Vegetation phenology monitoring method using time-series MODIS LAI data

Vegetation phenology can provide important informations which reflect the response of vegetation to climate and environment. Recently, remote sensing has become a new way to monitor vegetation phenology. Phenology from remote sensing has been widely used to monitor the response to climate. However, there were very few regional-to-global phenology products that limited the study and application of phenology. Based on the summary of existing methods, the paper proposed a new method which is more universal, stable and practical. This method was employed in China using time-series MODIS LAI data in 2007. The results were validated with ground phenology observations and MLCD data. The root mean square errors (RMSE) for different vegetation type were 4.0～33.5, the mean absolute errors were ?20.6～15.3 and the correlations were 0.404～0.887. By comparison with MLCD data, the success rate and the accuracy of the method have been highly improved.