Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Ciência Florestal (Online) |
Texto Completo: | https://periodicos.ufsm.br/cienciaflorestal/article/view/65702 |
Resumo: | Remote sensing through band ratio techniques for nutritional monitoring of clonal eucalyptus plantations is essential to guarantee health and productivity, reducing costs of forestry enterprises. The objective was to apply vegetation indices from high resolution satellite images in the nutritional diagnosis of macronutrients in plantations of clonal hybrids of Eucalyptus urophylla S. T. Blake. The study was carried out in 62 areas of six municipalities in the state of Bahia under cultivation of homogeneous eucalyptus plantations, aged between 1.3 and 1.8 years. The design was completely randomized with six treatments constituted by the rainfall regime (1000 to 1300 mm year-1 and 1300 to 1600 mm year-1) and soil types (class and texture). The nutritional diagnosis of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg) and sulfur (S) was performed from leaf analysis and determination of vegetation indices: normalized difference vegetation (NDVI), normalized difference water index (NDWI) and soil adjusted vegetation index (SAVI). The evaluated areas have high vigor (NDVI > 0.70) and the highest values were observed in the rainy regions (1300 to 1600 mm year-1) (mean of 0.78). The NDWI index presents the highest correlation for the average levels of Ca and Mg. The NDVI, NDWI and SAVI indexes present a strong correlation with each other (-0.97 to 1.00) and can help in mapping vigor and consequently in eucalyptus productivity. |
id |
UFSM-6_ce81f748966d4884b1dc99d28ce99dfe |
---|---|
oai_identifier_str |
oai:ojs.pkp.sfu.ca:article/65702 |
network_acronym_str |
UFSM-6 |
network_name_str |
Ciência Florestal (Online) |
repository_id_str |
|
spelling |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. BlakeÍndices de vegetação na diagnose nutricional de povoamentos híbridos de Eucalyptus urophylla S. T. BlakeManejo florestalSensoriamento remotoMacronutrientesForest managementRemote sensingMacronutrientsRemote sensing through band ratio techniques for nutritional monitoring of clonal eucalyptus plantations is essential to guarantee health and productivity, reducing costs of forestry enterprises. The objective was to apply vegetation indices from high resolution satellite images in the nutritional diagnosis of macronutrients in plantations of clonal hybrids of Eucalyptus urophylla S. T. Blake. The study was carried out in 62 areas of six municipalities in the state of Bahia under cultivation of homogeneous eucalyptus plantations, aged between 1.3 and 1.8 years. The design was completely randomized with six treatments constituted by the rainfall regime (1000 to 1300 mm year-1 and 1300 to 1600 mm year-1) and soil types (class and texture). The nutritional diagnosis of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg) and sulfur (S) was performed from leaf analysis and determination of vegetation indices: normalized difference vegetation (NDVI), normalized difference water index (NDWI) and soil adjusted vegetation index (SAVI). The evaluated areas have high vigor (NDVI > 0.70) and the highest values were observed in the rainy regions (1300 to 1600 mm year-1) (mean of 0.78). The NDWI index presents the highest correlation for the average levels of Ca and Mg. The NDVI, NDWI and SAVI indexes present a strong correlation with each other (-0.97 to 1.00) and can help in mapping vigor and consequently in eucalyptus productivity.O sensoriamento remoto, por meio das técnicas de razão de bandas para o monitoramento nutricional de plantios clonais de eucalipto, é fundamental para garantir a sanidade, produtividade e reduzir custos de empreendimentos florestais. Objetivou-se aplicar índices de vegetação a partir de imagens de satélite de alta resolução na diagnose nutricional de macronutrientes em plantios de híbridos clonais de Eucalyptus urophylla S. T. Blake. O estudo foi realizado em 62 áreas de seis municípios do estado da Bahia sob cultivo de plantios homogêneos de eucalipto, com idades entre 1,3 e 1,8 anos. O delineamento foi inteiramente casualizado com seis tratamentos constituídos pelo regime pluviométrico (1000 a 1300 mm ano-1 e 1300 a 1600 mm ano-1) e tipos de solo (classe e textura). A diagnose nutricional de nitrogênio (N), fósforo (P), potássio (K), cálcio (Ca), magnésio (Mg) e enxofre (S) foi realizada a partir da análise foliar e da determinação dos índices de vegetação: índice de vegetação por diferença normalizada (NDVI), índice