Building a Digital Twin of the University of North Texas Using LiDAR and GIS Data

Abstract

Digital twins are virtual renditions of the actual world that include real-world assets, connections, activities, and processes. Recent developments in technologies play a key role in advancing the digital twin concept in urban planning, designing, and monitoring. Moreover, the latest developments in remote sensing technology have resulted in accurate city-scale light detection and ranging (LiDAR) data, which can be used to represent urban objects (buildings, vegetation, roads, and utilities), enabling the creation of digital twin of urban landscapes. This study aims to build a digital twin of the University of North Texas (UNT) using LiDAR and GIS data. In this research, LiDAR point clouds are used to create 3D building and vegetation modeling along with other GIS data (bicycle racks and parking areas) in creating a digital twin model. 3D Basemap solutions of ArcGIS Pro and ArcGIS Online Scene Viewer, respectively, are used to create an initial 3D urban model and build the ultimate digital twin of UNT. The emergency management floorplans of UNT buildings are incorporated into the digital twin to increase emergency management efficiency. Moreover, solar power potential for individual buildings at UNT has been estimated using the Digital Surface Model (DSM) and integrated into the digital twin model to identify the buildings with the highest solar energy capacity. This study indicates that implementing a digital twin in a university enhances campus efficiency, safety, and sustainability, serving as a central system for a smart campus and contributing to intelligent urban growth.