# Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest
## 4 Discussion
### Trade-Off between Precision and Accuracy of Satellite Estimates  
By increasing spatial resolution and, consequently, the number of pixels representing a given target, we observed a systematic reduction of uncertainties (SD, SE, and CI) associated with our estimates of windthrow tree-mortality (Table 2). However, reductions in uncertainty were followed by systematic reductions in the quality of model fits, mostly due to large errors at the extremes of the disturbance gradient (i.e., low and extreme windthrow severity). This pattern suggests a trade-off between precision and accuracy [116]. In this case, precision indicates the reduction of uncertainty around the mean estimates, and accuracy indicates the closeness of the estimates in relation to the ground truth. In our study, all satellites delivered tree mortality estimates closer to the ground truth over a wide range of disturbance (from moderate to high windthrow severity). Future studies may extend and replicate our methods in regions with different forest attributes and environmental conditions. Although we equalized TOA values prior to comparing images, each satellite has a different setup of imaging angles (Nadir) and spectral resolution. The Nadir angle may affect the detection of targets with irregular surfaces [74; 98], such as in windthrown forests with high amounts of woody debris, survivor and new trees [1]. Large angles can imply obscuration of images and consequent distortion of geometric and spectral features of targets [111; 117; 118; 119]. Landsat 8 images are acquired under Nadir \(\sim\)0 deg, while Sentinel 2 and WorldView 2 have off-Nadir angles (\(\sim\)10.4 deg and \(\sim\)20 deg, respectively). These differences may have reduced the quality of the NPV signal from Sentinel 2, and especially WorldView 2, in relation to that obtained with Landsat 8. This may be critical in relatively small gaps or at the edge of highly impacted areas, where insolation is generally lower and the crown of given trees can promote strong shading effects on their neighbors [31; 120; 121]. To mitigate problems related to this issue, we normalized the fractions for GV and NPV without shade. This procedure ensures that the shadow fraction is filled by equal proportions of GV and NPV within the pixel [27]. Distortions due to the technical attributes of the different satellites were not the objective of the study, but we believe that these effects would not change the overall patterns we report. Apart from being usually acquired from off-Nadir angles due to acquisition costs or mission priorities, commercial high-resolution imagery, such as WorldView 2, can be costly and restricted to small areas [111]. These aspects limit the application of these for mapping windthrows and monitoring forest recovery across large regions and over time. Indeed, our results show that spatial resolution alone does not provide sufficient evidence for the mismatch between field and remote data. Downgrading the spatial resolution of Sentinel 2 and WorldView 2 to that of Landsat 8 changes the relative weight of the NPV and GV fractions (i.e., reduction and increase of NPV and GV values, respectively) (Figure S11). This pattern indicates that spatial resolution has a direct effect on the sensitivity to detect windthrow tree-mortality, as well as to distinguish rapid post-disturbance regeneration. This has a direct effect on estimated values of windthrow severity at subplot level. Although higher spatial resolution has the potential to increase the sensitivity to detect crown damage and branch fall [44], it does not seem to have the potential to strongly improve stand-to-landscape estimates of windthrow tree-mortality. The accurate and precise estimates we achieved with Landsat 8 may also be partially related to its large pixel size (900 m\({}^{2}\)) as in comparison to subplots (250 m\({}^{2}\)). Landsat 8 and Sentinel 2 have broad spectral resolutions and spectral bands that span from the visible to the shortwave infrared (0.43-2.2 \(\upmu\)m) [122; 123].