## 3 Results and Discussion
It should be noted that compensations are only paid under certain circumstances, namely the total damaged production is greater than 20%, the total annual compensation of each parcel does not exceed 80%, etc. [81]. Accordingly, considering the temporal dynamics of the flood as well as the flood depth instead of only the maximum extend of the flooded areas, may provide a better estimation of the inundated area. Detailed statistics of the various crops affected by the flood based on ELGA compensations, on the flooded areas limited to the flooded polygons delimited by RS, and on the flooded area extended outside the boundaries of the delimited polygons are presented in Table 4. The comparison of the affected areas for each crop according to ELGA and to RS in Table 4 indicates that there is a direct correspondence between the flooded area that was delineated with the present methodology and the area calculated and compensated by ELGA based on field surveys. The observed differences for individual crops (e.g., fodder crops) could be a result of the different sensitivity of each crop to temporal inundation. For example, fodder crops could suffer less damage for the same inundation time and depth than cotton or vegetables (they are a significant part of the other crops). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Crop**} & \multicolumn{6}{c}{**Affected areas**} \\ \cline{2-7}  & \multicolumn{2}{c}{**ELGA**} & \multicolumn{2}{c}{**RS**} & \multicolumn{2}{c}{**Extended**} \\ \cline{2-7}  & **(m\({}^{2}\))** & **(\%)** & **(m\({}^{2}\))** & **(\%)** & **(m\({}^{2}\))** & **(\%)** \\ \hline Cotton & 30,208,336 & 79 & 27,954,900 & 73 & 92,537,700 & 61 \\ Winter Cereals & 4,588,608 & 12 & 4,456,900 & 12 & 34,590,300 & 23 \\ Corn & 1,529,536 & 4 & 2,563,100 & 7 & 6,916,200 & 5 \\ Fodder & 382,384 & 1 & 2,348,100 & 6 & 12,338,900 & 8 \\ Other crops & 1,529,536 & 4 & 1,067,300 & 3 & 5,489,600 & 4 \\ \hline
**SUM** & **38,238,400** & **100** & **38,390,300** & **100** & **151,872,700** & **100** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Affected areas statistics according to the Greek Agricultural Insurance Organization (ELGA) compensations, to the flooded areas limited to the flooded polygons delimited by RS, and to the flooded area extended outside the boundaries of the delimited polygons (extended). In order to examine the accuracy of the land use data provided by the Integrated Administration and Control System OPEKEPE [68] a land use/cover classification of four multi-seasonal S2 images (Figure 4a-d) using a supervised maximum likelihood classification was also made, utilizing approximately 200 sampling points (mainly declared parcels). The overall accuracy of the classification was 89%, with a kappa of 0.87, due to high homogeneity of the different land use/cover types of the area. The lowest accuracy was observed mainly in the peri-urban areas where there is an intense mixture of classes and secondly the deficient or not updated declarations of the farmers (Figure 10a,b). Figure 10: (**a**) The land use/cover classified image; (**b**) Zoom in image showing the cross-checking of Sentinel-2 classified image and the land use/cover file of OPEKEPE for the accuracy assessment process (red polygon in Figure 10a). As a final step in this analysis, topographic depressions in the affected area that are more susceptible to flooding were also identified. Flood risk was due to the absence of artificial drainage systems or to their inability to outflow the excessive water to the natural streams (e.g., due to high water levels in the main streams). This process was based on the DEM as a means to assess areas prone to flooding and to provide a measure of flood risk.