Wetlands worldwide are becoming increasingly degraded, and this has motivated many attempts to manage and restore wetland ecosystems. Restoration actions require a large resource investment, so it is critical to measure the outcomes of these management actions. We evaluated the restoration of floodplain wetland vegetation across a chronosequence of land uses, using remote sensing analyses. We compared the Landsat-based fractional cover of restoration areas with river red gum and lignum reference communities, which functioned as a fixed target for restoration, over three time periods: (i) before agricultural land use (1987–1997); (ii) during the peak of agricultural development (2004–2007); and (iii) post-restoration of flooding (2010–2015). We also developed LiDAR-derived canopy height models (CHMs) for comparison over the second and third time periods. Inundation was crucial for restoration, with many fields showing little sign of similarity to target vegetation until after inundation, even if agricultural land uses had ceased. Fields cleared or cultivated for only one year had greater restoration success compared to areas cultivated for three or more years. Canopy height increased most in the fields that were cleared and cultivated for a short duration, in contrast to those cultivated for >12 years, which showed few signs of recovery. Restoration was most successful in fields with a short development duration after the intervention, but resulting dense monotypic stands of river cooba require future monitoring and possibly intervention to prevent sustained dominance. Fields with intensive land use histories may need to be managed as alternative, drier flood-dependent vegetation communities, such as black box (Eucalyptus largiflorens) grasslands. Remotely-sensed data provided a powerful measurement technique for tracking restoration success over a large floodplain.