## 4 Results and Discussion
The comparison of VD 1.0 and VD 2.0 reveals several general observations:  
* For both-negative trends, VD 2.0 rarely indicates a stronger decline (red in Figure 6c); Figure 7a shows a pixel where a fire occurred. The disagreement between methods is due to several reasons: (1) in the year where the change happened, no cloud-free image was available in VD 1.0, thus the fresh disturbance scar is not included in the regression; (2) before the change, the statically selected images coincide more closely with minimal cover, whereas they coincide more closely with peak cover thereafter--presumably due to a change in vegetation composition after the disturbance. * More commonly, however, VD 1.0 shows stronger negative trends (blue in Figure 6c, cf. Figure 7b). The trajectory shows large inter-annual variability with a low annual minimum of PV fractions, thus pointing to herbaceous-dominated vegetation composition. For such pixels, the static VD 1.0 image selection results in a volatile timing of the observation relative to the phenological cycle--sometimes close to peak cover, sometimes close to minimal cover. Thus, the resulting trend needs to be considered error-prone and potentially spurious. However, it is also apparent that, although the peak vegetation cover is rather stable over the long period (VD 2.0), there still is change related to a decreasing annual minimum of the cover, which is largely balanced by an increase in seasonal amplitude. This could be caused by an increase in herbaceous cover at the expense of a woody cover. * Orange colors in Figure 6c represent pixels where both trends are positive with a stronger increase in VD 1.0; pink colors in Figure 6c represent pixels with a positive trend in VD 1.0 and a negative trend in VD 2.0. In both time series, a change is included that transiently (Figure 7c) or progressively (Figure 7d) modifies the vegetation composition such that static image selection does not guarantee a stable location of the observation relative to the phenological cycle. Figure 6: Zoom on Psiloritis area, i.e., study area of [42]. (**a,b**) As in Figure 5. (**c**) Delta cover change (\(\Delta CC\)), i.e., Figure 6a,b. The colors read as follows: blue to red colors represent a cover loss in both methods, while blue (red) indicates less (more) loss in the Vegetation Dynamics 2.0 methodology; green to orange colors represent a cover gain in both methods, while green (orange) indicates a larger (smaller) gain in the Vegetation Dynamics 2.0 methodology. Pink and cyan represent areas with different change directions, where pink indicates a loss (gain) in Vegetation Dynamics 2.0 (1.0) and cyan indicates a gain (loss) in Vegetation Dynamics 2.0 (1.0). The point signatures in (**c**) refer to the pixels shown in Figure 7. White areas are non-natural areas or above 1500 m a.s.l, which were out of scope of this study. * Green colors in Figure 6c represent pixels where both trends are positive with a stronger increase in VD 2.0; teal colors in Figure 6c represent pixels with a negative trend in VD 1.0 and a positive trend in VD 2.0. The corresponding time series (cf. Figure 7e,f) reveal that there is indeed an increase in peak cover (VD 2.0). The VD 1.0 analysis, however, indicates a slight increase only (Figure 7e) or a strong decline (Figure 7f), which is caused by a systematic shift in the timing of the statically selected images relative to the phenological cycle as a consequence of changes in vegetation composition towards a higher share of herbaceous cover, i.e., earlier peak cover that quickly turns into NPV at the beginning of the dry Mediterranean summer. Figure 7: Representative time series for the different delta cover change types in Figure 6. Color coding as in Figure 3. Green circles represent the value of peak of season (VPS) metric (Vegetation Dynamics 2.0); white circles are the statically selected images from Vegetation Dynamics 1.0. Regression lines and cover change for both methods are shown. Subplots (**a**–**f**) are representative pixels that are referred to in the text below.