WasteDump-Dataset: YREB and Enhanced Global Dumpsite Annotations for Unregulated Waste Dump Segmentation

This dataset supports the paper "Label-Efficient Mapping of Unregulated Waste Dumps via Mixed Supervision with Feature Masked Recovery". It contains two parts: Part 1 - YREB Dataset: 16,429 samples (256x256 patches) from 11 administrative regions along the Yangtze River Economic Belt, China. Includes high-resolution satellite images (~0.26m spatial resolution), pixel-level binary masks (binary TIFF format, 0=background, 255=waste dump), and image-level labels. Pixel-level masks were manually annotated by expert interpreters using ENVI software. Part 2 - Enhanced Global Dumpsite Annotations: Pixel-level segmentation masks (binary TIFF format, 0=background, 255=waste dump) for the Global Dumpsite dataset (Sun et al., 2023, Nature Communications), spanning 7 countries with 0.3-1.0m spatial resolution. The original images are available from the source paper. Our contribution is the fine-grained pixel-level delineation performed using Labelme software. Code available at: https://github.com/rsshenli-geoai/SAM-FMR