Recent developments in low-cost structure-from-motion (SfM) technologies offer new opportunities for geoscientists to acquire high-resolution soil microtopography data at a fraction of the cost of conventional techniques. However, these new methodologies often lack easily accessible error metrics and hence are difficult to evaluate. In this research, a framework was developed to evaluate a SfM approach for soil microtopography measurement through assessment of uncertainty sources and quantification of their potential impact on overall 3D reconstruction. Standard deviations of camera interior orientation parameters estimated from SfM self-calibration within five different soil surface models were several orders of magnitude larger than precisions expected from pattern-based camera calibration. Sensitivity analysis identified the principal point position as the dominant source of calibration-induced uncertainty. Overall, surface elevation values estimated from both technologies were similar in magnitude with a root mean square (RMS) of elevation difference of 0·2 mm. Nevertheless, the presence of deformation in either SfM or traditional photogrammetric point clouds highlights the importance of quality assurance safeguards (such as a judicious choice of control points) in SfM workflows for soil microtopography applications.