Minimizing the adverse effects of bias and low repeatability precision in photogrammetry software through statistical analysis

While photogrammetry is widely implemented in fields such as archaeology and cultural heritage, the accuracy of this method has yet to be fully addressed. It is imperative that digital photogrammetry models depicting sites of cultural heritage have accurate dimensions to avoid misunderstandings and incorrect analysis. This paper outlines a new method for minimizing the adverse effects of bias and low repeatability precision in photogrammetry software. Specifically, this paper quantitatively addresses the effects of systematic error during scaling of digital photogrammetry models as well as the random error due to a repeatability issue inherent to photogrammetry software. The method was developed using statistical analysis and robust uncertainty calculations and validated through multiple case studies.