The Dataset bibliography is a product of the Task Force on Remote Sensing of Marine Litter & Debris (RSMLD), is specific to the topic, and is updated periodically when new references are submitted by readers or task force members. If you would like your dataset publication included please send the details to Raisha Lovindeer using the following format:
Lastname1, Initials1., Lastname2, Initials2., etc. (Year). Full title of publication, Available online [url] from Name of Repository, DOI url
The data must meet the following requirements ‘Remote sensing’ AND ‘Marine litter and debris’
Datasets Bibliography
Acuña-Ruz, T., and Mattar B., C. (2020). Thermal infrared spectral database of marine litter debris in Archipelago of Chiloé, Chile, Available online [https://pangaea.de/] from PANGAEA, https://doi.org/10.1594/PANGAEA.919536
Blondeau-Patissier, David; Schroeder, Thomas; Diakogiannis, Foivos; Li, Zhibin (2022): CSIRO Sentinel-1 SAR image dataset of oil- and non-oil features for machine learning (Deep Learning). v1. CSIRO. Data Collection. https://doi.org/10.25919/4v55-dn16
Corbari, L., Maltese, A., Capodici, F., Mangano, M. C., Sarà, G., & Ciraolo, G. (2020). Indoor spectroradiometric characterization of plastic litters commonly polluting the Mediterranean Sea: toward the application of multispectral imagery. Scientific Reports, 10(1), 19850. https://doi.org/10.
Daisuke, S, Mitsuko, H., Daisuke, M., Koshiro, M., and Shin’ichiro, K. (2022) The BeachLitter Dataset v2022. SEANOE. https://doi.org/10.17882/85472
de Vries, R. V. F. and Garaba, S. P. (2023) Dataset of spectral reflectances and hypercubes of submerged plastic litter, including COVID-19 medical waste, pristine plastics, and ocean-harvested plastics, Available online [https://data.4tu.nl/] from 4TU, https://doi.org/10.4121/769cc482-b104-4927-a94b-b16f6618c3b3.v1
de Vries, R. V. F., Garaba, S. P., and Royer, S.-J.(2023) Dataset of spectral reflectances and hypercubes of submerged biofouled, pristine, and ocean-harvested marine litter, Available online [https://data.4tu.nl/] from 4TU, https://doi.org/10.4121/7c53b72a-be97-478b-9288-ff9c850de64b.v1
Đuraš, A., Wolf, B. J., Ilioudi, A., Palunko, I. and De Schutter, B. (2024) A dataset for detection and segmentation of underwater marine debris in shallow waters. Scientific Data, v. 11, no. 1, pp. 921, https://doi.org/10.1038/s41597-024-03759-2
English, D. C., and Hu, C. (2020) Field and laboratory measured floating matter reflectance initial results, Data set. Available on-line [http://ecosis.org] from the Ecological Spectral Information System (EcoSIS), https://doi.org/10.21232/NxTTJsta
Garaba, S. P., Arias, M., Corradi, P., Harmel, T., de Vries, R., and Lebreton, L. (2021). Concentration, anisotropic and apparent colour effects on optical reflectance properties of virgin and ocean-harvested plastics, J. Hazard. Mater., 406, 124290, Dataset in Supplementary Material https://doi.org/10.1016/j.jhazmat.2020.124290
Garaba, S. P., Castagna, A., Devriese, L. I., Dierssen, H. M., Everaert, G., Knaeps, E., Sterckx, S. (2021). Spectral reflectance measurements of dry and wet plastic materials, asphalt, concrete klinker from UV-350 nm to SWIR-2500 nm around Spuikom, Belgium. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.937185
Garaba, S. P. and Dierssen, H. M. (2017). Spectral reference library of 11 types of virgin plastic pellets common in marine plastic debris, Available online [https://ecosis.org] from the Ecological Spectral Information System (EcoSIS), https://doi.org/10.21232/C27H34
Garaba, S. P. and Dierssen, H. M. (2019). Spectral reflectance of washed ashore macroplastics, Available online https://ecosis.org] from the Ecological Spectral Information System (EcoSIS), https://doi.org/10.21232/ex5j-0z25
