Remote sensing instruments, both aircraft and on-orbit platforms, undergo extensive laboratory calibrations to determine their geometric, spectral, and radiometric responses. Additional in-flight radiometric calibrations can be performed using well-characterized earth targets. The Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign provided such an opportunity when the ER-2 aircraft overflew Railroad Valley on August 13 and 15, 2019. Surface reflectances were available from the August 4, 2019 field team and from the Radiometric Calibration Network (RadCalNet) portal, and spectral aerosol optical depths from an on-site AERosol RObotic NETwork (AERONET) sunphotometer. The Enhanced MODIS Airborne Simulator (eMAS), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), and the “Classic” Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-C) sensors individually performed a vicarious calibration using their respective methodologies and selection of input parameters. A comparison of the at-sensor radiances predicted from these independent analyses highlights some of the uncertainties in the inputs, including choice of solar irradiance model. Although good agreement, within 5%, is found at visible wavelengths, difference can be as large as 15% in the shortwave infrared (SWIR). This highlights the need for the remote sensing community to agree upon a standard solar model, to remove sensor-to-sensor biases derived from in-flight calibrations.

中文翻译：

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FIREX-AQ 期间 eMAS、AirMSPI 和 AVIRIS 传感器的替代校准


遥感仪器，无论是飞机还是在轨平台，都经过广泛的实验室校准，以确定其几何、光谱和辐射响应。可以使用特征良好的地球目标进行额外的飞行中辐射校准。当 ER-2 飞机于 2019 年 8 月 13 日至 15 日飞越铁路谷时，火灾对区域到全球环境和空气质量的影响 (FIREX-AQ) 活动提供了这样的机会。2019 年 8 月 4 日现场团队提供了表面反射率以及来自辐射校准网络 (RadCalNet) 门户的数据，以及来自现场 AERosol RObotic NETwork (AERONET) 太阳光度计的光谱气溶胶光学深度。增强型 MODIS 机载模拟器 (eMAS)、机载多角度光谱偏振成像仪 (AirMSPI) 和“经典”机载可见光/红外成像光谱仪 (AVIRIS-C) 传感器分别使用各自的方法和输入参数的选择进行了替代校准。对这些独立分析预测的传感器辐射率的比较突出了输入中的一些不确定性，包括太阳辐照度模型的选择。尽管在可见光波长下一致性很好（在 5% 以内），但在短波红外 (SWIR) 下差异可能高达 15%。这凸显了遥感界需要就标准太阳模型达成一致，以消除飞行中校准产生的传感器间偏差。