Atenção: Todas as denúncias são sigilosas e sua identidade será preservada.
Os campos nome e e-mail são de preenchimento opcional
Metadados | Descrição | Idioma |
---|---|---|
Autor(es): dc.contributor | University of Brasília, Institute of Geosciences | - |
Autor(es): dc.contributor | University of Brasília, Institute of Geosciences | - |
Autor(es): dc.contributor | University of Brasília, Institute of Geosciences | - |
Autor(es): dc.contributor | Centre National de la Recherche Scientifique (CNRS), Géosciences Environnement Toulouse (GET), UMR5563, Institut de Recherche pour le Développement (IRD), Université Toulouse 3, | - |
Autor(es): dc.contributor | University of Brasília, Institute of Geosciences | - |
Autor(es): dc.contributor | University of Brasília, Institute of Geosciences | - |
Autor(es): dc.contributor | University of Brasília, Institute of Geosciences | - |
Autor(es): dc.contributor | https://orcid.org/0000-0002-0729-5767 | - |
Autor(es): dc.creator | Olivetti, Diogo | - |
Autor(es): dc.creator | Cicerelli, Rejane Ennes | - |
Autor(es): dc.creator | Martinez, Jean-Michel | - |
Autor(es): dc.creator | Almeida, Tati de | - |
Autor(es): dc.creator | Casari, Raphael Augusto das Chagas Noqueli | - |
Autor(es): dc.creator | Borges, Henrique Dantas | - |
Autor(es): dc.creator | Roig, Henrique Llacer | - |
Data de aceite: dc.date.accessioned | 2024-10-23T15:37:49Z | - |
Data de disponibilização: dc.date.available | 2024-10-23T15:37:49Z | - |
Data de envio: dc.date.issued | 2023-11-27 | - |
Data de envio: dc.date.issued | 2023-11-27 | - |
Data de envio: dc.date.issued | 2023-06-21 | - |
Fonte completa do material: dc.identifier | http://repositorio2.unb.br/jspui/handle/10482/46917 | - |
Fonte completa do material: dc.identifier | https://doi.org/10.3390/drones7070410 | - |
Fonte completa do material: dc.identifier | https://orcid.org/0000-0002-8199-5163 | - |
Fonte completa do material: dc.identifier | https://orcid.org/0000-0003-3281-8512 | - |
Fonte: dc.identifier.uri | http://educapes.capes.gov.br/handle/capes/887900 | - |
Descrição: dc.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. | - |
Descrição: dc.description | Instituto de Geociências (IG) | - |
Formato: dc.format | application/pdf | - |
Idioma: dc.language | en | - |
Publicador: dc.publisher | MDPI | - |
Direitos: dc.rights | Acesso Aberto | - |
Direitos: dc.rights | Copyright: © 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.subject | Água | - |
Palavras-chave: dc.subject | Sensoriamento remoto | - |
Palavras-chave: dc.subject | Aeronaves remotamente pilotadas | - |
Palavras-chave: dc.subject | Drones | - |
Palavras-chave: dc.subject | Clorofila-a | - |
Palavras-chave: dc.subject | Cianobactéria | - |
Título: dc.title | Comparing unmanned aerial multispectral and hyperspectral imagery for harmful algal bloom monitoring in artificial ponds used for fish farming | - |
Tipo de arquivo: dc.type | livro digital | - |
Aparece nas coleções: | Repositório Institucional – UNB |
O Portal eduCAPES é oferecido ao usuário, condicionado à aceitação dos termos, condições e avisos contidos aqui e sem modificações. A CAPES poderá modificar o conteúdo ou formato deste site ou acabar com a sua operação ou suas ferramentas a seu critério único e sem aviso prévio. Ao acessar este portal, você, usuário pessoa física ou jurídica, se declara compreender e aceitar as condições aqui estabelecidas, da seguinte forma: