# Coarse-Resolution Satellite Images Overestimate Urbanization Effects on Vegetation Spring Phenology
## 4 Results and Discussion
### Limitations  
This study has several limitations. First, the images with different spatial resolutions were stimulated from the 10 m data sets which may be different from the real satellite images. Currently, data from different spatial resolutions are limited, so simulation images enabled us to explore images with abundant spatial resolutions. Another benefit of using simulated images is to reduce the influence of atmospheric conditions and sensor configurations from different satellites when comparing their results, so that we can solely evaluate the impact of spatial resolutions on the results. However, the phenology detected from simulated images may be different from real satellite images which would affect practical values of findings from simulated images. To evaluate this problem,  
Figure 12: Typical NDVI profiles at first quartile (Q1) and third quartile (Q3) in rural areas (**a**) and urban areas (**c**); simulated mixed NDVI profiles in rural areas (**b**) and urban areas (**d**); and detected vegetation spring phenology for simulated mixed pixels by different methods, seasonal amplitude (0.3) (**e**), relative threshold (0.1) (**f**), inflexion-based method (**g**) and midpoint method (**h**).  
we compared vegetation spring phenology extracted from two datasets, simulated 500 m NDVI time series and real 500 m MODIS NDVI time series in 2016 (MOD13A1 product downloaded from USGS: [[https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/)]([https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/))). To cover our study area, two MODIS Tiles (h26v04 and h26v05) were mosaicked. Afterwards, we used the same method and same parameters (SG filtering and seasonal relative threshold of 0.3) in TIMESAT to extract vegetation spring phenology of MODIS NDVI profiles. The result shows that the patterns of vegetation spring phenology between a simulated image (500 m) and MODIS (500 m) are coincident (Figure 13). Additionally, the urbanization effect assessed by real MODIS images is around 9 days, which is similar with results from the resampled Sentinel-Landsat time series (7.4 days). Both results show a more significant urbanization effect at 500 m than finer spatial resolutions (e.g., 10 m).  
Second, the rural-urban phenology difference at 10 m was used as a reference to judge the results at other spatial resolutions. It should be noted that 10 m may not be high enough for detecting urban vegetation phenology considering the high heterogeneity of the urban landscape. To more accurately assess the urban effect on vegetation phenology, satellite time-series data with spatial resolution within 10 m are needed. Fortunately, it is expected that such data sets will be available soon due to the fast development of small satellites and satellite constellations.  
Third, Beijing and surrounding rural areas were used as a pilot area in this study. These data might not be sufficient to comprehensively evaluate the influence of spatial resolution on vegetation spring phenology in an urban environment. Our main objective of this study was to answer an important technical question, i.e., how spatial resolution of satellite images affects the results of rural-urban difference in vegetation spring phenology rather than studying urbanization effects on vegetation spring phenology in many cities. Our study provides a prototype for investigating this scale issue and may improve awareness on scale issues when using satellite data to assess urbanization effects on vegetation phenology. Future studies in more cities can help to thoroughly explore this issue.