Mapping rice cropping systems with optical imagery in multiple cropping regions is challenging due to cloud contamination and data availability; development of a phenology-based algorithm with a reduced data demand is essential. In this study, the Landsat-derived Renormalized Index of Normalized Difference Vegetation Index (RNDVI) was proposed based on two temporal windows in which the NDVI values of single and early (or late) rice display inverse changes, and then applied to discriminate rice cropping systems. The Poyang Lake Region (PLR), characterized by a typical cropping system of single cropping rice (SCR, or single rice) and double cropping rice (DCR, including early rice and late rice), was selected as a testing area. The results showed that NDVI data derived from Landsat time-series at eight to sixteen days captures the temporal development of paddy rice. There are two key phenological stages during the overlapping growth period in which the NDVI values of SCR and DCR change inversely, namely the ripening phase of early rice and the growing phase of single rice as well as the ripening stage of single rice and the growing stage of late rice. NDVI derived from scenes in two temporal windows, specifically early August and early October, was used to construct the RNDVI for discriminating rice cropping systems in the polder area of the PLR, China. Comparison with ground truth data indicates high classification accuracy. The RNDVI approach highlights the inverse variations of NDVI values due to the difference of rice growth between two temporal windows. This makes the discrimination of rice cropping systems straightforward as it only needs to distinguish whether the candidate rice type is in the period of growth (RNDVI<0) or senescence (RNDVI>0).