# Coarse-Resolution Satellite Images Overestimate Urbanization Effects on Vegetation Spring Phenology
## 4 Results and Discussion  
### Urbanization Effects on Vegetation Spring Phenology at Different Spatial Resolutions  
The spatial distributions of spring phenology of all vegetation types (including deciduous trees and crops) extracted by seasonal amplitude method (threshold: 0.3) in TIMESAT software from images with different spatial resolutions are shown in Figure 7. Seasonal amplitude method (also known as relative threshold method) to extract vegetation phenology is widely used, and it has been validated by ground truth and another phenological extraction method (e.g., inflexion-based method) [59; 60; 61]. Moreover, the parameter (0.3) is an empirical threshold that is more suitable for phenology monitoring in the north of China according to the previous studies [23]. A further robustness test of applied methods and thresholds was explored in the Section 4.3. The range of color bars of Figure 7 was unified for each figure. It is apparent that vegetation spring phenology in the central regions (urban areas) is earlier than surrounding regions (rural areas) at all spatial resolutions. Also, compared with the land cover map in Figure 6a, the regions of late spring phenology in Figure 7 are mainly cropland, because the spring phenology of the major crops in Beijing is significantly later than natural deciduous forests. This confirms the necessity of excluding croplands to accurately quantify urbanization effects on vegetation spring phenology at different spatial resolutions. Otherwise, the late vegetation spring phenology of cropland would lead to a large overestimation of the rural-urban phenology difference.  
The vegetation spring phenology (i.e., deciduous forests) in urban and rural areas at different spatial resolutions is quantified and summarized in Figure 8. It shows that vegetation spring phenology in urban areas is earlier than rural areas regardless of spatial resolution, and the extracted spring phenology in both rural and urban areas is earlier at coarser resolution (hereafter named as \"earlier-shifting\") but the magnitude of this earlier-shifting is different between rural and urban areas. Specifically, the vegetation spring phenology in rural areas from 10 m to 8 km is relatively stable  
Figure 7: Vegetation spring phenology extracted by TIMESAT at different spatial resolutions.  
(from 107 to 105 DOY, the pink range in Figure 8a), whereas the spring phenology in urban areas shifts to the much earlier dates with coarse spatial resolutions (from 105 to 97 DOY, the blue range in Figure 8b). The earlier-shifting pattern has a breakpoint at 90 m in urban areas. When spatial resolutions are finer than 90 m (e.g., 10 m, 30 m and 60 m), the earlier-shifting trend is sharp while the trend becomes flat at spatial resolutions coarser than 90 m (e.g., 120 m to 8 km), as shown in Figure 8b.  
The quantitative result of urbanization effects, that is, the vegetation spring phenological average difference between rural and urban areas at each spatial resolution, is shown in Figure 9. It is reasonable to assume that the urbanization effect at 10 m is the most accurate result because most vegetation pixels are more likely dominated by the same species. It is clear that the urbanization effects show an evident overestimation from 10 m to 8 km spatial resolutions, and this overestimation trend can be divided into two segments, a sharp increase from 10 m to 90 m, and a stable overestimate from 90 m to 8 km.  
Figure 8: The average vegetation spring phenology in rural (**a**) and urban areas (**b**) at spatial resolutions from 10 m to 8 km.  
Figure 9: Rural–urban differences of vegetation spring phenology from 10 m to 8 km.