Garaba, S. P. and Dierssen, H. M. (2019). Spectral reflectance of dry and wet marine-harvested microplastics from Kamilo Point, Pacific Ocean, Available online [https://ecosis.org] from the Ecological Spectral Information System (EcoSIS), https://doi.org/10.21232/r7gg-yv83
Garaba, S. P. and Dierssen, H. M. (2019). Spectral reflectance of dry marine-harvested microplastics from North Atlantic and Pacific Ocean, Available online [https://ecosis.org] from the Ecological Spectral Information System (EcoSIS), https://doi.org/10.21232/jyxq-1m66
Goddijn-Murphy, L. (2022). TISPLALI. Ocean Scan. https://www.oceanscan.org/dataset/ee6a58ca-af2c-4813-a7ba-f2a099544c9a. DOI: 10.5281/zenodo.6409151
Hidaka, M., Murakami, K., Koshidawa, K., Kawahara, S., Sugiyama, D., Kako, S., Matsuoka, D.( 2023) BePLi dataset v1: beach plastic litter dataset version 1 for instance segmentation of beach plastic litter. Data Br. 48 https://doi.org/10.1016/j. dib.2023.109176
Hueni, A. (2018) APEX and AVIRIS-NG hyperspectral georectified radiance of artificially distributed PET bottles in two different lakes in Switzerland (Hallwilersee and Greifensee). Available online https://ares-observatory.ch/data/
Hu, C. (2021). Floating matter reflectance from HICO. Available online [https://ecosis.org] from Ecological Spectral Information System (EcoSIS), https://doi.org/10.21232/74LvC3Kr
Kikaki, K., Kakogeorgiou, I., Mikeli, P., Raitsos, DE., Karantzalos, K. (2022). MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data. PLoS ONE 17(1): e0262247. https://doi.org/10.1371/
Knaeps, E., Strackx, G., Meire, D., Sterckx, S., Mijnendonckx, J., and Moshtaghi, M. (2020). Hyperspectral reflectance of marine plastics in the VIS to SWIR, Available online [https://data.4tu.nl/] from 4TU.Centre for Research Data, https://doi.org/10.4121/12896312.v2
Koestner Daniel, Foster Robert, El-Habashi Ahmed, Cheatham Shea, Stramski Dariusz, Reynolds Rick (2024). Measurements of the inherent optical properties of aqueous suspensions of microplastics and contrasting seawater samples. SEANOE. https://doi.org/10.17882/98404
Leone, G., Catarino, A., De Keukelaere, L., Bossaer, M., Knaeps, E., and Everaert, G. (2021) Hyperspectral reflectance dataset for dry, wet and submerged plastics in clear and turbid water. Available online from Marine Data Archive [https://marinedataarchive.org]. https://doi.org/10.14284/530
Maharjan N. (2022). Plastic detection in river using deep learning techniques. Available online [https://github.com] from Github, https://github.com/Nisha484/Nisha/tree/main/Datagithub
Olyaei, M., Ebtehaj, A., & Ellis, C. R. (2024) A hyperspectral reflectance database of plastic debris for river ecosystems. Zenodo. https://doi.org/10.5281/zenodo.10723548
Papakonstantinou, Apostolos, Moustakas, Argyrios, Kolokoussis, Polychronis, Papageorgiou, Dimitrios, De Vries, Robin, & Topouzelis, Konstantinos. (2022). Airborne spectral reflectance dataset of submerged plastic targets in a coastal environment (SUPPLEMENTARY DATA FILES). Available online [https://zenodo.org] from Zenodo. https://doi.org/10.5281/zenodo.7043319
Tasseron P, van Emmerik T, Schreyers L, Biermann L, and Peller J. (2021) Hyperspectral plastics dataset supplementary to the paper ‘Advancing floating plastic detection from space using hyperspectral imagery, Available online [https://data.4tu.nl/] from 4TU.Centre for Research Data https://doi.org/10.4121/14518278.v3.
Topouzelis K. (2020) PLP2019 dataset, Available online [https://zenodo.org] from Zenodo,
http://doi.org/10.5281/zenodo.3752719
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