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Water hyacinth (Eichhornia crassipes) is one of the most aggressive and lethal free-floating aquatic weed that degrades and chokes freshwater ecosystems and threatens aquatic life. Early detection and up-to-date information regarding its distribution is, therefore, crucial in understanding its spatial configuration and propagation rate. The present study, thus, sought to map the seasonal dynamics of invasive water hyacinth, in Greater Letaba river system in Limpopo Province, South Africa, using Sentinel-2 data and Linear Discriminant Analysis (LDA). Classification test results showed that seasonal water hyacinth distribution patterns can be accurately detected and mapped, using Sentinel-2 data with high accuracies. Water hyacinth was mapped with an overall accuracy of 80.79% during the wet season, and 79.04% during the dry season, with kappa coefficients of 0.76 and 0.724, respectively, using combined vegetation indices and spectral bands. The use of spectral bands (wet: 79.48% and dry: 75.98%) and vegetation indices (wet: 76.42% and dry: 74.42%) as independent dataset yielded slighter lower accuracies when compared to the use of the combined dataset. Further, areal coverage results showed that approximately 63.82% and 28.34% of the river system was infested with water hyacinth during wet and dry seasons, respectively. Findings of this study underscore the importance of new generation sensors in detecting and mapping the seasonal distribution of water hyacinth in river systems. Overall such findings provide a baseline or provide a framework for developing invasive aquatic species management and eradication strategies.