This study investigates the feasibility of utilizing time-series MODIS 250 m Normalized Difference Vegetation Index (NDVI) data from the year 2002 for discriminating rice cropping systems in the Mekong Delta, southern Vietnam. Data are processed using Empirical Mode Decomposition (EMD) and the Linear Mixture Model (LMM). The results indicate that EMD is a well-fitted filter for noise reduction of the time-series NDVI data. The classification results derived from the LMM showed an overall classification accuracy of 71.6% and a Kappa coefficient of 0.6. The lowest producer accuracy (50.1%) was observed for the single rainfed-rice crop because its temporal patterns could be confused with those of annual crops, and small rice planted parcels which had not been updated in the ground truth data. The results of this study support the validity of using this technique for regional mapping of rice growing areas.