# Detection of Forest Windstorm Damages with Multitemporal SAR Data--A Case Study: Finland
## 2 Material
### Field Data  
The training data and validation data were also selected in a collaboration with the Finnish Forest Centre and extracted from their forest database. The harvesting operation in Finnish forests presume an advance announcement and acceptance by the Forest Centre wherefore the Forest Centre has good overview of stands with wind damage but only after a longer reporting period. Two types of stands were selected for study: (a) stands in which harvesting had been planned to be carried out due to the windstorm damage; and (b) stands in which harvesting had not been reported. We call these stands damaged and non-damaged, respectively, in the following analysis. The total number of stands in reference database falling inside of all images was 977 after screening checks and removal of some doubtful stands, e.g., when stand characteristics seemed to be out-of-date in 2017. The number of damaged stand records was 313 and the number of non-damaged stand records 664. From the damaged stands, 195 stands were severely damaged and the rest slightly damaged. The severity category is assessed in the field by the forestry experts in charge. A severe damage presumes stand regeneration, while slight damage requires only removal of fallen or broken trees. The areas and growing stock characteristics are shown in Table 1 and similar statistics when the volume of growing stock is larger than 75 m\({}^{3}\)/ha in Table 2.  
Figure 1: The location of the study area in Southern Finland. Damaged and non-damaged stands displayed on Sentinel-1 scene from 19 August 2017, VV polarization and VH polarization are shown in Figure 2 (see also the zoomed figures with stand boundaries in Figures 3 and 4). Selection of the Training Data and Validation Data  
The field observation data were ordered based on the east and north coordinates and split into training and validation data using a systematic sampling. The goal was a representative variation both in training data and validation data. Three-fourths of the observations were selected into the training data and the remaining one-fourth into the validation data. The entire data were 977 stands, of which 732 were used as the training samples and the other 245 as validation samples (Table 3). Windstorm damages usually occur in more advanced stands: in thinning forests stands or mature forests stands. The analyses were therefore done also with the forest stands in which the volume of the growing stock on the basis of the Finnish multi-source national forest inventory (MS-NFI) was larger than 75 m\({}^{3}\)/ha, a value leaving out young forests (Table 3) (see Section 2.4 and the work of [PERSON] et al. [36]). The number of those stands was 912 from, of which 683 stands belonged to the training data and 229 stands to the validation data. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Damaged Stands**} & \multicolumn{3}{c}{**Non-Damaged Stands**} \\ \hline  & \multicolumn{3}{c}{**313 Stands**} & \multicolumn{3}{c}{**664 Stands**} \\ \hline Characteristics & Minimum & Average & Maximum & Minimum & Average & Maximum \\ \hline Area, ha & 0.05 & 1.89 & 33.96 & 0.03 & 0.91 & 7.24 \\ Diameter, cm & 0.00 & 19.57 & 29.25 & 0.00 & 17.79 & 27.79 \\ Height, dm & 2.00 & 169.32 & 253.00 & 0.78 & 159.98 & 247.35 \\ Age, years & 1.00 & 56.20 & 96.61 & 0.63 & 49.27 & 98.92 \\ Basal area, m\({}^{2}\)/ha & 0.00 & 18.79 & 30.00 & 0.00 & 18.27 & 30.23 \\ Volume, m\({}^{3}\)/ha & 0.00 & 167.60 & 337.83 & 0.71 & 159.75 & 330.87 \\ Volume, pine & 0.00 & 52.92 & 145.50 & 0.71 & 41.13 & 182.43 \\ Volume, spruce & 0.00 & 84.31 & 304.67 & 0.00 & 68.43 & 284.36 \\ Volume, birth spp. & 0.00 & 21.89 & 110.80 & 0.00 & 34.87 & 107.63 \\ Volume, other br. l. & 0.00 & 8.48 & 103.00 & 0.00 & 15.32 & 67.60 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Average stand-level areas and forest characteristics in training data, separately for damaged and non-damaged stands.