## 4 Discussion  
Rapid and variable cloud cover is one of the major challenges faced by applications of optical remote sensing technology. Establishing a microsatellite constellation to implement a space observation capability with high-frequency and high-resolution observation is a worldwide trend for the future satellite technology. The Planet Company operates a satellite constellation of over 200 active satellites, providing daily global observations with a spatial resolution of 3-5 m every day. The BNU-1 satellite is a type of microsatellite satellite designed by China for polar observation. It achieves the observation capability covering polar areas within 5 days and a resolution of 80 m. Limited by the carrying capacity of the BNU-1 satellite platform, there are still some deficiencies of BNU-1 images, such as the poor control of the satellite attitude resulting in the errors of its geolocation accuracy [10]. The issue of radiometric calibration of satellite sensors also often appears in microsatellite  
Figure 12: Comparisons of radiances from the original, the corrected BNU-1 image and the Landsat8 image. The blue scatters show the relationship between the radiances from the uncorrected BNU-1 image and the Landsat8 image. The red scatters show the relationship between the radiances from the corrected BNU-1 image and the Landsat8 image. satellites [17]. Absolute and relative radiometric calibration techniques are widely used in the radiometric calibration of satellite sensors [18]. This study evaluated the radiometric accuracy of the BUN-1 level-0 product. The results showed that systematic biases were detected at the edges of the blue band images obtained by the CMOS1 and CMOS2 sensors of BNU-1, resulting in a noticeable yellow color difference in the BNU-1 true color images. This study developed a relative sensor normalization method, using the panchromatic band radiometric data as references, to correct the radiometric bias in the blue band. The results of the study indicate that the relative sensor normalization method proposed in this study can improve the radiometric accuracy of the BUN-1 level-0 product. The yellow color difference appeared in the uncorrected BNU-1 true color image has been corrected. The corrected true color images have excellent visual performances. The radiances of snow surfaces also have good consistency with ground observations and Landsat-8 images in the red, green, and blue bands. The method proposed in this study corrects the systematic bias of the blue band using only the radiometric characteristics of the panchromatic band, which is simple and easy to be applied for other satellites. Moreover, the radiometric cross-calibration method is a type of widely used radiometric correction method by using images from another satellite to improve the radiometric errors of the target satellite. However, due to different satellite overpass times, the radiometric differences usually existed in the two satellite images from different satellites. Since the BNU-1 images of the panchromatic band and the blue band are observed simultaneously, the proposed method can avoid the radiometric differences caused by different satellite overpass times. While the relative sensor normalization method we proposed can effectively correct the radiometric bias in the BNU-1 blue band images, it still has some shortcomings. Firstly, for the low-reflectance surfaces, such as rocks and lichens, there are still gaps of radiances between the corrected BNU-1 images and the ground measurements. As shown in Table 3, the radiances of BNU-1 and Landsat 8 images for the low-reflectance surfaces are relatively close and are both higher than ground observations. This may be due to the scale effects of the BNU-1 and Landsat 8 images. The spatial resolutions of BNU-1 and Landsat 8 images are 80 m and 30 m, respectively. It is difficult for a single pixel in the BNU-1 and Landsat 8 images to be composed entirely of low-reflectance surfaces.