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.

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As a contextual and passive design strategy, solar envelopes play a great role in determining building mass based on desirable sun access during the predefined period. With the rapid evolution of digital tools, the design method of solar envelopes varies in different computational platforms. However, current approaches still lack in covering the detailed complex geometry and relevant information of the surrounding context. This, consequently, affects missing information during contextual analysis and simulation of solar envelopes. This study proposes a subtractive method of solar envelopes by considering the geometrical attribute contained in the point cloud of TLS (terrestrial laser scanner) dataset. Integration of point cloud into the workflow of solar envelopes not only increases the robustness of final geometry of existing solar envelopes but also enhances awareness of architects during contextual analysis due to consideration of surface properties of the existing environment.

To date, the potential development of 3D laser scanning has enabled the capture of high-quality and high-precision reality-based datasets for both research and industry. In particular, Terrestrial Laser Scanning (TLS) technology has played a key role in the documentation of cultural heritage. In the existing literature, the geometric properties of point clouds are still the main focus for 3D reconstruction, while the surface performance of the dataset is of less interest due to the partial and limited analysis performed by certain disciplines. As a consequence, geometric defects on surface datasets are often identified when visible through physical inspection. In response to that, this study presents an integrated approach for investigating the materials behavior of heritage building surfaces by making use of attribute point cloud information (i.e., XYZ, RGB, reflection intensity). To do so, fracture surface analysis and material properties are computed to identify vulnerable structures on the existing dataset. This is essential for architects or conservators so that they can assess and prepare preventive measures to minimize microclimatic impacts on the buildings.