<p>Aquatic vegetation found in wetland ecosystems play a critical role in governing biodiversity, water purification, flood regulation, and carbon sequestration. This study presents a comprehensive analysis of the seasonal dynamics of aquatic vegetation within 500 selected wetlands of India, employing multispectral satellite observations and a classification tree model. We develop a framework for the classification of aquatic vegetation into three main classes: submerged vegetation, algae or floating vegetation, and emergent vegetation. Our approach involves the utilization of extensive field data and various satellite-observed spectral indices tuned for aquatic vegetation delineation. The classification tree model exhibits good accuracy in classifying aquatic vegetation types, ranging from 87.8% for emergent vegetation to 94.3% for submerged vegetation class. We observed distinct spatio-temporal patterns of aquatic vegetation across different wetlands of India, with most wetlands showing peak submerged vegetation during the pre-monsoon season, while others exhibiting higher emergent and floating vegetation during the post-monsoon period. Among the 500 wetlands studied, significant declining trends in area were identified in 86 wetlands for emergent, 78 for floating and 88 for submerged aquatic vegetation class. We established regression-based relationship between the dynamics of aquatic vegetation and meteorological parameters, mainly rainfall and land surface temperature. We observed that changes in weather pattern influence the overall growth and distribution of aquatic vegetation in wetlands. The developed classification tree model offers a powerful tool for monitoring aquatic vegetation responses to environmental changes and assist in wetland conservation efforts.</p>