°C), and the lowest value was with a mean value of 22.31°C above the grass. Alternatively, based on the spatial analysis, the results of the IDW interpolation show that the lowest mean air temperature is above the grass (26.03°C), while the highest temperature can be observed over the asphalt (42.27°C). In terms of surface temperature, the lowest and highest temperatures were recorded above the grass and asphalt (19.52°C and 50.32°C). There were no substantial differences between the IDW interpolation results, and the results obtained from the measured data. Thus, using spatial interpolation of point data values can be an effective tool to generate detailed spatially continuous temperature maps. The research findings can be utilized to develop effective mitigation strategies to enhance urban microclimate in hot desert regions by using passive approaches of decreasing temperatures. | ||
| Keywords | ||
| Surface-Air Temperature; Spatial Autocorrelation; Ground Surface Materials; Hot Desert Climate; Spatial Interpolation | ||
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