## 3 Materials and Methods  
### Data and Software  
In Table 1, the used datasets are briefly presented. Free and open accessible datasets were selected to be used for each methodological part described in the following subsections. For the operational wildfire mapping, optical/multispectral Sentinel-2 mission satellite images of the ESA Copernicus program were utilized which are open and accessible from the Copernicus Open Access Hub [30]. The products used were the atmospherically corrected and scene classified Level-2A Bottom-of-Atmosphere (BOA) [31]. A key characteristic of Sentinel-2 images important in operational purposes is the 5-day interval between satellite acquisitions over an area and their availability on the Copernicus Open Access \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Datasets** & **Format** & \begin{tabular}{c} **Resolution** \\ **Spatial** \(\mid\) **Temporal** \\ \end{tabular} & **Source** & **Purpose/Use** \\ \hline Sentinel-2 imagery 1  & \begin{tabular}{c} Optical \\ Level-2A \\ \end{tabular} & 10 m (Used) \(\mid\) 2021 & \begin{tabular}{c} Copernicus Open \\ Access Hub \\ \end{tabular} & \begin{tabular}{c} Wildfire \\ Mapping and \\ C Factor \\ \end{tabular} \\ \hline Corine Land Cover 2018 & \begin{tabular}{c} Vector \\ (Polygon) \\ \end{tabular} & - \(\mid\) 2018 & \begin{tabular}{c} Copernicus Land \\ Monitoring Service \\ \end{tabular} & \begin{tabular}{c} Wildfire \\ Mapping and \\ \(P\) Factor \\ \end{tabular} \\ \hline EU-DEM v1.0 & Raster & 25 m \(\mid\) 2000 (2016) & \begin{tabular}{c} Copernicus Land \\ Monitoring Service \\ \end{tabular} & \(LS\) Factor \\ \hline Meteorological data & Text & - \(\mid\) 2021 & \
\begin{tabular}{c} Meteo.gr of the National \\ Observatory of Athens \\ (NOA) \\ \end{tabular} & \(R\) Factor \\ \hline Topsoil physical & & & & \\ properties for Europe & & & & \\ (based on & & & \\ LUCAS topsoil data) & & & & \\ \hline Topsoil organic carbon & & & & \\ (LUCAS) for EU25 & Raster & 500 m \(\mid\) 2014 &
\begin{tabular}{c} European Soil Data Centre \\ (ESDAC) of Joint Research \\ Centre (JRC) \\ \end{tabular} & \(K\) Factor \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Utilized datasets. Hub a few hours after their acquisition. In Table 2, the full list of Sentinel-2 acquisitions is given for each purpose of this study regarding the mapping of wildfires and the \(C\) factor of the RUSLE. The image selection was redundant to the cloud-free scene availability, taking into consideration the temporal coherence for each purpose. Land cover information for the affected study areas was retrieved with the use of the Corine Land Cover 2018 (CLC 2018) in vector polygon format from vector geodatabase open available from Copernicus Land Monitoring Service (Copernicus, 2018). The CLC 2018 is highly accurate (\(\geq\)85% accuracy) with a minimum mapping unit (MMU) of 25 hectares and a mapping minimum width (MMW) of 100 m, while it is detailed enough by having 44 land cover classes at its most analytical level-3 (Copernicus, 2018). In this study, it was used to map the affected area of the wildfire land cover and for the RUSLE's \(P\) factor. Regarding the meteorological data required for the estimation of the \(R\) factor of the RUSLE, these were retrieved from the Meteo.gr of the National Observatory of Athens (NOA) ([PERSON], 2018). Data regarding the precipitation for the examined period were obtained from the respective meteorological stations of the Meteo.gr network within and around of each area of study. The EU-DEM v1.0 is a digital elevation model (DEM) that was obtained freely from the Copernicus Land Monitoring Service for the application of the RUSLE's \(LS\) factor. With a resolution of 25 m, it was produced with the fusion of SRTM and ASTER GDEM datasets (Copernicus, 2018). The last dataset used refers to the topsoil properties necessary for the \(K\) factor calculation of the RUSLE. This dataset consists of 500 m rasters acquired from the European Soil Data Centre (ESDAC) of the Joint Research Centre (JRC).