Comparing satellite image and GIS data classified local climate zones to assess urban heat island: A case study of Guangzhou

Abstract

Cities are frontlines to tackle climate change challenges including the urban heat island (UHI) effect. The classification and mapping of local climate zones (LCZs) can effectively and consistently describe the urban surface structure across urban regions. This study pays attention to two mainstream methods in classifying LCZs, namely, by using geographic information system (GIS) data such as building footprints or remote sensing (RS) satellite images. Little has been done to compare the divergence and coherence of the abovementioned two methods in modeling UHI. Thus, by comparing pairwise LCZ classes of different urban form characteristics in Guangzhou, this study investigated how GIS- and RS-based approaches complement or conflict with each other in explaining the variance of UHI measured by land surface temperature (LST). First, while both GIS-based (R2 0.724) and RS-based (R2 0.729) approaches can effectively explain heat risks measured by LST, the RS-based method slightly outperforms the GIS counterpart. Second, the sizes of LCZs classified by two methods in urban core districts tend to converge but diverge in urban outskirts with disparities in low-rise urban forms. Both approaches found that LCZs with higher heights are all cooler among compact forms. LCZ E is always related to the highest average LST, and LCZ 7, 8, and 10 contribute significantly to heat islands from both GIS and RS results. This study has developed a comparable framework that is evident based for city planners, architects, and urban policy makers to evaluate which approaches can more accurately reveal relations between UHI and urban geometry with land cover.