Rice is a major economic crop in the Lower Mekong Subregion (LMS). Information on rice growing areas is thus vital for agricultural planning for the sake of food security. This study aimed to map rice cropping systems in LMS from timeseries MODIS NDVI data for 2010. We processed the time-series NDVI data using wavelet transform and crosscorrelation. The classification results were assessed using ground verification data. The results indicated that smooth NDVI profiles derived from wavelet transform reflected the temporal characteristics of rice crop phelonogy under different rice cropping systems, enabling us to select proper training patterns used in cross-correlation based classifier. The comparison between the classification map and ground verification data revealed that the results achieved from this classification approach was promising for regional mapping of rice cropping patterns. The overall accuracy and Kappa coefficient were 79.5 and 0.72 respectively.