# UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health
## 3 Results
### Spatial Resolution  
Through resampling the UAV imagery to the spatial resolution of the RapidEye data we examined the influence of spatial resolution on sensitivity to physiological stress onset. The general trends in the spectral indices were very similar between the original UAV imagery and the imagery that was resampled to 5 m (Figure 4). Restricting the analyses to data from 64 and 87 days after treatment (as this spanned the time of the satellite imagery acquisition) the mean reduction in NDVI and RENDVI was greater in the resampled imagery than the original imagery for clusters with sixteen (NDVI 14.6 vs. 11.9; RENDVI 6.39 vs. 5.28) and eight trees (NDVI 13.0 vs. 12.2; RENDVI 5.05 vs. 4.81). In contrast, there was a smaller shift in these indices for resampled imagery with clusters of four (NDVI 9.55 vs. 9.87; RENDVI 3.80 vs. 4.03), two (NDVI 8.18 vs. 9.63; RENDVI 3.18 vs. 3.86), and single trees (NDVI 5.32 vs. 8.66; RENDVI 1.25 vs. 2.41). Similar patterns were observed for the less sensitive metric GNDVI. Compared to the original imagery, the resampled imagery showed greater shifts in GNDVI for clusters of eight or more trees and smaller shifts in GNDVI for clusters with four or fewer trees.  
If the differences in the spectral indices observed between the satellite and UAV sensors were solely the result of spatial resolution then we would expect to see very similar results extracted from the satellite data and the resampled UAV imagery. In contrast to this expectation, resampling increased the magnitude of these differences for the larger cluster sizes with eight and sixteen trees, as described above. Consequently, the resampling process resulted in greater differences in all indices between data derived from UAV and satellite sensors for these two cluster sizes. Although resampling the UAV data decreased the magnitude of reductions in indices derived from smaller cluster sizes these values were still substantially larger than those derived from satellite imagery for cluster sizes of four trees (NDVI 9.55 vs. 2.12; RENDVI 3.80 vs. 2.57; GNDVI 2.30 vs. 0.56), two trees (NDVI 8.18 vs. 0.16; RENDVI 3.18 vs. 1.82; GNDVI 0.9 vs. 0.14), and single trees (NDVI 5.32 vs. 0.38; RENDVI 1.25 vs. 0.53; GNDVI 0.39 vs. 0.29).  
Figure 2: Box and whisker plots showing the distribution of three de-trended spectral indices derived from the two different sensors for control (n = 5) and treated (n = 25) plots over the course of the experiment.The dashed lines show the lower bound of the ‘no-change’ zone calculated from both treated and control plots during the first time step. Change is deemed to have occurred once the upper hinge of the box plot is below the ‘no-change’ bound.  
Figure 4: Each tile displays the mean de-trended spectral indices calculated from a given cluster size from a specific image source on a specific day. UAV-Resampled imagery shows the results extracted from UAV imagery resampled to the spatial resolution of the RapidEye data.  
Figure 3: Each datum represents the 75 th percentile of the spectral indices for an experimental cluster size for both sensors across the duration of the study. The control plots where no trees were treated are represented by the cluster size = 0. The red dashed line shows the 25 th percentile of the pre-treatment values and defines the lower bound of the ‘no-change’ region for a spectral index. The UAV results plotted here have been previously displayed in [12].