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. Building Information Models (BIMs) are of paramount importance in lifecycle management of buildings as they enable collaboration among various stakeholders at different phases of a construction project, from planning to maintenance and operation. However, there is usually inconsistency between the as-is condition of the building and its existing BIM, because BIMs are generally not updated to reflect changes in the environment. Monitoring the changes during a building’s lifecycle and keeping the BIM up-to-date is useful for a variety of applications. Yet this process often involves manual surveying inspections, which are very time-consuming, error-prone, and laborious. In this paper, we present an automated approach for building change detection through a comparison between the BIM and a point cloud of the building indoor environment. The approach is based on point classification and surface coverage to identify discrepancies between the BIM and the point cloud. Experiments on a synthetic dataset and an ISPRS Benchmark dataset show the potential of the proposed approach not only for change detection and identifying discrepancies, but also for locating the removed and new structures of the building in comparison with the BIM. The results are useful for updating the BIM to represent the as-is condition of the building and for temporal analysis of changes during a building’s lifecycle.

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

BUILDING CHANGE DETECTION THROUGH COMPARISON OF A LIDAR SCAN WITH A BUILDING INFORMATION MODEL