# Comparing Sentinel-2 and Landsat 8 for Burn Severity Mapping in Western North America
## 4 Discussion
### Image Compositing Approaches  
Applying the relatively new image compositing method to burn severity mapping showed similar, and in some cases stronger, correlations with CBI data compared to the traditional paired scene approach for both Landsat and Sentinel, corroborating the results of recent studies [50; 53]. The extended composite approach, which used a static pre- and post-fire date range for imagery selection, performed well for both Sentinel and Landsat, with the exception of Sentinel's RdNDVI (Table 4). Our study included fires from a diverse set of forested ecosystems within western North America (Table 1), and it is likely that further improvements to the extended composite method could be obtained by customizing the date ranges by region to account for differences in phenology and weather patterns. For instance, [PERSON] et al. [50] used an earlier date range of April through June for fires in the states of Arizona, New Mexico, and Utah, due to monsoonal precipitation patterns common in the region, while using a date range of June through September for all other fires. In the present study, we used a single date range (June through September) for the extended composite, as the delineation between fires affected by monsoonal precipitation was less clear for the fires in our analysis.  
One alternative to choosing a static temporal window for compositing is to make the date range dynamic. The other compositing method we tested, the hybrid composite, was developed specifically to customize the image selection process dynamically for the boreal region of North America, where rapid herbaceous green-up in the year following fire frequently depresses estimates of burn severity [70]. In the first test of this method for fires in temperate forests, we obtained contrasting results for Landsat and Sentinel, with modest improvements for all indices from Landsat imagery, while the \(R^{2}\) of all indices derived from Sentinel imagery (except RdNDVI) decreased compared to the extended composite version. While it is challenging to pinpoint the reason for this difference, one potential explanation is that the higher temporal resolution of Sentinel (3-5 days return time compared to 16 for Landsat) results in more cloud-free pixels obtained during the late fall and early spring included for the post-fire composite image. Particularly for areas that burned at lower to moderate severity and contain some proportion of deciduous vegetation, the NBR values could be depressed for these late and early season pixels, resulting in a lower post-fire mean composite pixel NBR unrelated to the effects of fire. If this is the case, then the addition of Landsat 9 imagery could pose the same issue for the hybrid compositing approach applied to the Landsat catalog in the future due to the increase in temporal resolution. Regardless, the fact that performance increased in the current analysis for Landsat compared to the extended composite shows promise for this dynamic approach to the temporal selection of imagery in regions outside of the Boreal, and performance could continue to be improved with the additional tweaking of date ranges.