# Comparing Sentinel-2 and Landsat 8 for Burn Severity Mapping in Western North America
## 4 Discussion
### The Effect of Imagery Resolution  
While acknowledging Sentinel's higher spatial resolution as an asset, research comparing Landsat and Sentinel for burn severity mapping is yet to examine the impact it will have on landscape assessments of fire severity patterns. Fire has heterogeneous effects at scales finer than 30 m [28; 86], particularly in non-stand replacing fires, resulting in high sub-pixel variability in tree mortality [31; 87] and frequency of smaller-sized unburned patches [32; 34]. Efforts to map burn severity with sub-30 m resolution imagery show an improved ability to capture fine-scale fire patterns of burn severity, e.g., [88; 89], though they had to rely on proprietary data sources, limiting the ability to scale-up analyses. Mapping NBR-derived indices at pseudo-10 m resolution with Sentinel by resampling the 20 m _SWIR_ band provided a 9-fold increase in resolution over the 30 m Landsat pixel, while still being a freely available dataset with global coverage. True 10 m resolution can also be obtained with Sentinel NDVI-derived indices, such as the RdNDVI we tested. Though RdNDVI performed worse than NBR-derived indices with the compositing approach (Table 4), it performed similarly in the paired scene approach (Table 5), suggesting that with some tweaking of the compositing date range, it could also be a useful index for assessing fine-scale fire effects. Fires mapped at a 10 m resolution had a consistent reduction in moderate severity compared to pixels resampled to 30 m (Figure 2C). While this effect was small overall, averaging a 1% reduction in moderate severity across the 26 fires, this corresponds to a total area of 2443 ha. The effect of this partitioning of'moderate' severity into low and high can be seen by looking at the continuous distribution of burn severity values from a 10 m and 30 m resolution burn severity map of the Hayes Two fire (Figure 2D). While this result is not surprising, given that the resampling process to reduce the 10 m Sentinel imagery to 30 m averages the underlying pixel values, it still provides a baseline for the magnitude of difference that could be expected when mapping burn severity at higher resolution in similar forest types. 'Moderate' severity is the result of a mixture of high and low severity effects within close proximity. This often occurs at the edge of high-severity patches [20], suggesting that mapping burn severity at higher resolution could help delineate unburned areas within a fire, providing more accurate estimates of area burned. Compared to the relatively small differences in severity class proportions, the effect that imagery resolution can have on metrics of the spatial arrangement of high-severity fire are starker, which is an important consideration as these factors gain increasing attention [90; 91; 92; 93]. High-severity patch interior was estimated by Landsat to be 6.6% higher than Sentinel across forested areas within fires in our analysis (Figure 2A), corresponding to a 24,273 ha difference. This is primarily driven by the difference in resolution, rather than differences between sensors, as evidenced by a similar difference between Sentinel estimates of high-severity patch interior when mapped at 10 and 30 m resolution (Figure 2C). While many landscape metrics that quantify patch spatial characteristics are known to be sensitive to resolution [94], this result highlights two important points. First, that researchers of burn severity patch dynamics need to be careful when comparing across resolutions, and ideally test the scaling relationship explicitly, and second, that burn severity maps using coarser-scale sensors may be overestimating the amount of area vulnerable to seed dispersal limitations in some fires, though it is beyond the scope of this analysis to determine whether the higher resolution imagery is actually picking up meaningful ecological differences. Yet, recent work indicated that surviving trees (i.e., fire refugia) are frequently located in Landsat pixels categorized as moderate- or even high-severity [34].