Honghu Lake, one of the seven largest fresh-water lakes in China, is well known for its ecological and economic importance, as well as its rapid changes in recent years. This study investigates the potential of using remote sensing to map and monitor aquatic vegetation changes in Honghu Lake on a large scale. Landsat images dated July 27, 2000, July 9, 2002, and July 17, 2008, and CBERS image dated August 12, 2005, are employed to map the aquatic vegetation distribution in the lake. A hybrid classiﬁcation method, combining the power of the decision tree classifier, naïve Bayes classifier, and supporting vector machine classifier is used to distinguish different wetland types. A novel polar coordinate map method is proposed to map the changes of aquatic vegetation on a large scale. The map demonstrates vegetation patch size changes and percentage changes in the whole lake directions during four periods. Validation using in situ surveys and historical ancillary data suggests that this approach could map the distribution and monitor the changes of aquatic vegetation on a large scale efficiently.