# Coarse-Resolution Satellite Images Overestimate Urbanization Effects on Vegetation Spring Phenology
## 4 Results and Discussion
### Possible Reasons for the Amplified Urbanization Effects at Coarse Spatial Resolutions  
Urbanization effects on vegetation spring phenology were explored widely, as shown in Table 1. Although existing studies were carried out in various areas, employed different phenological extraction algorithms, and used satellite data with a wide range of spatial scales (30 m to 1 km), they came to a similar conclusion: vegetation spring phenology in urban areas is earlier than rural areas because of the change of natural environment (e.g., increase of temperature and artificial light). This conclusion has been thoroughly validated by satellite-based remotely sensed data and ground observations [2; 23; 26; 32; 62]. Our study also confirmed this conclusion. Moreover, the current study demonstrated that vegetation spring phenology in urban areas is always earlier than rural areas observed from satellite images using a range of spatial resolutions (Figure 8). In addition, we found that vegetation spring phenology in rural areas remains relatively stable cross different resolutions, but in urban areas, predictions of phenology vary significantly between 10 m and 8 km spatial resolutions (Figure 8), which leads to the amplified urbanization effects at coarse spatial resolutions (Figure 9). To explore the reasons underlying the amplified urbanization effects at coarse spatial resolution, we further employed a histogram of vegetation spring phenology at a spatial resolution of 10 m in both urban and rural areas (Figure 10), which are regarded as the \"pure\" vegetation pixels. We found that vegetation spring phenology in urban areas has higher diversity, earlier spring phenology at first quartile (Q1), and later spring phenology at third quartile (Q3) than rural areas, as shown in Figure 10. This is mainly due to both the natural environment and vegetation species being relatively uniform in rural areas. However, they are much more complicated and heterogeneous in urban areas due to human activities (i.e., artificial light, ground water, land cover types, and planted vegetation), which results in the greater difference of vegetation spring phenology. Then, we calculated average Interquartile Range (IQR) at spatial resolutions from 10 m to 8 km in rural and urban areas to analyze mixed situations of spring phenology at each spatial resolution (Figure 11). As expected, Figure 11 shows that both IQR in rural and urban areas have increasing trends along with spatial resolutions, which means that the diversity of spring phenology of pixels becomes greater when mixing into coarse pixels. This is opposite to the variation of vegetation spring phenology with spatial resolution (Figure 8). To be specific, the IQR in rural areas is relatively stable at each spatial resolution while the urban IQR experiences a significant increase from IQR 0 day of \"pure\" vegetation at 10 m resolution to IQR 16 days at 8 km resolution. Additionally, the IQR in the urban area increases greatly from 10 m to 90 m and becomes more stable (12-16 days) at spatial resolutions coarser than 90 m. When we compared results displayed in Figure 11 with the spring phenology extracted from images of different spatial resolutions in Figure 8, it is clear that spring phenology in both rural and urban areas has a negative correlation with the IQR (correlation coefficients: rural: -0.877, urban: -0.969), suggesting that the large within-pixel diversity of spring phenology (i.e., large IQR) leads to earlier spring phenology detected from satellite images. Our results are thus well-aligned with current studies which found that species with earlier spring phenology in a mixed pixel results in earlier detections of phenological changes than ground truth observations [33; 63]. As documented, a simulation experiment [33] suggested that the compositions of vegetation species with different spring phenological dates in mixed pixels lead to the uncertainty of vegetation spring phenology extraction.