There is ample evidence of the cooling effects of green infrastructure (GI) that has been extensively documented in the literature. However, the study of the thermal profiles of different GI typologies requires the classification of urban sites for a meaningful comparison of results, since specific spatial and physical characteristics produce distinct microclimates.
In this paper, the Local Climate Zones (LCZ), a scheme of thermally relatively homogeneous urban structures proposed by Stewart and Oke, was used for mapping and classifying the urban morphology of a study area in Sydney, Australia. A GIS-based workflow for an automated classification based on airborne remote sensing data is presented. The datasets employed include high resolution hyperspectral imagery, LiDAR (light detection and ranging), and cadastral information. This paper also proposes a standardised and replicable workflow that can be applied by researchers and practitioners from novices to experts. The results presented here provide evidence that LCZ can be effectively derived from multiple airborne remote sensing datasets, which can then be used to identify morphological profiles to support varied climatological studies. Future stages of this research include coupling this method with a newly developed GI typology for a more comprehensive analysis of the cooling effects of GI by taking into account the morphological disparities of LCZ.