Abstract
The rapid development of unmanned aerial vehicles (UAVs) has contributed to a proliferation of multispectral aerial survey technologies and services. Aerial reconnaissance allows to obtain the detailed digital map of the area, including the geographical distribution of radiant temperatures. These temperature maps allow to find out the composition of the objects (figure out type of the material), their real dimensions and size. There are studies concerning processing of multispectral aerial survey images (both obtained in visible and infrared ranges) and selecting the UAV optimal flight altitude for detection, recognition, and identification of monitoring objects. However, the issue of developing an integrated algorithm of UAV multispectral aerial survey for classifying monitoring objects (taking into account the choice of optimal flight altitude and camera’s resolution parameters) still remains open. This article considers the choice of the flight altitude of the UAVs based on Johnson’s criteria for detection, recognition, and identification of monitoring objects. The integrated approach for conducting aerial survey based on mathematical relationship between optimal flight altitude of the UAVs and resolving power of its onboard camera is proposed.
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This research is supported by the RFBR Project No. 19-29-06044.
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Trefilov, P., Mamchenko, M., Romanova, M., Ischuk, I. (2021). Improving Methods of Objects Detection Using Infrared Sensors Onboard the UAV. In: Ronzhin, A., Shishlakov, V. (eds) Proceedings of 15th International Conference on Electromechanics and Robotics "Zavalishin's Readings". Smart Innovation, Systems and Technologies, vol 187. Springer, Singapore. https://doi.org/10.1007/978-981-15-5580-0_8
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