The vegetation that develops in the riparian zone has an important influence on many processes within the hydrosystem. As a result, it is often at the heart of management practices designed to influence the river's ecological and hydraulic functioning. The implementation of coherent management actions, integrating the various river-related issues and stakeholders, requires diagnosis and appropriate planning at basin scale. Remote sensing can be used to obtain up-to-date data on the state of riparian vegetation over large areas at low cost. The aim of this thesis is to develop tools for mapping riparian vegetation and to assess their value for riparian management. Firstly, a literature review was carried out to obtain an overview of the use of remote sensing for the study of riparian vegetation. The results show a close relationship between the tools used, the riparian vegetation characteristics studied and the extent mapped. High-resolution data are rarely used for rivers over 100 km in length, or for mapping species composition. A significant proportion of the studies carried out relate to the dynamics of riparian ecosystems, and aerial and satellite images are valued for their availability as time series. We identified opportunities to seize with the increased availability of high-resolution data in little-studied regions, for large areas and as time series. Some approaches have reached an operational level and are now being used for management purposes. To transfer remote sensing approaches to riparian managers, we suggest mutualizing achievements by producing robust, open-source tools that can be adapted to each specific project. Secondly, we focused on mapping the above-ground biomass of riparian forests, on which several key functions of riparian systems depend. Specifically, LiDAR data were used in a tree-centric approach to map above-ground biomass in riparian forests along 200 km of rivers and their associated floodplains, in the Semois and Chiers watersheds. Two approaches were tested, based on a LiDAR ...