Investigating the Spatial Heterogeneity of Urban Heat Island Responses to Climate Change Based on Local Climate Zones

Abstract

Global warming and the urban heat island (UHI) phenomenon have significant impacts on human activities, against which it is necessary to develop effective coping strategies. Based on the local climate zone (LCZ) system, this study used the land-cover and surface temperature data on the Chang–Zhu–Tan (CZT) urban agglomeration in China in 2006, 2010, 2016, and 2020 to analyze the impact of climate change on the land surface temperature (LST) under different land-cover types. The results illustrate that the LCZ map generated on the basis of the improved World Urban Database and Access Portal Tools (WUDAPT) is more accurate and efficient than the traditional method. The accuracy is increased by more than 15%. From 2006 to 2020, the main built-up types in the CZT urban agglomeration were the sparsely built, the large low-rise, and the compact mid-rise types. The low-plant type represents the most significant proportion of the natural types, followed by the water and the dense-tree types. The built-up types in the CZT urban agglomeration tend to be the high-rise, dense, and industrial types. Urban construction land is taken mainly from the sparsely built type of land. The average LST of the large low-rise and heavy-industry zones is significantly higher than the average LST of the three cities. The average LST values for the water and dense-tree zones are significantly lower than the other average LST values. The LST is stable in each LCZ, showing little correlation with the size of the LCZ area. Compact low-rise land use is ineffective against climate warming and inhibits economic growth. Compact high-rise and open high-rise land can not only effectively deal with climate warming but can also significantly stimulate economic growth. This paper helps us to understand the effect of land cover on climate warming and the economic benefits of LCZs in the CZT urban agglomeration and provides strategies to optimize the use of land resources.