A computational workflow to analyse material properties and solar radiation of existing contexts from attribute information of point cloud data

Abstract

This paper investigates a prospective application of point cloud data in supporting the contextual analysis of the built environment during the conceptual design process. Often, the complexity of site information causes architects to neglect several relevant properties that may affect environmental performance analysis, especially when dealing with a complex design case. For example, the current approaches of 3D site modelling lack an understanding of the site characteristics of existing environments with respect to either geometrical or material properties. With the advancement of 3D laser scanning technologies, capturing complex information from real contexts offers great possibilities for architects. From geometric and radiometric information stored within point cloud data, this study specifically proposes a novel approach to contextual analysis that considers material aspects and simulates solar radiation in the real environment. In doing so, three computational stages are developed. First, the correction of a raw dataset is designed to not only minimize errors during the scanning process but to also clean the selected dataset. Second, material exploration and the simulation of solar radiation are respectively used to calculate material properties and solar energy in the existing built environment. Third, an integrated environmental simulation aims at identifying materials found in existing areas within a certain level of insolation. As a form of design decision-making support, the present study ultimately generates a computational workflow for analysing the built environment from which architects may conduct a comprehensive analysis of an existing context before initiating design exploration