## 3 Materials and Methods
### Methodology
#### 3.2.1 Operational Wildfire Mapping  
The operational mapping of the previously mentioned wildfires was performed with the use of the Sentinel-2 L2A imagery listed in Table 2. In order to have the most accurate and timely available results, cloud-free images acquired immediately before and after each wildfire event were carefully selected. These images were imported in SNAP and then preprocessed with nearest neighbor resampling of the spectral bands to 10 m resolution and then subset to the area of interest (AOI) extent to enhance processing performance. The next steps included the creation of a cloud and water mask with band maths operations based on the available scene classification from the L2A product and the estimation of the water mask with the normalized difference water index (NDWI) [38] and the collocation of the pre-fire and post-fire event imagery followed to merge them into one product.  
For this study, for the wildfire mapping, the related spectral indices were applied. More analytically, the normalized burn ratio (NBR) is the used index that utilizes the spectral bands of near-infrared (NIR) in which burned areas present low reflectance and shortwave-infrared (SWIR) in which burned areas show high reflectance for the mapping of burned areas and the assessment of burn severity based on Equation (1). The index has high values where healthy vegetation exists and low values in burned areas and areas with low or no vegetation presence [15; 16; 39; 40].  
\[\text{NBR}\ =\frac{\text{NIR}-\text{SWIR}}{\text{NIR}+\text{SWIR}} \tag{1}\]  
The NBR index was calculated before (pre-fire) and after (post-fire) the fire event and then the difference between the two, the dNBR (Equation (2)), results in a better distinction of the burned areas while the burn severity is also assessed. Burn severity is a term used to express the degree of a wildfire's impact on an area's ecosystem. The assessment of burn severity contributes to quantifying the impact of a wildfire and aids restoration attempts and natural disaster management. Based on the dNBR values, the burn severity is classified  
Figure 2: Methodology flowchart.  
into categories as is shown in Table 3 with the higher values corresponding to higher severity and thus the more severe impact of the wildfire on an area [40; 41; 42; 43; 44].  
\[\text{dNBR }=\text{PrefireNBR}-\text{PostfireNBR} \tag{2}\]  
After the dNBR estimation, the relativized burn ratio (RBR) was calculated based on Equation (3). This index aids the assessment of burn severity in a diversity of ecosystems and regions by enhancing accuracy. Additionally, it aids the identification of the changes after a fire in areas with low vegetation [45].  
\[\text{RBR }=\frac{\text{dNBR}}{\text{prefireNBR}+1.001} \tag{3}\]  
The final RBR raster was masked using the above-mentioned cloud and water mask in order to be not only clear from any possible clouds, but also to eliminate existing water surfaces due to their spectral characteristics which make them attributed falsely as burned areas. Results production followed with the masked RBR raster import to the GIS software and its reclassification according to the Table 3 burn severity classes. Conversion to vector polygons, burned area extraction, and clipping of CLC 2018 to the burned area extent were the last steps including the area estimations.