DonNTU (Donetsk, Russia)

Mogilny S. G., Professor, Doctor of Engineering Sciences

SSUGiT (Novosibirsk, Russia)
Sholomitskii A. A., Professor, Doctor of Engineering Sciences

SSUGiT (Novosibirsk, Russia)¹ ; Abylkas Saginov Karaganda Technical University (Karaganda, Kazakhstan)²
Kosarev N. S., Associate Professor, PhD, kosarevnsk@yandex.ru
Kazantseva V. V., Senior Lecturer

Abylkas Saginov Karaganda Technical University (Karaganda, Kazakhstan)
Ozhigin D. S., Associate Professor, PhD

Academician Melnikov Research Institute of Comprehensive Exploration of Mineral Resources–IPKON, Russian Academy of Sciences (Moscow, Russia)

Kulibaba S. B., Leading Researcher, Doctor of Engineering Sciences

deformations of embankment dams and dikes, including geodetic monitoring techniques and remote sensing methods such as terrestrial and aerial laser scanning and unmanned aerial vehicle (UAV) photogrammetry. A detailed analysis of the Sherubai-Nura Reservoir dam UAV image processing was conducted. The analysis showed that the coordinates of approximately 50% of the points in the object model were obtained by machine vision (MV) methods from only two images. A statistical relationship was identified between the number of images in which a point appears and the root mean square errors of point coordinates in the object model. Based on the analysis, recommendations for improving the accuracy of determining point coordinates in the model were formulated. It is shown that to achieve an accuracy of 0.05 meters, a point must be recognized in at least 9 images. Research has shown that increasing the number of images per point should not be achieved by increasing overlap between images and flight lines, as this does not improve photogrammetric intersection angles. Instead, mutually perpendicular flight lines and flight lines with an oblique camera orientation should be used. An important factor for point recognition in images by MV algorithms is the ground sampling distance (GSD) which should not exceed 2 cm/pixel. The authors note that self-calibration of images should be applied with caution unless appropriate conditions are met. In any case, it is advisable to use camera calibration on special high-precision calibration targets. By applying these recommendations, periodic monitoring of embankment dam deformations can be performed with high accuracy, thereby improving the operational safety of the structures.

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