Abstract
The urban heat island (UHI) becomes more and more serious with the acceleration of urbanization. Many researchers have shown interest in studying the UHI by using remote sensing data, but these studies rarely examine the mountainous cities. Studies on UHI in mountainous cities often used empirical parameters to estimate the land surface temperature (LST), and lacked satellite-ground synchronous experiments to test the accuracy. This paper revised the parameters in the mono-window algorithm used to retrieve the LST according to the characteristics of mountainous cities. This study examined the spatial and temporal patterns of the UHI intensity in Chongqing, a typical mountainous city, and its relationship with land cover from 2007 to 2016 based on the Landsat 5 TM and Landsat 8 TIRS data and the improved method. The accuracy of the LST derivation increased by about 1 °C compared to the traditional method. The high LST areas increased and extended from the downtown to suburban area each year, but the rate of change decreased. The UHI is dramatically impacted by the rivers. There is a good relationship between the urban sprawl and the UHI. The LST was reduced by about 1 °C within a 300 m distance from large urban fringe green spaces. The urban landscape parks had a strong effect relieving the UHI at a 100 m distance. The LST was reduced by about 0.5 °C. This study greatly improves the accuracy of LST derivation, and provides reliable parameters for the UHI researched in mountainous cities.
Highlights
Urbanization is one important attribute of regional social and economic development
The accuracy of the land surface temperature (LST) derivation increased by about 1 ◦C compared to the traditional method and provides reliable parameters for the urban heat island (UHI) researched in mountainous city
Qualitative and quantitative analyses were used to study the spatio-temporal features of UHI and the relationship between LUCC and UHI in the study area
Summary
Urbanization is one important attribute of regional social and economic development. It results in land use/cover changes and increased building density, both horizontally and vertically, in urban areas. Many other researchers have shown interest in estimating the magnitude of UHI, analyzing its spatio-temporal evolution features, understanding its implication with respect to a broad set of environmental factors, and looking for the measures to reduce its detrimental effects [9,10,11,12,13,14,15,16] These studies on the UHI phenomenon can be divided into two types: ground-based observed air temperature in urban and rural weather stations and remotely-sensed data-based land surface temperature [17]. It is hampered by the lack of proper parameters to retrieve the LST in mountainous cities; (3) Many studies lacked satellite-ground synchronous experiment to test the accuracy
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