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Flight Parameter Setting of Unmanned Aerial Vehicle Hyperspectral Load
Flight Parameter Setting of Unmanned Aerial Vehicle Hyperspectral Load
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Flight Parameter Setting of Unmanned Aerial Vehicle Hyperspectral Load
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Flight Parameter Setting of Unmanned Aerial Vehicle Hyperspectral Load
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Flight Parameter Setting of Unmanned Aerial Vehicle Hyperspectral Load
Flight Parameter Setting of Unmanned Aerial Vehicle Hyperspectral Load
Journal Article

Flight Parameter Setting of Unmanned Aerial Vehicle Hyperspectral Load

2022
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Overview
Correct flight parameters are critical for obtaining high-quality unmanned aerial vehicle (UAV) remote sensing images. For the UAV, the Rikola hyperspectral load needs to set the instrument's exposure time, UAV flight mode, flight altitude, and other issues when acquiring data. Using the control variable method, UAV Rikola hyperspectral images were collected under different parameters, and the gray-scale target and image's quantitative evaluation index was used to obtain the spectral curves of gray-scale targets, ground features, signal-to-noise ratio (SNR), information entropy, and sharpness of imagery. The results of the comparative analysis show: the vegetation hyperspectral data quality was better when determining the Rikola hyperspectral exposure time using the 64% diffuse plate; UAV hover mode and cruise mode had little impact on data quality; when the flight altitude was within 100 m above ground level, the higher the flying height, the better the data quality. This study therefore provides evidence for obtaining high-quality data using UAV hyperspectral load.