## 1 Introduction  
Radiometric calibration of satellite sensors involves converting a measured digital number (DN) to physical units of radiance (e.g., reflectance) to provide reliable quantified scientific data. The process can be classified into pre- and in-flight calibrations [1]. Pre-flight calibration is conducted using laboratory experiments of a well-known radiance source to determine the linear relationship between DN and radiance for each spectral band of the satellite sensor. Although the satellite imaging sensor of the launched satellite is well calibrated by the pre-flight process, the sensor responses to radiometric targets tend to change in orbit because of the differences between laboratory and space environments. The imaging sensor is also influenced by outgassing phenomena, extreme temperature conditions, and exo-atmospheric solar radiation, which affects optical transmission and the charge-coupled device (CCD) [2; 3; 4]. In addition, sensor aging over time contributes to sensor degradation [5; 6]. In a previous report on sensor degradation of the advanced very high-resolution radiometer (AVHRR), band 1 (0.58-0.68 nm) and 2 (0.725-1.00 nm) responses decreased by 4.5% and 3.6%, respectively, in just one year [6]. A report on the Landsat-7 onboard lamp 1, which is typically operational during imaging, showed a decrease of between 1.9% (band 7, 2080-2350 nm) and nearly 30% (band 1, 450-515 nm) in the seven bands over ten years [7]. Therefore, the DN to radiance coefficient must be periodically updated to maintain the quality of satellite imagery [8; 9]. There are three typical approaches used to radiometrically calibrate satellite imaging sensors in orbit: onboard, cross- (or inter-) satellite, and vicarious (relying on in situ data) calibration [3; 9; 10]. Onboard calibration is processed by onboard-mounted calibrators (e.g., a solar diffuser and a blackbody gain monitor) on a satellite, using artificial or natural sources such as lamps, deep space, or the sun, as reference targets. Onboard calibrators provide an opportunity to periodically monitor the performance and stability of the imaging sensor and perform radiometric calibrations at a high temporal frequency [3; 4]. However, it is difficult to mount such calibrators on satellites due to the constraints of power, weight, cost, and the space environment [9; 11]. Furthermore, calibrator performance must be regularly checked or compensated for by other calibration approaches because over time, uncertainties would increase due to degradation of the calibrators [6]. Cross-calibration is commonly applied to numerous imaging sensors. Typical examples include the advanced space-borne thermal emission and reflection radiometer (ASTER), the moderate resolution imaging spectroradiometer (MODIS), and Landsat TM/ETM+ [12; 13; 14; 15]. Obtaining the reference radiance using this approach is more straightforward than in other calibration methods because the imaging sensor can be calibrated using only satellite images. Cross-calibration employs another well-calibrated satellite imaging sensor and stable radiance from relatively homogeneous land cover such as a desert, deep ocean or lakes, a snowfield, or the top of thick convective clouds [4; 9; 16]. Nevertheless, several factors can cause errors, including a gap in imaging times, a difference of spectral response functions, a fully non-homogeneous radiance of the reference target, and different viewing geometries and spatial resolution [8; 9; 17]. Meanwhile, vicarious calibration relies on in-situ data and is processed using a radiative transfer model based on well-characterized natural or artificial targets determined from a field campaign and measurements of atmospheric aerosol optical depth (AOD), water vapor, ozone, and CO\({}_{2}\) concentration.