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. High-quality 3-D point clouds generated from repeat camera-equippedunmanned aerial vehicle (UAV) surveys are increasingly being used toinvestigate landscape changes and geomorphic processes. Point cloud qualitycan be expressed as accuracy in a comparative (i.e., from survey to survey)and absolute (between survey and an external reference system) sense. Herewe present a simple workflow for calculating pairs or sets of point cloudswith a high comparative accuracy, without the need for ground control pointsor a differential GNSS (dGNSS)-equipped UAV. The method is based on the automated detection ofcommon tie points in stable portions of the survey area. We demonstrate theefficacy of the new approach using a consumer-grade UAV in two contrastinglandscapes: the coastal cliffs on the island of Rugen, Germany, and thetectonically active Daan River gorge in Taiwan. Compared to a standardapproach using ground control points, our workflow results in a nearlyidentical distribution of measured changes. Compared to a standard approachwithout ground control, our workflow reduces the level of change detectionfrom several meters to 10–15 cm. This approach enables robust changedetection using UAVs in settings where ground control is not feasible.

Short Communication: A simple workflow for robust low-cost UAV-derived change detection without ground control points