## 5 Results
### Study Site 1
#### 5.1.2 Biophysical Parameters Computation  
Image analysis conducted as reported in the materials and method section of this study highlighted the great efficiency for RBR to assess the soil burn severity and its variation over time. Indeed, the possibility to also observe the partial vegetation regrowth via the same index reduces the complexities deriving from the comparison of different indices. However, despite the information provided regarding vegetation health and resprouting, RBR nature and aim was not focused on vegetation health analysis. Therefore, biophysical indices were computed to fill the gap between fire burnt severity and vegetation recovery in multitemporal observations to assess the variation of vegetation health and ground cover. SNAP allowed for the computation of LAI, fCover, and fAPAR. For each index, the higher the value, the healthier and stronger the vegetation resprouting was evaluated. The LAI index, defined as the green leaf area per unit horizontal ground area, made it possible to observe through the acquisitions (Figure 7a-c) the progressive vegetation restoration highlighted by the index value variations. Despite the index being reported to range between one and eight, to favor the data visualization it was decided to represent the values within the 1% and 99% range. This decision was also supported by the presence of multiple fires surrounding the investigated area contributing for the index saturation, therefore reducing the information available on the area of interest (Figure 7a, 4 July 2017 acquisition). The timeseries graphic computed for LAI values for the burned area exhibiteda strong decrease compared to the pre-fire image (Figure 8a), with the 2017 summer and winter periods having the lowest values of leaf area index recorded. Figure 6: Sentinel-2 RBR computed index severity classes and area represented over the scene. (**a**) June–July 2017 couplelet; (**b**) August–September 2017 couplelet; (**c**) December–January 2018 couplet; (**d**) April–July 2018 couplet; (**e**) October–January 2019 couplet; (**f**) May–August 2019 couplet. 5-8A-5 color composite. Figure 7: LAI index representation from 4 June 2017 to 3 August 2019. The trend increased with spring-summer 2018, settling on moderate seasonal fluctuations after January 2019. Using as a reference a nearby unburned area timeseries (Figure 8b), LAI values were almost doubled, showing a natural decrease for wintertime acquisitions and peaks at the end of summer, highlighting the unaffected vegetation behavior. fA-PAR is a direct measure of the proportion of incoming photosynthetically active radiation (400-700 nm) absorbed by the canopy. As chlorophyll content is dependent on vegetation health and water, any decrease of it will result in an increase of reflectance. In brief, the index provides a measure of the health of vegetation. Applied to the multitemporal acquisitions of the area of interest (Figure 9a-c), the index performed better compared to LAI for the individuation of unburned patches within the burned area. In the months following the event, it was possible to appreciate the pattern of vegetation activity in the least affected areas. The observation of fAPAR timeseries graph (Figure 10a) showed a small resprouting of bushes and understory, but no leafed vegetation was shown in the LAI timeseries for the second part of summer 2017. Figure 8: LAI index timeseries computed for: (**a**) the burned area (medium severity); (**b**) unburned area. Figure 9: FAPAR representation from 4 June 2017 to 3 August 2019. A more evident resprouting of photosynthetically absorbent features as canopies was observed from May 2018 until January 2019 with a successive decrease in summer 2019. Comparing this trend to the unburned area timeseries (Figure 10b), we can appreciate how unaffected vegetation photosynthetically absorbent features reduce over summer to further increase in autumn and winter. fCover corresponds to the gap fraction of vegetation for the nadir direction (Figure 11a-c).