Effective catchment monitoring requires an integrative approach for selecting remotely sensed data to monitor land-cover change. Catchment analyses and monitoring requirements in the Maroochy and Mooloolah River Catchments (south-east Queensland) were addressed by linking government and community information needs to appropriate scales of remotely sensed data and processing routines. A hybrid image classification approach applied to Landsat Thematic Mapper image data acquired in 1988 and 1997 provided catchment scale land-cover maps (with accuracies of 73% and 84%). Land-cover change maps derived from post-classification comparison provided information on the spatial distribution and type of land-cover changes between 1988–1997. Land-cover change was dominated by activities related to urban residential expansion (suburban and rural residential) and agricultural expansion (sugar cane farms). Significant spatial variations in the geometric registration accuracy of the image data sets and classification accuracies produced moderate to low change detection accuracies. However, the framework and community consultation used for selecting and processing data ensured the resource managers and community groups were fully aware of the limitations of the land-cover change mapping process and that the output images were suitable for incorporating in resource monitoring activities.