Description:
The dynamics of urban vegetation phenology play an important role in influencing human activities. Previous studies have shown high-resolution remote sensing as a tool for urban vegetation mapping, but the low temporal resolution of these data limits their use for phenological modeling. Therefore, it is of great significance to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for urban vegetation phenology monitoring. Here, we extracted the start and end of growing season (SOS and EOS) in urban ecosystems based on both the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) from the 250 m MODIS vegetarion indices product (MOD13Q1). Then the accuracies of the satellite-derived SOS and EOS were evaluated through comparing phenological observations at 18 ground sites. Results showed that SOS was most consistent with the prime of leaf unfolding date and EOS was most consistent with the beginning of leaf coloring date. Overall, EVI was found to have stronger predictive strength than NDVI in detecting urban vegetation phenology in terms of both higher correlation coef- ficients and lower root-mean-square errors. In addition, the dynamic threshold method was more accurate in deriving SOS, while the double logistic method had relatively higher accuracy in deriving EOS .