# Comparing Sentinel-2 and Landsat 8 for Burn Severity Mapping in Western North America
## 3 Results  
### Landsat and Sentinel Burn Severity Correspondence with Field Data  
Across the burn severity indices and mapping approaches tested, Landsat and Sentinel performed similarly as measured by their correlation with CBI field data (i.e., higher \(R^{2}\) or lower \(RMSE\) error). However, when comparing between specific mapping approaches (e.g., imagery season used for the compositing approach and atmospheric correction in the paired scene approach), some consistent differences were observed. Using the paired scene approach, Bottom of Atmosphere (BOA) Sentinel imagery with Sen2 Cor atmospheric and terrain corrections consistently performed better than the uncorrected Top of Atmosphere (TOA) imagery. BOA imagery improved \(R^{2}\) by an average of 0.078, with a particularly large increase of 0.212 for RdNBR (Table 5). Compared to Landsat imagery, the BOA Sentinel imagery also performed better across all indices with an average increase in \(R^{2}\) of 0.059. Using the extended composite imagery method, Sentinel performed marginally better than Landsat with all three NBR-derived indices (dNBR, RBR, RdNBR, mean \(R^{2}\) = 0.590 and 0.606, Landsat and Sentinel, respectively), with the Sentinel-derived RdNBR showing the overall highest coefficient of determination with field-measured burn severity of all methods tested (\(R^{2}\) = 0.643, Table 4). Conversely, when using the hybrid composite imagery method, Landsat-derived NBR indices performed better than Sentinel, with an average difference of 0.057 \(R^{2}\) across the three indices. For Landsat, the hybrid compositing method performed better than the extended compositing with the three NBR indices, increasing \(R^{2}\) by an average of 0.023. For Sentinel, the opposite trend occurred, with hybrid compositing reducing \(R^{2}\) by an average of 0.05 compared to extended compositing. The only non-NBR-derived index tested, RdNPVI, performed consistently worse than the average of its NBR counterparts, lowering \(R^{2}\) for both Landsat compositing methods (0.036 and 0.081, extended and hybrid compositing, respectively), as well as for Sentinel (0.180 and 0.041, extended and hybrid compositing, respectively). RdNDVI derived from the Sentinel extended composite method performed notably worse than all other indices with an \(R^{2}\) of 0.426. Finally, comparing the paired scene and image compositing methods, Landsat NBR-derived indices from both compositing methods slightly outperformed their paired scene counterparts, increasing \(R^{2}\) by an average of 0.014 and 0.037 (extended and hybrid compositing methods, respectively, Tables 4 and 5). In contrast, the paired scene approach using the Sentinel atmospherically corrected BOA imagery improved \(R^{2}\) for the NBR indices by 0.01 compared to the extended composite method, and by 0.06 compared to the hybrid composite method. However, when comparing the compositing approaches, which used uncorrected TOA imagery in the paired scene approach also using TOA imagery, both compositing methods improved average NBR indices by 0.088 and 0.038 (extended and \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Spectral Index**} & \multicolumn{2}{c}{** Landsat 8**} & \multicolumn{2}{c}{**Sentinel-2**} \\  & **Surface Reflectance** & \multicolumn{2}{c}{**Bottom of Atmosphere**} & \multicolumn{2}{c}{**Top of Atmosphere**} \\  & **(Tier 1)** & \multicolumn{2}{c}{**(Level 2A)**} & \multicolumn{2}{c}{**(Level 1C)**} \\ \hline  & \(R^{2}\) & \(RMSE\) & \(R^{2}\) & \(RMSE\) & \(R^{2}\) & \(RMSE\) \\ \(dNBR\) & 0.537 & 0.517 & 0.578 & 0.505 & 0.533 & 0.538 \\ \(RBR\) & 0.584 & 0.471 & 0.637 & 0.444 & 0.601 & 0.465 \\ \(R\)_dNBR_ & 0.607 & 0.447 & 0.633 & 0.443 & 0.421 & 0.661 \\ \(R\)_dNDVI_ & 0.481 & 0.544 & 0.597 & 0.492 & 0.578 & 0.492 \\ \hline \hline \end{tabular}
\end{table}