Estimation of combustible material in Cerrado grassland area from RGB sensor images
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Pesquisa Florestal Brasileira (Online) |
Texto Completo: | https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1706 |
Resumo: | The quantification of fuel material in the Cerrado area is limited by the difficulty in obtaining data, the high costs and the high time spent in the field. In search of alternatives that facilitate the data acquisition, the use of RGB sensors stands out being able to be a useful and effective tool in quantifying the combustible material. In this context, the objective of this work was to evaluate the feasibility of using images from an airborne RGB sensor by a multirotor to estimate the combustible material by means of regression analysis. The fuel material was sampled from the area that was weighed in the field and dried in an oven. With the digital images processing, the height (htMDA) and the vegetation index (NGRDI) of the pixels covering the sample units were obtained, followed by a correlation analysis between the digital processing data and the combustible material. Subsequently, three regression models were adjusted, in which adjusted coefficient of determination (R²aj) was obtained from 0.39 to 0.80. The use of RGB sensors has potential for estimation of combustible material. When the htMDA and NGRDI variables are combined, values closer to the mid-range are obtained. |
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Estimation of combustible material in Cerrado grassland area from RGB sensor imagesEstimativa do material combustível em área de Cerrado campo sujo a partir de imagens do sensor RGBBiofuelsDigital modelsRemote sensingSensoriamento remotoModelos digitaisBiocarburanteThe quantification of fuel material in the Cerrado area is limited by the difficulty in obtaining data, the high costs and the high time spent in the field. In search of alternatives that facilitate the data acquisition, the use of RGB sensors stands out being able to be a useful and effective tool in quantifying the combustible material. In this context, the objective of this work was to evaluate the feasibility of using images from an airborne RGB sensor by a multirotor to estimate the combustible material by means of regression analysis. The fuel material was sampled from the area that was weighed in the field and dried in an oven. With the digital images processing, the height (htMDA) and the vegetation index (NGRDI) of the pixels covering the sample units were obtained, followed by a correlation analysis between the digital processing data and the combustible material. Subsequently, three regression models were adjusted, in which adjusted coefficient of determination (R²aj) was obtained from 0.39 to 0.80. The use of RGB sensors has potential for estimation of combustible material. When the htMDA and NGRDI variables are combined, values closer to the mid-range are obtained.A quantificação do material combustível em área do Cerrado campo sujo é limitada pela dificuldade em obtenção de dados, nos altos custos e no elevado tempo gasto em campo. Em busca de alternativas que facilitem a obtenção dos dados, o uso de sensores RGB se destaca, podendo ser uma ferramenta útil e eficaz na quantificação do material combustível. Nesse contexto, o trabalho teve como objetivo avaliar a viabilidade da utilização de imagens provenientes de um sensor RGB aerotransportado por um multirotor para estimava do material combustível por meio da análise de regressão. Foi realizada a amostragem do material combustível da área que foi pesada em campo e seca em estufa. Com o processamento das imagens digitais foram obtidas a altura (htMDA) e o índice de vegetação (NGRDI) dos pixels que abrangiam as unidades amostrais, seguidos de análise de correlação entre dados do processamento digital e o material combustível. Posteriormente, foram ajustados três modelos de regressão, em que foram obtidos coeficiente de determinação ajustados (R²aj) de 0,39 a 0,80. O uso dos sensores RGB apresentam potencial para a estimação de material combustível. Quando se combina as variáveis htMDA e NGRDI, são obtidos valores mais próximos da linha média de distribuição.Embrapa Florestas2018-12-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/170610.4336/2018.pfb.38e201801706Pesquisa Florestal Brasileira; v. 38 (2018)Pesquisa Florestal Brasileira; Vol. 38 (2018)1983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1706/822Souza, Igor VianaSantos, Micael MoreiraGiongo, MarcosCarvalho, Edmar Vinicius deSilva Machado, Igor Elóiinfo:eu-repo/semantics/openAccess2019-05-10T19:43:46Zoai:pfb.cnpf.embrapa.br/pfb:article/1706Revistahttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/PUBhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/oaipfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br1983-26051809-3647opendoar:2019-05-10T19:43:46Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Estimation of combustible material in Cerrado grassland area from RGB sensor images Estimativa do material combustível em área de Cerrado campo sujo a partir de imagens do sensor RGB |
title |
Estimation of combustible material in Cerrado grassland area from RGB sensor images |
spellingShingle |
Estimation of combustible material in Cerrado grassland area from RGB sensor images Souza, Igor Viana Biofuels Digital models Remote sensing Sensoriamento remoto Modelos digitais Biocarburante |
title_short |
Estimation of combustible material in Cerrado grassland area from RGB sensor images |
title_full |
Estimation of combustible material in Cerrado grassland area from RGB sensor images |
title_fullStr |
Estimation of combustible material in Cerrado grassland area from RGB sensor images |
title_full_unstemmed |
Estimation of combustible material in Cerrado grassland area from RGB sensor images |
title_sort |
Estimation of combustible material in Cerrado grassland area from RGB sensor images |
author |
Souza, Igor Viana |
author_facet |
Souza, Igor Viana Santos, Micael Moreira Giongo, Marcos Carvalho, Edmar Vinicius de Silva Machado, Igor Elói |
author_role |
author |
author2 |
Santos, Micael Moreira Giongo, Marcos Carvalho, Edmar Vinicius de Silva Machado, Igor Elói |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Souza, Igor Viana Santos, Micael Moreira Giongo, Marcos Carvalho, Edmar Vinicius de Silva Machado, Igor Elói |
dc.subject.por.fl_str_mv |
Biofuels Digital models Remote sensing Sensoriamento remoto Modelos digitais Biocarburante |
topic |
Biofuels Digital models Remote sensing Sensoriamento remoto Modelos digitais Biocarburante |
description |
The quantification of fuel material in the Cerrado area is limited by the difficulty in obtaining data, the high costs and the high time spent in the field. In search of alternatives that facilitate the data acquisition, the use of RGB sensors stands out being able to be a useful and effective tool in quantifying the combustible material. In this context, the objective of this work was to evaluate the feasibility of using images from an airborne RGB sensor by a multirotor to estimate the combustible material by means of regression analysis. The fuel material was sampled from the area that was weighed in the field and dried in an oven. With the digital images processing, the height (htMDA) and the vegetation index (NGRDI) of the pixels covering the sample units were obtained, followed by a correlation analysis between the digital processing data and the combustible material. Subsequently, three regression models were adjusted, in which adjusted coefficient of determination (R²aj) was obtained from 0.39 to 0.80. The use of RGB sensors has potential for estimation of combustible material. When the htMDA and NGRDI variables are combined, values closer to the mid-range are obtained. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-29 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1706 10.4336/2018.pfb.38e201801706 |
url |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1706 |
identifier_str_mv |
10.4336/2018.pfb.38e201801706 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1706/822 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Embrapa Florestas |
publisher.none.fl_str_mv |
Embrapa Florestas |
dc.source.none.fl_str_mv |
Pesquisa Florestal Brasileira; v. 38 (2018) Pesquisa Florestal Brasileira; Vol. 38 (2018) 1983-2605 1809-3647 reponame:Pesquisa Florestal Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Florestal Brasileira (Online) |
collection |
Pesquisa Florestal Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br |
_version_ |
1783370936820432896 |