Remote sensing is one of the most useful tools for mapping and studying vegetation because of the advantages of synoptic view (in time and space) compared to traditional in situ survey. Remotely sensed vegetation indices (VIs) derived from airborne and satellite images represent a powerful and effective way to monitor vegetation status, growth, and bio-physical parameters. This is especially true for aquatic ecosystems, whose characterization is extremely time-consuming and expensive. This work runs a comparison of different VIs in mapping aquatic vegetation (AV) and assesses the capabilities of two recently developed indices specifically designed to analyze aquatic ecosystems: the Normalized Difference Aquatic Vegetation Index (NDAVI) and the Water Adjusted Vegetation Index (WAVI). Three aquatic ecosystems in northern Italy are studied: Lake Garda, Mantua lake system, and Venice Lagoon. A multispectral and multisensor dataset is utilized, ranging from aerial to satellite data, with varying spatial (2–90 m) and spectral resolutions ($ 0.01 - 0.15~micro{hbox{m}}$). Literature VIs (NDVI, SAVI, and EVI), and two recently proposed VIs (NDAVI and WAVI) are derived and their performance in terms of both AV mapping capabilities and vegetation features separability is assessed. Best performances are shown in most of the cases by the recently introduced indices and by WAVI, in particular, thus demonstrating the usefulness of a specific index for mapping AV. Their use in integration with other VIs can be envisaged in order to effectively describe a wide range of AV features from multispectral remotely sensed data.