Article ID Journal Published Year Pages File Type
6921826 Computers, Environment and Urban Systems 2018 12 Pages PDF
Abstract
Intensive urbanization has led to the depletion of vegetation and its replacement by impervious surfaces, resulting in the accumulation of thermal energy, with urban areas becoming warmer than peripheral areas, a phenomenon known as the Urban Heat Island (UHI). Much of the literature has focused on the relationship between the UHI and urban factors at peak summer times, without considering seasonality effects. There is, however, clear evidence that the UHI varies over the year, with implications for greening mitigation strategies, as green spaces are known to help reduce summer local temperatures, but also reduce exposure to winter cold, thus increasing local winter temperatures. Both effects are likely to generate, in varying extents, benefits in terms of better health and reduced energy usage and pollution emissions. This paper addresses the seasonality of the impacts of building rooftop and façade areas, urban canyons, water bodies, vegetation, and solar radiation, on UHI intensity. In a case study of the central area of Columbus, Ohio, these various 2D and 3D inputs, as well as land surface temperatures estimated with remotely-sensed imagery, are captured within a spatial grid, and used in spatial regression analyses. The estimation results confirm the opposite effects of greenery, measured by the NDVI, on summer and winter temperatures. The estimated models are then used to simulate the seasonal changes in temperatures resulting from a potential urban greening strategy involving green roofs, the greening of parking lots and other vacant spaces, and vegetation densification. The results show that increased greenery reduces temperatures in summer and increases them in winter, thus demonstrating that greening and land-use policies designed to mitigate the UHI must account for seasonal effects to achieve year-long effectiveness.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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