# Detection of Forest Windstorm Damages with Multitemporal SAR Data--A Case Study: Finland
## 2 Material
### Sentinel-1 SAR Data  
In total, 40 Sentinel-1 GRD (ground range detected) images, Level-1 data with VV and VH polarizations, were downloaded from ESA Open Access Hub. Some of these images covered the test site only partly. In total, 27 image layers were constructed (mosaiced) from the images. The images were acquired in interferometric wide (IW) mode between 4 January and 25 September 2017. Multi-temporal data are necessary for change detection, but aggregating the data also reduces the effect of the random scattering (speckle) on the estimates and error estimates. It makes it possible to utilize the variation of the data acquisition conditions in the estimation using multifaceted information. The dates of the images are shown in Table 4.  
The pixel spacing of orthorectified scenes was set to 10 m. The local digital elevation model (DEM) available from National land Survey was used (see Section 2.5). Scenes were aggregated in azimuth and range to obtain images with pixel dimensions approximately corresponding to the 10 m grid spacing. Bi-linear interpolation method was used for resampling in connection with the orthorectification. Radiometric normalization of intensity was done using a projected pixel area-based approach to minimize the effect of the topography. The scenes with a pixel size of about 13.5 m were further re-projected to the ERTS89/ETRS-TM35 FIN projection (EPSG:3067) and resampled to a final pixel size of 10 m.  
In total, 27 Sentinel-1 mosaics were constructed from the 40 original Sentinel-1 scenes and thus the final data stack includes 54 backscatter intensities layers of VH and VV polarizations. Examples of intensity variations before and after the damages are shown in Figures 3 and 4 with stand boundaries displayed on the intensities.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Mosaic** & **Date** & **Mosaic** & **Date** & **Mosaic** & **Date** \\ \hline
1 & 4 January & 10 & 14 July & 19 & 20 August \\
2 & 16 January & 11 & 15 July & 20 & 1 September \\
3 & 28 January & 12 & 21 July & 21 & 7 September \\
4 & 9 February & 13 & 26 July & 22 & 12 September \\
5 & 21 February & 14 & 2 August & 23 & 13 September \\
6 & 2 July & 15 & 7 August & 24 & 18 September \\
7 & 3 July & 16 & 8 August & 25 & 19 September \\
8 & 8 July & 17 & 14 August & 26 & 24 September \\
9 & 9 July & 18 & 19 August & 27 & 25 September \\ \hline \hline \end{tabular}
\end{table}
Table 4: The 27 Sentinel-1 data mosaics from 2017 used and their acquisition dates.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Data** & \multicolumn{4}{c}{**Entire Dataset**} & \multicolumn{4}{c}{**Volume > 75 m\({}^{3}\)/ha**} \\ \hline  & \multicolumn{4}{c}{**Damage**} & \multicolumn{4}{c}{**Damage**} \\ \hline  & No & Severe & Slight & Total & No & Severe & Slight & Total \\ \hline Training & 492 & 142 & 98 & 732 & 474 & 120 & 89 & 683 \\ Validation & 172 & 49 & 24 & 245 & 57 & 48 & 24 & 229 \\ \hline Total & 664 & 191 & 122 & 977 & 631 & 168 & 113 & 912 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The numbers of forest stands in the training data and validation data classified also based on the severity of the damage in the entire dataset and when the volume of growing stock is larger than 75 m\({}^{3}\)/ha.  
Figure 3: Examples of damaged and non-damaged stands displayed on Sentinel-1 scenes: (**a**) before windstorm damage, 7 August 2017; and (**b**) after windstorm damage, 19 August 2017 (**b**) (VV polarization, EPSG:3067).  
Figure 4: Examples of damaged and non-damaged stands displayed on Sentinel-1 scenes: (**a**) before windstorm damage, 7 August 2017; and (**b**) after windstorm damage, 19 August 2017 (**b**) (VH polarization, EPSG:3067).