Urban vegetation phenology analysis using high spatio-temporal NDVI time series

Most of current products can partially reach the requirement of high spatial and temporal resolution needed in urban applications. Fortunately, the new generation of satellite in a form of constellation, e.g. Europe’s Sentinel-2, China’s HJ-1A/B and GF-1/6, is expected to provide more frequent observations (<1 week) with a higher spatial resolution (<30 m). Consequently, a proper method should be selected to construct high spatio-temporal time-series NDVI and to derive phenological features for urban applications. In this study, a high spatio-temporal NDVI product for urban scale vegetation time series is conducted based on HJ-1A/B data. Three related issues, i.e. the optimal filter, time series decomposition, phenological features derivation are addressed. In addition, the effect of spatial and temporal resolution on the phenological features extraction is also discussed according to the comparison between the derived NDVI product and that extracted from MODIS. The results show that the Savitzky-Golay (S-G) filter is the best filter for the reconstruction of HJ NDVI time series. There is some difference for phenology derivation using “season” and “season + trend” depending on the absence/presence of breakpoints in the curve. The spatial details of phenological features can be built by the high-spatial time-series NDVI, showing a great potential in urban applications. Compared with the MODIS NDVI time series, HJ NDVI time series can get more detail information than overall phenological features because of its high spatio-temporal resolution.