AbstractIn the past four decades, remote-sensing data and methodologies have been increasingly used in many fields to improve the efficiency, accuracy, or safety of data collection, and construction management is no exception. In recent years, unoccupied airborne systems (UAS), commonly referred to as drones, have emerged as an important platform for the collection of remote-sensing data. When coupled with increasingly affordable sensors and automated image processing techniques, UAS have made the application of remote-sensing approaches to myriad construction and civil engineering problems practical and attractive to the point that UAS-based airborne imaging is becoming routine for many construction management tasks. Based on our review of literature, a comprehensive discussion on the use of UAS methodologies for collecting and analyzing data to assist with construction research is much needed. This paper was developed to discuss current best practices in UAS aerial imagery collection and processing for construction research, including defining key terms. In addition, this paper discusses a variety of methods for the analysis of UAS collected aerial imagery for the following tasks: preconstruction planning, material tracking, project progress tracking, safety, as-built documentation, and building/structure inspection. This paper also includes a perspective on the future of UAS for a variety of construction management tasks. This work contributes to the Data Management and Data Science Body of Knowledge by informing construction researchers of the state of the art of UAS data collection and analysis methodologies. This study also provides practitioners with a comprehensive guide to the use of UAS for onsite construction management tasks, which is an essential component of e-Construction.

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