Mapping Local Climate Zones for urban morphology classification based on airborne remote sensing data

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