Developing Metrics for Quantifying Buildings’ 3D Compactness and Visualizing Point Cloud Data on a Web-Based App and Dashboard

Abstract

Measuring three-dimensional (3D) building expansion and quantifying both horizontal and vertical dimensions in a nonautomated manner may not be possible for big data sets. This paper aims to present novel metrics for measuring both vertical and horizontal developments and to develop a web-based app and a dashboard workflow which identifies differences in the form and scale of buildings. The novel 3D metrics are developed based on the concepts of contact surface and 3D discrete compactness. A workflow was developed exploiting the potential of advanced geographic information system (GIS) functions, along with airborne lidar data processing, to apply the metrics on both a simulation of big data sets and digital building models from point clouds. The database system, including a geo-web-based app, is developed for visualizing 3D compactness computations on a dashboard and sharing the outcome with practitioners using their own smartphones. In the simulation experiment, nine 3D building block types were created, and the computation results were compared with the same size building blocks, which were derived from lidar point cloud data sets. The computation results of both the simulation and airborne lidar data, which included 123 and 127,407 data points, respectively, show that the novel metrics are able to identify differences among the typologies and intermediate 3D patterns. The presented workflow also enables online visualization of the computation output.