Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UnB |
Texto Completo: | http://repositorio2.unb.br/jspui/handle/10482/46917 https://doi.org/10.3390/drones7070410 https://orcid.org/0000-0002-8199-5163 https://orcid.org/0000-0003-3281-8512 |
Resumo: | This 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. |
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Olivetti, DiogoCicerelli, Rejane EnnesMartinez, Jean-MichelAlmeida, Tati deCasari, Raphael Augusto das Chagas NoqueliBorges, Henrique DantasRoig, Henrique LlacerUniversity of Brasília, Institute of GeosciencesUniversity of Brasília, Institute of GeosciencesUniversity of Brasília, Institute of GeosciencesCentre National de la Recherche Scientifique (CNRS), Géosciences Environnement Toulouse (GET), UMR5563, Institut de Recherche pour le Développement (IRD), Université Toulouse 3,University of Brasília, Institute of GeosciencesUniversity of Brasília, Institute of GeosciencesUniversity of Brasília, Institute of Geoscienceshttps://orcid.org/0000-0002-0729-57672023-11-28T14:00:29Z2023-11-28T14:00:29Z2023-06-21OLIVETTI, 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.http://repositorio2.unb.br/jspui/handle/10482/46917https://doi.org/10.3390/drones7070410https://orcid.org/0000-0002-8199-5163https://orcid.org/0000-0003-3281-8512engMDPICopyright: © 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/).info:eu-repo/semantics/openAccessComparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farminginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleÁguaSensoriamento remotoAeronaves remotamente pilotadasDronesClorofila-aCianobactériaThis 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.Instituto de Geociências (IG)reponame:Repositório Institucional da UnBinstname:Universidade de Brasília (UnB)instacron:UNBLICENSElicense.txtlicense.txttext/plain102http://repositorio2.unb.br/jspui/bitstream/10482/46917/2/license.txtaed4704d04bb260d4decd80db311aaa5MD52open accessORIGINALARTIGO_ComparingUnmannedAerial.pdfARTIGO_ComparingUnmannedAerial.pdfapplication/pdf19360915http://repositorio2.unb.br/jspui/bitstream/10482/46917/1/ARTIGO_ComparingUnmannedAerial.pdfa508d5e42d309a215eb4414b863f060cMD51open access10482/469172023-11-28 11:13:35.95open accessoai:repositorio2.unb.br:10482/46917U3VibWlzc8OjbyBlZmV0aXZhZGEgZGUgYWNvcmRvIGNvbSBsaWNlbsOnYSBjb25jZWRpZGEgcGVsbyBhdXRvciBlL291IGRldGVudG9yIGRvcyBkaXJlaXRvcyBhdXRvcmFpcy4KBiblioteca Digital de Teses e DissertaçõesPUBhttps://repositorio.unb.br/oai/requestopendoar:2023-11-28T14:13:35Repositório Institucional da UnB - Universidade de Brasília (UnB)false |
dc.title.pt_BR.fl_str_mv |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming |
title |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming |
spellingShingle |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming Olivetti, Diogo Água Sensoriamento remoto Aeronaves remotamente pilotadas Drones Clorofila-a Cianobactéria |
title_short |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming |
title_full |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming |
title_fullStr |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming |
title_full_unstemmed |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming |
title_sort |
Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming |
author |
Olivetti, Diogo |
author_facet |
Olivetti, Diogo Cicerelli, Rejane Ennes Martinez, Jean-Michel Almeida, Tati de Casari, Raphael Augusto das Chagas Noqueli Borges, Henrique Dantas Roig, Henrique Llacer |
author_role |
author |
author2 |
Cicerelli, Rejane Ennes Martinez, Jean-Michel Almeida, Tati de Casari, Raphael Augusto das Chagas Noqueli Borges, Henrique Dantas Roig, Henrique Llacer |
author2_role |
author author author author author author |
dc.contributor.affiliation.pt_BR.fl_str_mv |
University of Brasília, Institute of Geosciences University of Brasília, Institute of Geosciences University of Brasília, Institute of Geosciences Centre National de la Recherche Scientifique (CNRS), Géosciences Environnement Toulouse (GET), UMR5563, Institut de Recherche pour le Développement (IRD), Université Toulouse 3, University of Brasília, Institute of Geosciences University of Brasília, Institute of Geosciences University of Brasília, Institute of Geosciences |
dc.contributor.orcid.none.fl_str_mv |
https://orcid.org/0000-0002-0729-5767 |
dc.contributor.author.fl_str_mv |
Olivetti, Diogo Cicerelli, Rejane Ennes Martinez, Jean-Michel Almeida, Tati de Casari, Raphael Augusto das Chagas Noqueli Borges, Henrique Dantas Roig, Henrique Llacer |
dc.subject.keyword.pt_BR.fl_str_mv |
Água Sensoriamento remoto Aeronaves remotamente pilotadas Drones Clorofila-a Cianobactéria |
topic |
Água Sensoriamento remoto Aeronaves remotamente pilotadas Drones Clorofila-a Cianobactéria |
description |
This 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. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-11-28T14:00:29Z |
dc.date.available.fl_str_mv |
2023-11-28T14:00:29Z |
dc.date.issued.fl_str_mv |
2023-06-21 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
OLIVETTI, 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. |
dc.identifier.uri.fl_str_mv |
http://repositorio2.unb.br/jspui/handle/10482/46917 |
dc.identifier.doi.pt_BR.fl_str_mv |
https://doi.org/10.3390/drones7070410 |
dc.identifier.orcid.none.fl_str_mv |
https://orcid.org/0000-0002-8199-5163 https://orcid.org/0000-0003-3281-8512 |
identifier_str_mv |
OLIVETTI, 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. |
url |
http://repositorio2.unb.br/jspui/handle/10482/46917 https://doi.org/10.3390/drones7070410 https://orcid.org/0000-0002-8199-5163 https://orcid.org/0000-0003-3281-8512 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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MDPI |
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MDPI |
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