# Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest
## 2 Materials and Methods
### Spectral Mixture Analysis and Remote Sensing Estimates of Windthrow Tree-Mortality
We conducted our analyses using the normalized GV and NPV fractions, for which the sum equals to 1 using the following equation:  
\[\mathrm{NPV}_{\mathrm{norm}}=\frac{\mathrm{NPV}}{(\mathrm{GV}+\mathrm{NPV})} \tag{1}\]  
where \(\mathrm{NPV}_{\mathrm{norm}}\) is the normalized values of the endmembers ranging from 0 to 1 [27]. This implies that a reduction in one fraction leads to an increase in the other fraction by the same proportion [27] (Figure S10). The best images were selected according to [84], our field observations, and the spatial distribution of \(\mathrm{NPV}_{\mathrm{norm}}\) values across the windthrow patches visible in the RGB compositions. We checked the histograms of the \(\mathrm{NPV}_{\mathrm{norm}}\) images and selected those with more than 98% of the pixels with values between 0 and 1 [85]. We also used the residual error (RMS) from the SMA as a selection criterium (i.e., the lower the better) (Figure 2). The differences between the \(\mathrm{NPV}_{\mathrm{norm}}\) before (i.e., old-growth) and after disturbance (\(\Delta\mathrm{NPV}\)) provide a quantitative measure of windthrow tree-mortality [9; 86]. The larger the \(\Delta\mathrm{NPV}\) values, the greater the windthrow tree-mortality [9; 14; 23]. For Landsat 8 and Sentinel 2, we calculated the \(\Delta\mathrm{NPV}\) fraction using the selected pair of images as described earlier (Table S6). In addition, we focused on images whose acquisition date was as close as possible to the windthrow date. We defined the probable date of occurrence based on the analysis of a time-series of Sentinel 2, which has a shorter revisiting time (~5 days) compared to Landsat 8 (~16 days). This approach could not be implemented for WorldView 2, for which we had a single image after the windthrow. The \(\mathrm{NPV}_{\mathrm{norm}}\) and \(\mathrm{\Delta NPV}\) for Landsat 8 and Sentinel 2 varied with similar ranges and amplitudes (Figures S5 and S6, Tables S5 and S6). As supported by this pattern and the old-growth stage of forest surrounding the windthrown areas (i.e., no human or large-scale natural disturbances), comparison analyses were conducted for \(\mathrm{NPV}_{\mathrm{norm}}\) of the three satellites. We calculated \(\mathrm{NPV}_{\mathrm{norm}}\) at subplot level (Table S3). For this, we converted the \(\mathrm{NPV}_{\mathrm{norm}}\) images in raster format to \(\mathrm{NPV}_{\mathrm{norm}}\) polygons in shapefile format using QGIS [87]. We further intersected the subplot shapefile polygon with the \(\mathrm{NPV}_{\mathrm{norm}}\) polygons for isolating all segments inside respective subplots. Thus, for each field subplot we obtained one or more segments of \(\mathrm{NPV}_{\mathrm{norm}}\). We calculated the area of each \(\mathrm{NPV}_{\mathrm{norm}}\) polygon to obtain a weighted NPV value for each subplot [1,2,4] as:  
\[\mathrm{NPV}=\frac{\mathrm{NPV}_{\mathrm{norm}}*\mathrm{A}}{250} \tag{2}\]  
where NPV is the weighted value within each subplot, \(\mathrm{NPV}_{\mathrm{norm}}\) is the normalized value of each pixel, and A is the area of each pixel (m\({}^{2}\)) that is fully or partially included in the respective subplot; 250 is equivalent to the area (m\({}^{2}\)) of each subplot. Apart from the 30 field subplots, we estimated windthrow tree mortality for 100 virtual subplots (10 m \(\times\) 25 m; hereafter referred to as virtual subplots) that were randomly distributed across the disturbed forest (Figure 1d,e). These virtual subplots were used to evaluate the robustness of tree mortality estimates by the three satellites in adjacent areas containing a greater variation of windthrow severity (Figure 1e). The NPV weighted values for virtual subplots were obtained using the same method described for field subplots. Figure 2: Cuts of selected \(\mathrm{NPV}_{\mathrm{norm}}\) images obtained from Spectral Mixture Analysis. (**a**) Landsat 8; (**b**) Sentinel 2; (**c**) WorldView 2.