{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T00:47:05Z","timestamp":1774658825907,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,16]],"date-time":"2021-04-16T00:00:00Z","timestamp":1618531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Region of Sardinia (Italy)","award":["TEMPUS POR\/FESR Sardegna 2014 \u2013 2020 Asse 1 Azione 1.1.3 Strategia 2"],"award-info":[{"award-number":["TEMPUS POR\/FESR Sardegna 2014 \u2013 2020 Asse 1 Azione 1.1.3 Strategia 2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An automatic custom-made procedure is developed to identify macroplastic debris loads in coastal and marine environment, through hyperspectral imaging from unmanned aerial vehicles (UAVs). Results obtained during a remote-sensing field campaign carried out in the seashore of Sassari (Sardinia, Italy) are presented. A push-broom-sensor-based spectral device, carried onboard a DJI Matrice 600 drone, was employed for the acquisition of spectral data in the range 900\u22121700 nm. The hyperspectral platform was realized by assembling commercial devices, whereas algorithms for mosaicking, post-flight georeferencing, and orthorectification of the acquired images were developed in-house. Generation of the hyperspectral cube was based on mosaicking visible-spectrum images acquired synchronously with the hyperspectral lines, by performing correlation-based registration and applying the same translations, rotations, and scale changes to the hyperspectral data. Plastics detection was based on statistically relevant feature selection and Linear Discriminant Analysis, trained on a manually labeled sample. The results obtained from the inspection of either the beach site or the sea water facing the beach clearly show the successful separate identification of polyethylene (PE) and polyethylene terephthalate (PET) objects through the post-processing data treatment based on the developed classifier algorithm. As a further implementation of the procedure described, direct real-time processing, by an embedded computer carried onboard the drone, permitted the immediate plastics identification (and visual inspection in synchronized images) during the UAV survey, as documented by short video sequences provided in this research paper.<\/jats:p>","DOI":"10.3390\/rs13081557","type":"journal-article","created":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T06:35:53Z","timestamp":1618814153000},"page":"1557","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":67,"title":["High-Resolution Aerial Detection of Marine Plastic Litter by Hyperspectral Sensing"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3571-2353","authenticated-orcid":false,"given":"Marco","family":"Balsi","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazione, Elettronica e Telecomunicazioni (DIET), Universit\u00e0 di Roma La Sapienza, 00184 Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6982-4989","authenticated-orcid":false,"given":"Monica","family":"Moroni","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Civile, Edile e Ambientale (DICEA), Universit\u00e0 di Roma La Sapienza, 00184 Rome, Italy"}]},{"given":"Valter","family":"Chiarabini","sequence":"additional","affiliation":[{"name":"KIM-RemoteSensing GmbH, 9020 Klagenfurt am W\u00f6rthersee, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4098-5492","authenticated-orcid":false,"given":"Giovanni","family":"Tanda","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti (DIME), Universit\u00e0 Degli Studi di Genova, 16145 Genoa, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.marpolbul.2014.12.041","article-title":"The impact of debris on marine life","volume":"92","author":"Gall","year":"2015","journal-title":"Mar. Pollut. Bull."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"447","DOI":"10.3389\/fmars.2019.00447","article-title":"Toward the integrated marine debris observing system","volume":"6","author":"Maximenko","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez-Vicente, V., Clark, J.R., Corradi, P., Aliani, S., Arias, M., Bochow, M., Bonnery, G., Cole, M., C\u00f3zar, A., and Donnelly, R. (2019). Measuring marine plastic debris from space: Initial assessment of observation requirements. Remote Sens., 11.","DOI":"10.3390\/rs11202443"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2665","DOI":"10.5194\/essd-12-2665-2020","article-title":"Hyperspectral longwave infrared reflectance spectra of naturally dried algae, anthropogenic plastics, sands and shells","volume":"12","author":"Garaba","year":"2020","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/S0003-2670(98)00012-9","article-title":"Plastic material identification with spectroscopic near infrared imaging and artificial neural networks","volume":"361","author":"Wienke","year":"1998","journal-title":"Anal. Chim. Acta"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2205","DOI":"10.3390\/s150102205","article-title":"PET