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dc.contributor.authorOlivetti, Diogo-
dc.contributor.authorCicerelli, Rejane Ennes-
dc.contributor.authorMartinez, Jean-Michel-
dc.contributor.authorAlmeida, Tati de-
dc.contributor.authorCasari, Raphael Augusto das Chagas Noqueli-
dc.contributor.authorBorges, Henrique Dantas-
dc.contributor.authorRoig, Henrique Llacer-
dc.date.accessioned2023-11-28T14:00:29Z-
dc.date.available2023-11-28T14:00:29Z-
dc.date.issued2023-06-21-
dc.identifier.citationOLIVETTI, Diogo et al. Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming. Drones, [S. l.], v. 7, n. 7, 410. DOU: https://doi.org/10.3390/drones7070410. Disponível em: https://www.mdpi.com/2504-446X/7/7/410.pt_BR
dc.identifier.urihttp://repositorio2.unb.br/jspui/handle/10482/46917-
dc.language.isoengpt_BR
dc.publisherMDPIpt_BR
dc.rightsAcesso Abertopt_BR
dc.titleComparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farmingpt_BR
dc.typeArtigopt_BR
dc.subject.keywordÁguapt_BR
dc.subject.keywordSensoriamento remotopt_BR
dc.subject.keywordAeronaves remotamente pilotadaspt_BR
dc.subject.keywordDronespt_BR
dc.subject.keywordClorofila-apt_BR
dc.subject.keywordCianobactériapt_BR
dc.rights.licenseCopyright: © 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/).pt_BR
dc.identifier.doihttps://doi.org/10.3390/drones7070410pt_BR
dc.description.abstract1This 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.pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-8199-5163-
dc.identifier.orcidhttps://orcid.org/0000-0003-3281-8512-
dc.contributor.affiliationUniversity of Brasília, Institute of Geosciencespt_BR
dc.contributor.affiliationUniversity of Brasília, Institute of Geosciencespt_BR
dc.contributor.affiliationUniversity of Brasília, Institute of Geosciencespt_BR
dc.contributor.affiliationCentre National de la Recherche Scientifique (CNRS), Géosciences Environnement Toulouse (GET), UMR5563, Institut de Recherche pour le Développement (IRD), Université Toulouse 3,pt_BR
dc.contributor.affiliationUniversity of Brasília, Institute of Geosciencespt_BR
dc.contributor.affiliationUniversity of Brasília, Institute of Geosciencespt_BR
dc.contributor.affiliationUniversity of Brasília, Institute of Geosciencespt_BR
dc.contributor.orcidhttps://orcid.org/0000-0002-0729-5767-
dc.description.unidadeInstituto de Geociências (IG)pt_BR
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