The inspection of strategic works such as dams is of vital importance both for their maintenance and for the safety of downstream populations. The reduced accessibility, both for uptake needs and for their strategic nature, and the large time needed for an inspection by traditional method do not facilitate the investigation of this type of structures. The new unmanned aerial vehicle (UAV) technology, equipped with high-performance cameras, allows for rapid photographic coverage of the whole dam system. Apart from the placement on the structure of a high number of markers, the correct geo-referencing and validation of the model also requires an important terrestrial topographic campaign by total station, Global Positioning System and laser scanner. Punctual, linear and surface analysis shows the high accuracy of the drone acquiring technique. The product is suitable for a detailed survey of the conservation status of the materials and the complete metric reconstruction of the dam system and the adjacent land. The present work explains firstly a UAV acquisition and then the first dense point cloud validation procedure of a concrete arch gravity dam. The Ridracoli dam is the object of the survey, located in the village of Santa Sofia in central Italy.
This paper investigates the accuracy of models obtained by drone surveys. To this end, this work analyzes how the placement of ground control points (GCPs) used to georeference the dense point cloud of a dam affects the resulting three-dimensional (3D) model. Images of a double arch masonry dam upstream face are acquired from drone survey and used to build the 3D model of the dam for vulnerability analysis purposes. However, there still remained the issue of understanding the real impact of a correct GCPs location choice to properly georeference the images and thus, the model. To this end, a high number of GCPs configurations were investigated, building a series of dense point clouds. The accuracy of these resulting dense clouds was estimated comparing the coordinates of check points extracted from the model and their true coordinates measured via traditional topography. The paper aims at providing information about the optimal choice of GCPs placement not only for dams but also for all surveys of high-rise structures. The knowledge a priori of the effect of the GCPs number and location on the model accuracy can increase survey reliability and accuracy and speed up the survey set-up operations.
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