Developing a rapid method for 3-dimensional urban morphology extraction using open-source data

Abstract Available and accessible three-dimensional (3D) urban morphology data have become essential for extensive academic research on built-up environments and urban climates. A rapid and consistent methodology for extracting urban morphology information is urgently needed for sustainable urban development in global cities, particularly given future trends of rapid urbanization. However, there is still a lack of generally applicable methods that use open-source data in this context. In this study, we developed a simple and highly efficient method for acquiring 3D urban morphology information using open-source data. Building footprints were acquired from the Maps Static application programming interface. Building heights were extracted from an open digital surface model, i.e., the ALOS World 3D model with a resolution of 30 m (AW3D30). Thereafter, urban morphological parameters, including the sky view factor, building coverage ratio, building volume density, and frontal area density, were calculated based on the retrieved building footprints and building heights. The proposed method was applied to extract the 3D urban morphology of Hong Kong, a city with a complex urban environment and a highly mixed geographical context. The results show a usable accuracy and wide applicability for the newly proposed method.