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

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