Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming

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Autor(es): dc.contributorUniversity of Brasília, Institute of Geosciences-
Autor(es): dc.contributorUniversity of Brasília, Institute of Geosciences-
Autor(es): dc.contributorUniversity of Brasília, Institute of Geosciences-
Autor(es): dc.contributorCentre National de la Recherche Scientifique (CNRS), Géosciences Environnement Toulouse (GET), UMR5563, Institut de Recherche pour le Développement (IRD), Université Toulouse 3,-
Autor(es): dc.contributorUniversity of Brasília, Institute of Geosciences-
Autor(es): dc.contributorUniversity of Brasília, Institute of Geosciences-
Autor(es): dc.contributorUniversity of Brasília, Institute of Geosciences-
Autor(es): dc.contributorhttps://orcid.org/0000-0002-0729-5767-
Autor(es): dc.creatorOlivetti, Diogo-
Autor(es): dc.creatorCicerelli, Rejane Ennes-
Autor(es): dc.creatorMartinez, Jean-Michel-
Autor(es): dc.creatorAlmeida, Tati de-
Autor(es): dc.creatorCasari, Raphael Augusto das Chagas Noqueli-
Autor(es): dc.creatorBorges, Henrique Dantas-
Autor(es): dc.creatorRoig, Henrique Llacer-
Data de aceite: dc.date.accessioned2024-10-23T15:37:49Z-
Data de disponibilização: dc.date.available2024-10-23T15:37:49Z-
Data de envio: dc.date.issued2023-11-27-
Data de envio: dc.date.issued2023-11-27-
Data de envio: dc.date.issued2023-06-21-
Fonte completa do material: dc.identifierhttp://repositorio2.unb.br/jspui/handle/10482/46917-
Fonte completa do material: dc.identifierhttps://doi.org/10.3390/drones7070410-
Fonte completa do material: dc.identifierhttps://orcid.org/0000-0002-8199-5163-
Fonte completa do material: dc.identifierhttps://orcid.org/0000-0003-3281-8512-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/887900-
Descrição: dc.descriptionThis work aimed to assess the potential of unmanned aerial vehicle (UAV) multi- and hyper-spectral platforms to estimate chlorophyll-a (Chl-a) and cyanobacteria in experimental fishponds in Brazil. In addition to spectral resolutions, the tested platforms differ in the price, payload, imaging system, and processing. Hyperspectral airborne surveys were conducted using a push-broom system 276-band Headwall Nano-Hyperspec camera onboard a DJI Matrice 600 UAV. Multispectral airborne surveys were conducted using a global shutter-frame 4-band Parrot Sequoia camera onboard a DJI Phantom 4 UAV. Water quality field measurements were acquired using a portable fluorometer and laboratory analysis. The concentration ranged from 14.3 to 290.7 µg/L and from 0 to 112.5 µg/L for Chl-a and cyanobacteria, respectively. Forty-one Chl-a and cyanobacteria bio-optical retrieval models were tested. The UAV hyperspectral image achieved robust Chl-a and cyanobacteria assessments, with RMSE values of 32.8 and 12.1 µg/L, respectively. Multispectral images achieved Chl-a and cyanobacteria retrieval with RMSE values of 47.6 and 35.1 µg/L, respectively, efficiently mapping the broad Chl-a concentration classes. Hyperspectral platforms are ideal for the robust monitoring of Chl-a and CyanoHABs; however, the integrated platform has a high cost. More accessible multispectral platforms may represent a trade-off between the mapping efficiency and the deployment costs, provided that the multispectral cameras offer narrow spectral bands in the 660–690 nm and 700–730 nm ranges for Chl-a and in the 600–625 nm and 700–730 nm spectral ranges for cyanobacteria.-
Descrição: dc.descriptionInstituto de Geociências (IG)-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherMDPI-
Direitos: dc.rightsAcesso Aberto-
Direitos: dc.rightsCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).-
Palavras-chave: dc.subjectÁgua-
Palavras-chave: dc.subjectSensoriamento remoto-
Palavras-chave: dc.subjectAeronaves remotamente pilotadas-
Palavras-chave: dc.subjectDrones-
Palavras-chave: dc.subjectClorofila-a-
Palavras-chave: dc.subjectCianobactéria-
Título: dc.titleComparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional – UNB

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