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and, indirectly, methane emission from rice-wetlands at subcontinental scales(Denier van der Gon et al 1999, van Leeuwen 1998).Classification of rice using radar image time seriesSAR remote sensing offers favorable capabilities for rice mapping and monitoring.The typical radar response to rice fields at different growing stages is the key factorfor discriminating rice from other land-use classes. Le Toan et al (1997) studied theradar response to rice fields at different growing stages. They distinguished threemain periods in the crop cycle: (1) sowing-transplanting, (2) growing, and (3) theafter-harvest period. They found a bridge-shaped backscatter pattern representing theradar signature of rice during the growing period (Fig. 1). In ERS, the SAR timeseries classification of rice can take place on the basis of this typical signature. LeToan demonstrated that detection of changes of 3 dB or more over the growing seasonindicates rice areas.The methodology of Le Toan works fine for extensive rice areas in flat terrainin the same growing stage. For smaller rice fields, however, this methodology doesnot work, especially not in mountainous terrain, where the dynamic range of backscatteris somewhat compressed (Verhoeven and van Leeuwen 1999). Also, the presenceof small rice fields in different growing stages is difficult to detect using thismethod.For classification of rice using radar time series, standard methodologies suchas maximum likelihood of iso-data clustering can yield unsatisfying results. A majordisadvantage of these techniques is that they ignore the typical time sequence of theRadar backscatteringSurfacecontribution InteractionVolumecontributionSowingTilleringSowingTilleringStemextensionFloweringStem extensionVegetative stageReproductive stageFig. 1. Radar backscatter response over a rice-growing cycle. Source:CEO-EWSE.Monitoring rainfed and irrigated rice in Southeast Asia . . . 159