## 4 Discussion  
The current study employed both PlanetScope NICFI and Landsat-8 data to analyze the trajectory of spectral recovery in vegetation after blowdown events. Our findings indicate that determining the date of blowdown disturbance plays a key role when estimating damage using traditional remote-sensing-based methodologies based on the \(\Delta\)NPV. PlanetScope NICFI data provide a more effective monitoring capability compared to Landsat data due to its enhanced temporal resolution, which allows it to identify the precise date of blowdown occurrence. Furthermore, our findings also show that the apparent effects of blowdown on vegetation as observed by the satellite imagery may fade away after 15 months of recovery. Therefore, blowdown detection at annual intervals would likely be required in order not to miss disturbance events, which could be achieved either using Landsat or PlanetScope NICFI datasets. Then, determining the date of disturbance can come on a later stage using a denser time series of PlanetScope, Sentinel-2 or Landsat satellites to achieve a more exact date of disturbance. Moreover, our results highlight the importance of considering a regular monthly time scale as a minimum requisite for estimating the date of which blowdown events occurred. Using this approach, we can more accurately estimate damage caused by blowdowns. In contrast, missing this time window may result in underestimating the disturbance by a significant percentage. For instance, \(\Delta\)NPV decreased in 28.47% in the first month post-disturbance, and up to 50% by four months post-disturbance. Therefore, if the change in \(\Delta\)NPV is used as a way to estimate wind damage, time since disturbance becomes a crucial factor that must be considered in the analysis. This study is the first to address the spectral trajectory of blowdown events on a regular monthly basis using the PlanetScope NICFI program. Our results demonstrate its strong potential for accurate estimation of vegetation damage and subsequent recovery. Further use of daily observations can refine this knowledge. Our findings show that identifying the precise date of blowdown occurrence can have significant impact for consistent damage estimation using the \(\Delta\)NPV approach. When detecting the disturbance of blowdown with the variation in non-photosynthetic vegetation (\(\Delta\)NPV), a simple threshold method is usually used in the literature [25; 51; 52], that is, when the \(\Delta\)NPV of a pixel is greater than a critical value, it is considered to be turned into a blowdown gap. For instance, [PERSON] et al. [25] consider 0.06 and [PERSON] et al. [51] set it to 0.16. According to our results, this critical value depends on how many months of recovery have gone by when the imagery is obtained. Therefore, in order to apply the \(\Delta\)NPV method over larger areas, one would need to know the exact date of blowdown occurrence, or one would incur an underestimation of the actual tree mortality. For example, a linear regression between field and remote-sensing data for imagery acquired six months after blowdown [27] will have much lower NPV values than if the imagery was acquired right after disturbance. The use of such an equation would have to be cautious to consider at the same time since disturbance. Therefore, we strongly suggest that integrating field data with remote-sensing estimates must take into account time since disturbance; otherwise, the established relationships will not be reliable for extrapolation in other areas. While we have only investigated spectral mixture fractions--the most traditional data used for blowdown damage estimates--the presented results can likely be generalized to other vegetation indices, as the spectral recovery with vegetation recovery is also reflected on other spectral bands and vegetation indices [53]. PlanetScope NICFI data provided a more reliable identification of the maximum \(\Delta\)NPV after blowdown occurrence than Landsat-8.