Abstract
A sensor aboard an unmanned aerial vehicle (UAV) is vulnerable to vibration and natural conditions such as erratic winds. Considering the difference between laboratory and vicarious environments of calibration, a vicarious calibration is closer to the real environment and is a complement to laboratory calibrations for remote sensors. The existing vicarious calibration of UAVs only uses a reflectance-based method, rather than irradiance-based method. Therefore, the error caused by aerosol type assumptions, which is the largest uncertainty for reflectance-based method, is not considered sufficiently during vicarious calibration of UAVs. Considering the difference in the upward radiative transfer path between satellites and UAVs, we propose an improved irradiance-based method.
A simulation experiment and two field experiments were conducted to validate the improved method. To illustrate the impact of inappropriate aerosol type selection on the results derived from both the reflectance-based and improved irradiance-based methods, the simulation experiment was designed with different aerosol optical thickness, heights and aerosol types. Additionally, two field calibration campaigns, under different weather conditions, were performed to calibrate a Headwall hyperspectral imager payload on a UAV, with the help of calibration tarps and MODTRAN5 radiative transfer code. When weather conditions were unsatisfactory, the total uncertainties of the original and improved methods were 5.9–6.7% and 2.3-3.5% respectively, and the uncertainties caused by aerosol type assumption were 15.8-18.7% and 3.5-8.0% respectively. The results of the simulation and field experiments verified that the improved method has higher accuracy and lower uncertainty, and is more suitable for the vicarious calibration of UAV hyperspectral remote sensors.
A Method Suitable for Vicarious Calibration of a UAV HyperspectralRemote Sensor
A sensor aboard an unmanned aerial vehicle (UAV) is vulnerable to vibration and natural conditions such as erratic winds. Considering the difference between laboratory and vicarious environments of calibration, a vicarious calibration is closer to the real environment and is a complement to laboratory calibrations for remote sensors. The existing vicarious calibration of UAVs only uses a reflectance-based method, rather than irradiance-based method. Therefore, the error caused by aerosol type assumptions, which is the largest uncertainty for reflectance-based method, is not considered sufficiently during vicarious calibration of UAVs. Considering the difference in the upward radiative transfer path between satellites and UAVs, we propose an improved irradiance-based method.
A simulation experiment and two field experiments were conducted to validate the improved method. To illustrate the impact of inappropriate aerosol type selection on the results derived from both the reflectance-based and improved irradiance-based methods, the simulation experiment was designed with different aerosol optical thickness, heights and aerosol types. Additionally, two field calibration campaigns, under different weather conditions, were performed to calibrate a Headwall hyperspectral imager payload on a UAV, with the help of calibration tarps and MODTRAN5 radiative transfer code. When weather conditions were unsatisfactory, the total uncertainties of the original and improved methods were 5.9–6.7% and 2.3-3.5% respectively, and the uncertainties caused by aerosol type assumption were 15.8-18.7% and 3.5-8.0% respectively. The results of the simulation and field experiments verified that the improved method has higher accuracy and lower uncertainty, and is more suitable for the vicarious calibration of UAV hyperspectral remote sensors.