LAUSR

Abstract There is a growing trend in the application of Unmanned Aerial Vehicle (UAV) systems for visual inspection of building facades. Current practices remain at a low efficiency to manage the large amount of UAV-collected close-range facade images to support the inspection and documentation of facade anomalies such as cracks and corrosions. This paper proposes a GIS-based two-step procedure to streamline the process of the management of UAV-collected images for supporting building facade inspection. First, a 2D GIS spatial model of building facades is created by net-unfolding facade surfaces around the building footprint in GIS to store the geometric and geographic information of building facades. Then, the UAV-collected images are automatically geo-registered to the 2D GIS spatial model through computer vision techniques applied in GIS. An experimental case study is also presented to demonstrate the process and evaluate the performance of the proposed method. It is demonstrated that the GIS-based spatial model of net-unfolded building facades allows for an efficient and effective registration of UAV-captured close-range facade images without apparent loss of pixel data. Provided with image data processing capabilities to detect and assess facade anomalies, the proposed GIS-based workflow can contribute to an automated documentation of UAV-based facade inspections to support the decision-making of further maintenance actions.