## 3 Results
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Blue Band 02**} & \multicolumn{2}{c}{**Green Band 03**} & \multicolumn{2}{c}{**Red Band 04**} & \multicolumn{2}{c}{**NIR Band 05**} \\ \hline
**Percentile** & **TOAR** & **CMAC** & **LaSRC** & **TOAR** & **CMAC** & **LaSRC** & **TOAR** & **CMAC** & **LaSRC** & **TOAR** & **CMAC** & **LaSRC** \\ \hline
40 & 2.8\% & 4.5\% & 3.1\% & 3.4\% & 4.5\% & 4.1\% & 3.3\% & 4.1\% & 3.6\% & 3.5\% & 4.0\% & 3.8\% \\ \hline
45 & 2.7\% & 4.6\% & 3.2\% & 3.4\% & 4.6\% &  
**Test 2. SR distributions derived under low-to-moderate Atm-I:** The SR retrieval values in each QIA were averaged across the 31 images at each of the percentile steps for the three treatments. The resulting average CDFs are plotted per band in Figure 11 for each of the five QIAs. This comparison confirms that the CMAC SR retrieval is equivalent to that of LaSRC. The CMAC average SR retrievals are virtually identical to LaSRC and effectively  
Figure 10: Low-reflectance indices and regression lines for L8/9 calculated for LaSRC and CMAC. Figure 9: Bandwise plots of % error estimates from the 21 percentiles of reflectance distributions of 31 images for 5 QIAs (n = 3255 per band). Plotting atop one another, the pooled error plots show strong convergence for the error profiles of the two methods. plot one atop the other. Slight disagreement can be seen where the orange display of CMAC is exposed. Each of these cases occurred in the blue and green bands for complexities of the CMAC shape that followed from the same shape in the TOAR curves. These results confirm that CMAC v1.1L output is at least as accurate as LaSRC for low-to-moderate levels of Atm-I. Furthermore, this result indicates that the MPC based on single precise points for the translation of the S2 calibration for LaSRC application is appropriate for the calibration of CMAC for new satellites, and especially flocks of numerous smallsats. Figure 11: Average reflectance distribution per band (n = 31) for five SoCal QIAs by reflectance DN. These reflectance distributions of CMAC and LaSRC plot atop one another in all cases with only minor discrepancies where the CMAC curves more closely emulate the shape of TOAR. **Test 3. Quantitative performance of CMAC and LaSRC in moderate-to-extreme Atm-I:** The August 2021 and 2022 British Columbia image pair, taken a year apart, captured ideal conditions for a comparison of images that were haze-affected compared to relatively haze-free conditions (Figure 5). The three AOIs selected to support a comparison of CMAC and LaSRC L8/9 SR retrievals (cities of Penticton, Kelowna, and Vernon) captured a gradient of conditions from moderate to extreme haze effects on the 2021 image. The three circular AOIs for extraction of pixel statistics around these three cities were mapped to contain significant proportions of cultivated dense dark vegetation (DDV). Live spreadsheets for Test 3 containing extracted four-band VNIR pixel values and their statistical analyses are available for download in the Supplemental Materials. CMAC v1.1L software can be accessed through a link to cloud-based correction for a verification of the SR retrieval reported here, and shapefiles are included to support data extraction for this purpose. Table 2 provides a summarization of the results for the NDVI and NDVI-like indices calculated from the extracted data of moderate-to-extreme Atm-I (3 August 2021) versus relatively low Atm-I (6 August 2022). Data from the low-Atm-I image of 2023 (1 August) are included for comparison to the 2022 data. Table 2 cells contain the results from averaging the band values extracted for the 20 highest NDVI per circular sampled area (Figure 6) that were, in turn, averaged and used to calculate the indices presented. As mentioned previously, the lower the Atm-I, the closer the SR retrieval data are to true surface reflectance.