A Subband Radiometric Calibration Method for UAV-Based Multispectral Remote Sensing

In recent years, the use of unmanned aerial vehicles (UAVs) to obtain high-resolution multispectral images has received increasing attention. When using reflectance data for quantitative remote sensing, radiometric calibration is needed that converts digital number to reflectance. Empirical linear radiometric calibration models with large calibration sites are feasible and convenient for remote sensing satellite wide-band sensors, but problems may exist with using this method directly in a UAV high-resolution remote sensing application. In this paper, we proposed a high precision, low cost subband empirical line (SEL) radiometric calibration method with two targets composed of black and white nonwoven fabric. To verify the results of the calibration model, analyses were performed by examining the influence of function selection, calibration materials, and the number of calibration panels. Next, the method was applied to natural field targets. The results show that the black and white panels have good spectral, Lambertian, and contrast characteristics; the power equation was more suitable for the visible bands, whereas the linear equation was more suitable for red-edge and near-infrared bands. The average absolute errors between the predicted reflectance and the measured reflectance were at around 10%. The proposed method had smaller errors and higher accuracy than the other function method, and a high correlation between the predicted and measured reflectance of the maize samples was observed. The SEL method developed in this study provides a reference for studying the radiometric calibration of other multispectral sensors.