Navigating 3D Scanning and Point Clouds: Theory, Practice, and Real-world Applications
In the coming decades, it seems inevitable that architects will increasingly focus on renovations and rehabilitations –especially in established urban centers–, whether to modernize outdated structures or adapt to new uses and demands by contemporary society. A main challenge when executing these types of projects is obtaining a truly reliable working base, including accurate and true-to-life 3D models. Conducting surveys can be a herculean task, requiring extensive hours or days of on-site work and considerable effort to organize and interpret the collected information, often resulting in data that lacks adequate precision.
In the coming decades, it seems inevitable that architects will increasingly focus on renovations and rehabilitations –especially in established urban centers–, whether to modernize outdated structures or adapt to new uses and demands by contemporary society. A main challenge when executing these types of projects is obtaining a truly reliable working base, including accurate and true-to-life 3D models. Conducting surveys can be a herculean task, requiring extensive hours or days of on-site work and considerable effort to organize and interpret the collected information, often resulting in data that lacks adequate precision.
To simplify these processes, technological advancements have provided a solution: site surveys based on point clouds and 3D scanning, which have the potential to revolutionize the design process. Point clouds are collections of millions or billions of individual measurement points on the surface of objects, which can be obtained through laser scanners, drones, or 3D cameras. Each measurement point contains X, Y, and Z coordinates, as well as other optical properties (reflectance, color). Multiple scanning positions are registered (stitched) to create point clouds of an entire scene, which can be loaded into virtually any CAD platform for standard fieldwork.