4.7 Article

Diurnal and seasonal trends and associated determinants of surface urban heat islands in large Bangladesh cities

Journal

APPLIED GEOGRAPHY
Volume 135, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apgeog.2021.102533

Keywords

Surface urban heat islands; MODIS; Driving factors; Urban expansion; Cross-city comparison; Spatiotemporal analysis

Categories

Funding

  1. [7188134]

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This study focused on the intensity of surface urban heat island (SUHI) in five major cities in Bangladesh and found that factors such as dense city population, a high degree of imperviousness, and the absence of greenery may contribute to urban warming. The findings of this study will help in developing effective local-scale climate change adaptation plans for the projected substantial increase in urban population in Bangladesh in the future.
Many surface urban heat island (SUHI) studies have been conducted around the globe, however there is still a lack of information available regarding the intensity of SUHI (SUHII) in Bangladesh cities. This study focused on diurnal and seasonal SUHI variability, temporal trends and possible drivers in five major cities. Mean annual daytime SUHII ranged from 2.88 degrees C for Dhaka to 0.84 degrees C for Rajshahi, while nighttime intensity varied from 1.91 degrees C (Chittagong) to 0.30 degrees C (Sylhet). The pre-monsoon period exhibited the greatest magnitude and the seasonal amplitude during the winter season was positive for Dhaka and Khulna but negative for the other cities. Correlation analysis indicated that a dense city population, a high degree of imperviousness and the absence of greenery were likely to act singly, or in combination, to increase urban warming within these cities. An increasing warming trend during daytime was observed. The urban population of Bangladesh is projected to increase substantially in future (i.e., to 81.4 million by 2029), so the findings of this study provide valuable insights into this warming issue and will assist in the development of effective local-scale climate change adaptation plans.

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