Monitoring fine-scale vegetation processes over wider spatial extents is often logistically challenging. We demonstrate a practical approach for monitoring high-resolution (i.e sub-meter) vegetation cover changes using UAV-mounted multispectral cameras. We use the post-fire shrublands of the Cape Floristic Region, South Africa as a case study. Repeated NDVI images of post-fire sites were generated biannually over three years using UAV-mounted multispectral cameras and commercial, image-processing software. We applied a procedure for identifying and correcting temporal radiometric noise in repeated NDVI images using pseudoinvariant features (PIFs). We then extracted vegetation cover data using NDVI thresholding. The quality of UAV-based vegetation cover data was assessed using detailed ground-truthing. Relative radiometric image normalization reduced radiometric noise in NDVI data and resulted in stronger correlations between UAV-based and ground-based area cover measurements over time. UAV-mounted multispectral cameras are effective high-resolution vegetation monitoring tools which could help ecologists to investigate fine-scale vegetation processes across wider spatial extents.