SWIR hyperspectral data cubes for plastics detection in the environment

The dataset contains 9 hyperspectral cubes related to paper "Attention‑Gated U‑Net for Robust Cross‑Domain Plastic Waste Segmentation using UAV Based Hyperspectral SWIR Sensor" by S. Bouchelaghem, M. Balsi, M. Moroni, submitted in November 2025 to Remote Sensing Applications: Society and Environment. Corresponding author: [e-mail]
Data were acquired using a push-broom SWIR camer mounted on a drone, in controlled natural environments, where sorted plastics objects were placed on the ground.
The files contain hyperspectral cubes organized as 81 layers corresponding to wavelengths from 900 to 1700 nm, sampled every 10nm in the folder "drone_cube". Layers from 900 to 930 are dummy (filled with zeros) because they were not actually acquired. For each cube, manually-drawn masks are provided, for labelling according to plastics polymer or other material in the folder "masks". Additional folder "Training_dataset2" include the training used for the deep learning model.