2024, 04 April |
DOI: 10.14489/td.2024.04.pp.064-068 Asadov H. H., Bayramov H. Z. Abstract. The urgent importance of the task of monitoring the state of forests lies in the danger of forest fires. Forest fires are a frequent occurrence in almost all continents. Despite the high information content of the spectral signs of a forest fire, the corresponding functionality is not fully used in the known implementations of the forest fire early detection system. The spectral region in which it is possible to distinguish forest areas in a state of fire from their usual state is quite wide and covers the middle and thermal zone of the infrared part of the spectrum. The installation of spectral equipment (multi- and hyperspectrometers) on board the UAV (unmanned aerial vehicle) can certainly expand the functionality of unmanned equipment in the early detection of forest fires. The optimal procedure for using UAVs equipped with hyperspectral equipment for early detection of forest fires is proposed. An optimization problem has been formulated and solved to determine the most appropriate mode of changing the UAV flight altitude with an increase in the wavelength of the measurements being carried out. According to the proposed method, on the right branch of the Planck curve, with increasing wavelength, the flight altitude should be increased, and on the left branch it should be reduced. This order corresponds to the case of increasing the wavelength on both branches and follows from the integral restriction set on the function of the dependence of the flight altitude on the wavelength, which comes from the limited real energy resources on board the UAV. Based on the developed method, a new technique for early detection of forest fires based on the use of hyperspectral method is proposed. Keywords: forest fires, unmanned aerial vehicle (UAV), altitude, hyperspectrometer, measurements.
H. H. Asadov, H. Z. Bayramov (National Aerospace Agency, Baku, Republic of Azerbaijan) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , huseyn,bayramov0228@
1. Li S. (2018). Wildfire Early Warning System Based on Wireless Sensors and Unmanned Aerial Vehicle. Journal of Unmanned Vehicle Systems, 7(9).
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