Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/103475
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Andriolo, Umberto | - |
dc.contributor.author | Garcia-Garin, Odei | - |
dc.contributor.author | Vighi, Morgana | - |
dc.contributor.author | Borrell, Asunción | - |
dc.contributor.author | Gonçalves, Gil | - |
dc.date.accessioned | 2022-11-15T10:55:35Z | - |
dc.date.available | 2022-11-15T10:55:35Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 2072-4292 | pt |
dc.identifier.uri | https://hdl.handle.net/10316/103475 | - |
dc.description.abstract | The abundance of litter pollution in the marine environment has been increasing globally. Remote sensing techniques are valuable tools to advance knowledge on litter abundance, distribution and dynamics. Images collected by Unmanned Aerial Vehicles (UAV, aka drones) are highly efficient to map and monitor local beached (BL) and floating (FL) marine litter items. In this work, the operational insights to carry out both BL and FL surveys using UAVs are detailly described. In particular, flight planning and deployment, along with image products processing and analysis, are reported and compared. Furthermore, analogies and differences between UAV-based BL and FL mapping are discussed, with focus on the challenges related to BL and FL item detection and recognition. Given the efficiency of UAV to map BL and FL, this remote sensing technique can replace traditional methods for litter monitoring, further improving the knowledge of marine litter dynamics in the marine environment. This communication aims at helping researchers in planning and performing optimized drone-based BL and FL surveys. | pt |
dc.language.iso | eng | pt |
dc.publisher | MDPI | pt |
dc.relation | UIDB 00308/2020 | pt |
dc.relation | PTDC/EAM-REM/30324/2017 | pt |
dc.relation | 1MED15_3.2_M12_334; European Union- European Regional Development Fund- Interreg MED | pt |
dc.rights | openAccess | pt |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt |
dc.subject | Plastics | pt |
dc.subject | Environmental Monitoring | pt |
dc.subject | Beach Pollution | pt |
dc.subject | Ocean Pollution | pt |
dc.subject | Machine Learning | pt |
dc.subject | Drone | pt |
dc.subject | Coastal Monitoring | pt |
dc.title | Beached and Floating Litter Surveys by Unmanned Aerial Vehicles: Operational Analogies and Differences | pt |
dc.type | article | - |
degois.publication.firstPage | 1336 | pt |
degois.publication.issue | 6 | pt |
degois.publication.title | Remote Sensing | pt |
dc.peerreviewed | yes | pt |
dc.identifier.doi | 10.3390/rs14061336 | pt |
degois.publication.volume | 14 | pt |
dc.date.embargo | 2022-01-01 | * |
uc.date.periodoEmbargo | 0 | pt |
item.languageiso639-1 | en | - |
item.fulltext | Com Texto completo | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
crisitem.project.grantno | Institute for Systems Engineering and Computers at Coimbra - INESC Coimbra | - |
crisitem.author.researchunit | INESC Coimbra – Institute for Systems Engineering and Computers at Coimbra | - |
crisitem.author.orcid | 0000-0002-0185-7802 | - |
crisitem.author.orcid | 0000-0002-1746-0367 | - |
Appears in Collections: | I&D INESCC - Artigos em Revistas Internacionais FCTUC Matemática - Artigos em Revistas Internacionais |
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File | Description | Size | Format | |
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Beached-and-Floating-Litter-Surveys-by-Unmanned-Aerial-Vehicles-Operational-Analogies-and-DifferencesRemote-Sensing.pdf | 1.17 MB | Adobe PDF | View/Open |
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This item is licensed under a Creative Commons License