Aquatic vegetation is not only an important group/type of shallow lakes, but also an indicator of lake environment. It plays an important role in ecological restoration and management of shallow lakes. To monitor real-time spatial-temporal distributions of aquatic vegetation in this study, classification tree(CT) model for mapping aquatic vegetation types was developed through HJ-CCD images. Aquatic vegetation of Lake Taihu was classified into emergent, floating-leaved and submerged vegetation by CT model. Living histories of dominant species of submerged vegetation were extracted from literatures and surveys. Combining with living histories and multi-temporal HJ-CCD images, a method was proposed for mapping dominant species of submerged vegetation of Lake Taihu. Based on the method, submerged vegetation in Lake Taihu was subdivided into seven dominant species. By verification of the using field survey points, the overall accuracies of CT model for mapping aquatic vegetation were 83.04%, 81.82% and 85.47%, respectively during three periods of the investigations on July, August and September of 2013. The overall accuracy of dominant species of submerged vegetation was 62.20%. Therefore, CT model and the method for mapping dominant species of submerged vegetation proposed in this study could be helpful for lake management including guiding aquatic vegetation harvesting and ecological restoration. Meanwhile, it lays foundation for further research of historical changes in submerged vegetation of Lake Taihu.