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Abstract |
Owing to the developments that exist in urban landscapes, urban areas experience climates that are different from their surroundings even when in the same climatic region. This is a prominent phenomenon in most urban areas and is commonly known as Surface Urban Heat Island (SUHI). An understanding of some of the drivers of SUHI is imperative for cities worldwide if they endeavor to suppress the socio-economic mishaps related to extremely high UHI. In this study, we sought to explain the drivers of SUHI in two developing cities in Zimbabwe using remote sensing data. We do this through the use of a classification and regression model. The model used climate, land descriptors and anthropogenic activity data as predictor variables against summer night land surface temperature. Using the coefficient of determination (R2) and the root mean square error (RMSE) for evaluation, modelled SUHI was strongly related to actual SUHI. We also found out that night-time lights, a proxy of anthropogenic activity, contributed more to summer night surface urban heat island as compared to other variables used in the study. This study adds more knowledge on the likely drivers of UHI for southern African cities. By identifying SUHI drivers in urban cities, it is plausible to formulate policies or initiatives that regulate extreme summer night SUHI. |
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