## 3 Results  
The CMAC calibration v1.1 for S2 was tested for the direct correction of L8/9 data without alteration. The two satellite systems are nominally the same, having blue, green, red and NIR bands but somewhat different RSRs, as shown in Figure 7. The resulting S2 v1.1 AC-processed images often contain clearly incorrect color balance - RGB color balance and lack of haze provide competent indications when AC results for RGB bands are incorrect and which bands may be over- or under-represented. The MPC calibration performed for this investigation was confirmed via visual inspection to produce acceptable results (Figure 8). Data generated for Tests 1 and 2 were extracted from the L8/9 images as TOAR or AC output from CMAC and LaSRC within the QIA shapefile boundaries. These data were analyzed in spreadsheets. As a precursor to the three tests listed earlier, the provisional CMAC v1.1-L calibration was developed through the MPC pathway and tested qualitatively by correcting several relatively high-level Atm-I images. The example CMAC v1.1-L correction in Figure 8 exhibits elevated Atm-I ranging between 970 and 1240. The CMAC test correction can be seen to have cleared most of the haze and restored a natural-appearing color balance. This result provided qualitative assurance that the MPC calibration was  
Figure 8: The L8 image of Lake Tahoe TOAR and Atm-I grayscale in Figure 1 corrected by CMAC (**a**) and LaSRC (**b**). Wisps of uncorrected haze over the lake in (**a**) result from scaling issues. Figure 7: Relative spectral responses for the four VNIR bands examined here. Sentinel 2 (solid) and Landsat 8 (dashed) visible bands are not equivalent. appropriate for application to process clean-to-moderate Atm-I recorded for the 31 test images of the five SoCal QIAs. Although the v1.1-L calibration is acceptable, it is provisional and subject to further improvement. Figure 8 is instructive: there are obvious features that indicate that the Atm-I levels exceeded the calibration for both methods. For example, the LaSRC image exhibits residual haze and a strong green color shift for thicker patches of haze visible in Figure 1, indicating that Atm-I levels exceeded LaSRC capability--the green shift visible here was also found for LaSRC-corrected images for all four tests. Residual haze and thin wisps of uncorrected smoke are visible toward the upper left of Lake Tahoe in the CMAC correction. Because the scale of these features approaches the 300 m grid cells that mapped the Atm-I grayscale, the residual haze may be related to spatial resolution. The uncorrected wisps of haze in Figure 8 are features of the TOAR smoke plume visible in Figure 1a that are not captured by the Atm-I grayscale (Figure 1b). Figure 8 illustrates how the trend for increasingly higher resolution in smallsat imaging can enhance the accuracy and precision for SR retrieval. As spatial resolution increases, the finer detail from a higher resolution can capture Atm-I. Also, with higher resolutions, pixel mixing will decrease, and this will enhance spectral diversity, which is important in AI and other machine analyses; it is a property actively being explored for machine learning in remote sensing investigations [20], for meteorology [21], and especially for vegetation diversity as affected by climate change [22; 23; 24]. **Test 1. Performance statistics of corrected images under low-to-moderate Atm-I:** CV% was estimated from the average and standard deviation of each band for the 31 images of each QIA. Table 1 provides grand averages of the CV% for L8/9 AC across the five QIAs that show relatively close agreement of CV% among the three treatments. Table 1 values exhibit patterns similar to those observed in the corresponding S2 analysis presented in paper 1: higher CV% (greater dispersion and lower precision) exists at the upper and lower tails of both distributions. Dispersion increased as band wavelength decreased--lowest for NIR and highest for blue. Each CV% value in Table 1 represents an average of 155 values (31 images \(\times\) 5 QIAs).