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Application of UAV 3D HD Photographic Model in High Slope (Highway)

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1303))

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Abstract

With the rapid development of science and technology, the new generation of aerial photography represented by UAV has been widely used in all walks of life. As an important part of expressway, slope maintenance inspection is always the key and difficult point of road inspection. UAV aerial survey technology has the obvious advantage of high geometric precision and high resolution, and its intervention solves the difficult problems faced by traditional highway survey. In this study, UAV is used for slope maintenance inspection, and the characteristics of UAV, the environment of expressway slope and the problems existing in inspection are analyzed. Based on the current working mode of manual image analysis, the quality of the inspection task is controlled from two aspects of shooting and flight, so as to meet the requirements of the inspectors to interpret the slope state. The research also considers the characteristics of UAV and different types of slope, and selects the algorithm suitable for the slope secondary inspection path planning. The research results of this paper confirm that UAV can effectively solve the problems in image resolution, geometric accuracy of ground objects and flight cost of aerial photogrammetry of large aircraft, and greatly improve the survey efficiency.

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Acknowledgements

This research was funded by the Science and Technology Project of CCCC Fourth Harbor Engineering Co., Ltd (No. 2019-A-06-I-11).

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Correspondence to Kaiqiang Zhang .

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Zhang, K., Qin, Z., Zhang, G., Sun, Y. (2021). Application of UAV 3D HD Photographic Model in High Slope (Highway). In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_6

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  • DOI: https://doi.org/10.1007/978-981-33-4572-0_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4573-7

  • Online ISBN: 978-981-33-4572-0

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