Deep Learning Image Segmentation of Sandy Beaches in Southeastern Australia

The collection includes beach coastlines from Southeastern Australia, specifically Victoria and New South Wales, used to train an image segmentation model using the U-Net deep learning architecture for mapping sandy beaches. The dataset contains polygons that represent the outline or extent of the raster images and polygons drawn by citizen-scientists. Additionally, we provide the trained model itself, which can be utilized for further evaluation or refined through fine-tuning. The resulting predictions are also available in Shapefiles format, which can be loaded to NationalMap. This collection supplements the publication: Regional-Scale Image Segmentation of Sandy Beaches: Comparison of Training and Prediction Across Two Extensive Coastlines in Southeastern Australia (Yong et al. 2025)