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Integration and Assessment Between 3D Data from Different Geomatics Techniques. Case Study: The Ancient City Walls of San Ginesio (Italy)

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R3 in Geomatics: Research, Results and Review (R3GEO 2019)

Abstract

The growing availability of complementary geomatics techniques made possible the data collection of a wide variety of objects creating high-quality 3D recordings and representations. Digital photogrammetry proved to be a valuable method to achieve good results in terms of accuracy and quality, exploiting high-resolution images. Mobile Laser Scanners as SLAM devices can produce dense 3D point cloud required to create high-resolution geometric models. In this research project, the data integration from UAV photogrammetry and ‘handheld’ Mobile Laser Scanner has been tested, performing a comparison, evaluation and assessment of their combined use. The efficiency of this approach has been proved for the survey of the ancient city walls of San Ginesio, close to Macerata (Italy). Given the seismic events that seriously damaged San Ginesio and the Marche Region in 2016, the final output defines a suitable baseline for future analysis and restoration activities. Therefore, it wants to prove the necessity to assess novel methods to perform fast and agile acquisition campaigns for the conservation of the fragile heritage.

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Acknowledgements

Our thanks to the team of Restoration course at the Engineering Faculty of Università Politecnica delle Marche, to give us the opportunity to have carried out this survey and for the fruitful collaboration, and the San Ginesio Municipality for providing base material useful to plan the acquisition campaigns.

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Correspondence to Francesco Di Stefano .

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Di Stefano, F., Chiappini, S., Piccinini, F., Pierdicca, R. (2020). Integration and Assessment Between 3D Data from Different Geomatics Techniques. Case Study: The Ancient City Walls of San Ginesio (Italy). In: Parente, C., Troisi, S., Vettore, A. (eds) R3 in Geomatics: Research, Results and Review. R3GEO 2019. Communications in Computer and Information Science, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-62800-0_15

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  • DOI: https://doi.org/10.1007/978-3-030-62800-0_15

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