SWIR hyperspectral data cubes for plastics detection in the environment
Description
The dataset contains 7 hyperspectral cubes related to paper "Plastic litter detection in the environment by hyperspectral aerial remote sensing and machine learning" by M. Balsi, M. Moroni, S. Bouchelaghem, submitted in February 2025 to Remote Sensing. Corresponding author: marco.balsi@uniroma1.it 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. 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. Additional folders include visible images showing the experimental setup, and .mat files of the cubes for use directly in Matlab. The latter files contain layers from 940 to 1340 nm and from 1460 to 1680 nm (total 60 layers). Others were removed because noisy or empty.
Files
Steps to reproduce
Please refer to the paper cited in the description, or to the corrisponding author: marco.balsi@uniroma1.it