and PVC separation with hyperspectral imagery","volume":"15","author":"Moroni","year":"2015","journal-title":"Sensors"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Balsi, M., Esposito, S., and Moroni, M. (2018, January 8\u201310). Hyperspectral characterization of marine plastic litters. Proceedings of the 2018 IEEE International Workshop on Metrology for the Sea, Learning to Measure Sea Health Parameters (MetroSea), Bari, Italy.","DOI":"10.1109\/MetroSea.2018.8657875"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1080\/07038992.2016.1207484","article-title":"Remote sensing technologies for enhancing forest inventories: A review","volume":"42","author":"White","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2427","DOI":"10.1080\/01431161.2016.1252477","article-title":"Forestry applications of UAVs in Europe: A review","volume":"38","author":"Torresan","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s11119-012-9274-5","article-title":"The application of small unmanned aerial systems for precision agriculture: A review","volume":"13","author":"Zhang","year":"2012","journal-title":"Precis. Agric."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"779","DOI":"10.5424\/sjar\/2009074-1092","article-title":"Review. Precision viticulture. Research topics, challenges and opportunities in site-specific vineyard management","volume":"7","author":"Rosell","year":"2009","journal-title":"Span. J. Agric. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"012034","DOI":"10.1088\/1742-6596\/1224\/1\/012034","article-title":"Use of multispectral and thermal imagery in precision viticulture","volume":"1224","author":"Tanda","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Tanda, G., Balsi, M., Fallavollita, P., and Chiarabini, V. (2020). A UAV-based thermal-imaging approach for the monitoring of urban landfills. Inventions, 5.","DOI":"10.3390\/inventions5040055"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.isprsjprs.2015.10.004","article-title":"Remote sensing platforms and sensors: A survey","volume":"115","author":"Toth","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.marpolbul.2017.11.011","article-title":"Concept for a hyperspectral remote sensing algorithm for floating marine macro plastics","volume":"126","author":"Peters","year":"2018","journal-title":"Mar. Pollut. Bull."},{"key":"ref_17","first-page":"11699","article-title":"Sensing ocean plastics with an airborne hyperspectral shortwave infrared imager","volume":"52","author":"Garaba","year":"2018","journal-title":"Environ. Sci. Technol."},{"key":"ref_18","first-page":"175","article-title":"Detection of floating plastics from satellite and unmanned aerial systems (Plastic Litter Project 2018)","volume":"79","author":"Topouzelis","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Topouzelis, K., Papageorgiou, D., Karagaitanakis, A., Papakonstantinou, A., and Ballesteros, M.A. (2020). Remote sensing of sea surface artificial floating plastic targets with Sentinel-2 and unmanned aerial systems (Plastic Litter Project 2019). Remote Sens., 12.","DOI":"10.3390\/rs12122013"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"S17","DOI":"10.1016\/j.rse.2007.12.015","article-title":"Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean","volume":"113","author":"Gao","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"10228","DOI":"10.3390\/s120810228","article-title":"Mosaicing of hyperspectral images: The application of a spectrograph imaging device","volume":"12","author":"Moroni","year":"2012","journal-title":"Sensors"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"012007","DOI":"10.1088\/1742-6596\/1249\/1\/012007","article-title":"Vegetation monitoring via a novel push-broom-sensor-based hyperspectral device","volume":"1249","author":"Moroni","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.rse.2016.03.021","article-title":"Mapping tree species in tropical seasonal semi-deciduous forests with hyperspectral and multispectral data","volume":"179","author":"Ferreira","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1111\/j.1469-1809.1936.tb02137.x","article-title":"The use of multiple measurements in taxonomic problems","volume":"7","author":"Fisher","year":"1936","journal-title":"Ann. Eugen."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","article-title":"Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy","volume":"27","author":"Peng","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/8\/1557\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:49:06Z","timestamp":1760161746000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/8\/1557"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,16]]},"references-count":25,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["rs13081557"],"URL":"https:\/\/doi.org\/10.3390\/rs13081557","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,16]]}}}