Evaluating the effect of seasonal variations on walking behaviour in a hot weather country using logistic regression

Khaled Shaaban, Deepti Muley and Dina Elnashar

International Journal of Urban Sciences, 2018, vol. 22, issue 3, 382-391

Abstract: The city of Doha, Qatar experiences a hot and arid weather throughout the year. This study investigates the effect of season, type of day, and time of day on the walking behaviour of pedestrians in these conditions using logistic regression. The study uses data obtained from observational surveys conducted at a densely populated mixed-use neighbourhood located in the heart of the city. The results showed the walking activity is much less during hot weather. The results of the logistic regression analysis suggested that the pedestrians from other nationalities living in Qatar had much higher odds of walking compared to the Qatari nationals. Furthermore, men had almost double the odds of walking compared to females. The choice of the time of day model indicated that a pedestrian has more than twice the odds of walking in the evening time compared to the morning and afternoon times. The results can help policy makers and public agencies to develop programmes to promote the walking culture in this region.

Date: 2018
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DOI: 10.1080/12265934.2017.1403363

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