Understanding macroplastic transport in rivers and having accurate macroplastic emissions estimates are essential to address current and future challenges in waste management, in the context of an increase in plastic production and consumption. Information about macroplastic fluxes in rivers remains scarce and most rivers remain ungauged. Model estimates of macroplastic transport often disagree with field-based estimates, and neglect the role floating vegetation might play in accumulating and transporting plastic debris. The aim of this research is to quantify the role of vegetation in macroplastic transport in rivers. The first objective is to estimate the contribution of floating aquatic vegetation to macroplastic propagation in rivers, using field measurement techniques. Secondly, we focus on determining the distinct spectral signatures of both floating aquatic vegetation and plastic in rivers, in order to build a classification algorithm for automatic detection using satellite imagery. The spectral signatures of macroplastic and floating vegetation will be studied in details in a laboratory setting, using a multispectral camera. The same sensor will then be mounted on a UAV (Unmanned Aerial Vehicle) and various indices and classification algorithms will be tested on images collected in the field. Thirdly, we will use freely available satellite imagery to estimate the abundance of vegetation and macroplastic in one river system, the Saigon river in Vietnam over 2 to 4 years. Finally, we will evaluate the robustness and relevance of our remote sensing detection tool for another river system with floating aquatic vegetation presence, such as the Mekong river.