## 2 Materials and Methods
### Data Sources  
In this work, two different sources of information have been adopted: Copernicus Sentinel-2 [30], which provides satellite imagery, and Copernicus Emergency Management Service (EMS) [2], which provides manually generated damage severity maps of burned regions hit by past wildfires. The EMS damage severity maps where used as ground truth grading maps.  
Copernicus is the European Union's Earth Observation Programme, implemented in partnership with the Member States and the European Space Agency (ESA), offering information services based on satellite Earth Observation and in situ (non-space) data. Sentinel-2 is the second mission of the Sentinel spatial program, concerning satellites able to gather spectral data. In particular, the service can provide two kinds of products: Level-1C and Level-2A. Level-1C products provide raw data [31, 32], composed of 100 \(\times\) 100 km\({}^{2}\) tiles (ortho-images in UTM/WGS84 projection), resulting from the use of a Digital Elevation Model (DEM) to project the image in cartographic geometry. The tiles are acquired as 13 different spectral wavelengths and spatial resolutions, summarized in Table 1.  
Level-2A products [33, 34] are generated applying an algorithm for atmospheric reflectance correction on Level-1C products, resulting in an orthoimage Bottom-Of-Atmosphere (BOA) corrected product. The applied correction reduce (i) the noise brought by natural conditions, like air turbulence and fog, and (ii) the influence of aerosols, producing a more qualitative image which highlights ground information. It is applied on every spectral band listed in Table 1, except for band 10 which does not contain any surface information and, therefore, it is omitted. Given the goal of this paper to estimate burning severity levels, it is crucial to avoid atmospherical noise, which could lead to erroneous analyses and predictions. Therefore, in this paper, Level-2A products were used as source data. Currently, those products are very large (about 600 MB for each tile) and thus hard to manage in raw format. Therefore, we used Sinergise Sentinel-Hub Service [35], a cloud based engine that  
\begin{table}
\begin{tabular}{c l c c} \hline \hline \multirow{2}{*}{**Band**} & \multirow{2}{*}{**Description**} & **Central** & **Spatial** \\  & & **Wavelength (\(\mu\)m)** & **Resolution (m)** \\ \hline
1 & Coastal aerosol & 0.443 & 60 \\
2 & Blue & 0.490 & 10 \\
3 & Green & 0.560 & 10 \\
4 & Red & 0.665 & 10 \\
5 & Vegetation red edge & 0.705 & 20 \\
6 & Vegetation red edge & 0.740 & 20 \\
7 & Vegetation red edge & 0.783 & 20 \\
8 & Near Infrared (NIR) & 0.842 & 10 \\
8A & Narrow NIR & 0.865 & 20 \\
9 & Water vapour & 0.940 & 60 \\
10 & Short wavelength infrared (SWIR) & 1.375 & 60 \\
11 & SWIR & 1.610 & 20 \\
12 & SWIR & 2.190 & 20 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sentinel-2 spectral bands description.  
handles the complexity of management of raw data internally, making Earth observation imagery easily accessible through Application Programming Interfaces (APIs).  
Through the Emergency Management Service, Copernicus provides annotations on natural disasters made by domain experts who, depending on the situation, can use in situ measurements, aircrafts, and Sentinel satellite imagery to record the effects of the hazard and the severity of the damage. In the wildfire context, the EMS severity level ranges from 0 (unburned sub-area with \"No damages\") to 4 (\"Completely Destroyed\" sub-area). Intermediate values are used to represent the following situations; \"Negligible to slight damage\", \"Moderately Damaged\", and \"Highly Damaged\".  
In this paper, we opted for the Copernicus EMS annotations because they are freely available for many past wildfire events.