Hyperspectral dataset and associated MATLAB scripts supplementary to the paper 'Towards Robust River Plastic Detection: Combining Lab and Field-based Hyperspectral Imagery'

doi:10.4121/20343012.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/20343012
Datacite citation style:
Paolo Tasseron; Louise Schreyers; Tim van Emmerik; Joseph Peller; Lauren Biermann (2022): Hyperspectral dataset and associated MATLAB scripts supplementary to the paper 'Towards Robust River Plastic Detection: Combining Lab and Field-based Hyperspectral Imagery'. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20343012.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This database is the supplementary material of Tasseron et al., (2022): 'Towards Robust River Plastic Detection: Combining Lab and Field-based Hyperspectral Imagery' [Submitted and currently under review], preprint available online at https://doi.org/10.31223/X5RW7V. The dataset contains raw images, MATLAB scripts used for training classifier algorithms, trained pipelines, required toolboxes and labelled training datasets used in subsequent analyses. 

history
  • 2022-07-22 first online, published, posted
publisher
4TU.ResearchData
format
Zipped folder containing: - Image files used in analyses (.hdr, .mat, .raw) - MATLAB scripts (.m) - Trained pipelines to be imported in MATLAB(.mat) - Toolboxes (.m) - Training datasets to be imported in MATLAB (.mat)
funding
  • NWO Open Mind grant 18127
  • 4TU.Federation Plantenna project
  • Veni research program The River Plastic Monitoring Project with project number 18211
organizations
Hydrology and Quantitative Water Management, Wageningen University & Research

IMEC

OnePlanet Research Center

DATA

files (2)