Spring vegetation green-up date in China inferred from SPOT NDVI data: A multiple model analysis

Phenological changes are closely related to the carbon cycle of terrestrial ecosystems, and satellite data have been widely used in large scale phenological research. Numerous methods have been developed to reconstruct distinct satellite derived vegetation signals from continuous vegetation index time series and to track the points corresponding to important phenological events. In this study, we perform a multiple-method investigation of the spring vegetation growth onset phenology in temperate China north of 30°N with NDVI (normalized difference vegetation index) data produced from SPOT satellites. The results indicated that the spring onset dates estimated from five different methods show similar spatial pattern along latitudinal or altitudinal gradients, but with significant variances in the dates. In most areas (76% of pixels), the standard deviation (SD) of the estimated spring onset dates from different methods is within one month, while in a few places (2% of pixels), mostly agricultural cropland, the SD is more than 60 days. Comparing the satellite derived green-up onset dates against the gross primary productivity (GPP) time series curves acquired from six eddy covariance towers further highlights the strengths and limits of different methods in estimating phenological events. In a vast region with diverse vegetation types and physical environment, it is critical to choose the “right” method for the “right” place. Generally climate factors such as temperature and precipitation play an important role in controlling the start of vegetation growth in temperate China. Yet this climate-phenology relationship varies largely across different regions and vegetation types.

► We perform a multi-method investigation of spring phenology in temperate China. ► Satellite derived green-up onset dates are compared with flux measurements in six sites. ► The comparison suggests critical need to choose “right” method for “right” place. ► Climate plays an important role in controlling spring phenology in temperate China.