de diferença normalizada da água (NDWI) e índice de vegetação ajustado ao solo (SAVI). As áreas avaliadas possuem alto vigor (NDVI > 0,70) e os maiores valores foram observados nas regiões chuvosas (1300 a 1600 mm ano-1) (médio de 0,78). O índice NDWI apresenta maior correlação para os teores médios de Ca e Mg. Os índices NDVI, NDWI e SAVI apresentam forte correlação entre si (-0,97 a 1,00) e podem auxiliar no mapeamento do vigor e consequentemente na produtividade de eucalipto.Universidade Federal de Santa Maria2023-06-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/6570210.5902/1980509865702Ciência Florestal; Vol. 33 No. 2 (2023): Publicação Contínua; e65702Ciência Florestal; v. 33 n. 2 (2023): Publicação Contínua; e657021980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/65702/60972Copyright (c) 2023 Ciência Florestalhttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessRamos, Juliana Carvalho BarbosaLeite, Elton da SilvaPoelking, Everton LuísFreitas, Luis Carlos deMelo, Iago NeryMartins, Ricardo PrevidenteCosta, João Albany2023-07-21T03:38:48Zoai:ojs.pkp.sfu.ca:article/65702Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2023-07-21T03:38:48Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake Índices de vegetação na diagnose nutricional de povoamentos híbridos de Eucalyptus urophylla S. T. Blake |
title |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake |
spellingShingle |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake Ramos, Juliana Carvalho Barbosa Manejo florestal Sensoriamento remoto Macronutrientes Forest management Remote sensing Macronutrients |
title_short |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake |
title_full |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake |
title_fullStr |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake |
title_full_unstemmed |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake |
title_sort |
Vegetation indices in the nutritional diagnosis of hybrid stands of Eucalyptus urophylla S. T. Blake |
author |
Ramos, Juliana Carvalho Barbosa |
author_facet |
Ramos, Juliana Carvalho Barbosa Leite, Elton da Silva Poelking, Everton Luís Freitas, Luis Carlos de Melo, Iago Nery Martins, Ricardo Previdente Costa, João Albany |
author_role |
author |
author2 |
Leite, Elton da Silva Poelking, Everton Luís Freitas, Luis Carlos de Melo, Iago Nery Martins, Ricardo Previdente Costa, João Albany |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Ramos, Juliana Carvalho Barbosa Leite, Elton da Silva Poelking, Everton Luís Freitas, Luis Carlos de Melo, Iago Nery Martins, Ricardo Previdente Costa, João Albany |
dc.subject.por.fl_str_mv |
Manejo florestal Sensoriamento remoto Macronutrientes Forest management Remote sensing Macronutrients |
topic |
Manejo florestal Sensoriamento remoto Macronutrientes Forest management Remote sensing Macronutrients |
description |
Remote sensing through band ratio techniques for nutritional monitoring of clonal eucalyptus plantations is essential to guarantee health and productivity, reducing costs of forestry enterprises. The objective was to apply vegetation indices from high resolution satellite images in the nutritional diagnosis of macronutrients in plantations of clonal hybrids of Eucalyptus urophylla S. T. Blake. The study was carried out in 62 areas of six municipalities in the state of Bahia under cultivation of homogeneous eucalyptus plantations, aged between 1.3 and 1.8 years. The design was completely randomized with six treatments constituted by the rainfall regime (1000 to 1300 mm year-1 and 1300 to 1600 mm year-1) and soil types (class and texture). The nutritional diagnosis of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg) and sulfur (S) was performed from leaf analysis and determination of vegetation indices: normalized difference vegetation (NDVI), normalized difference water index (NDWI) and soil adjusted vegetation index (SAVI). The evaluated areas have high vigor (NDVI > 0.70) and the highest values were observed in the rainy regions (1300 to 1600 mm year-1) (mean of 0.78). The NDWI index presents the highest correlation for the average levels of Ca and Mg. The NDVI, NDWI and SAVI indexes present a strong correlation with each other (-0.97 to 1.00) and can help in mapping vigor and consequently in eucalyptus productivity. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-06-07 |
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://periodicos.ufsm.br/cienciaflorestal/article/view/65702 10.5902/1980509865702 |
url |
https://periodicos.ufsm.br/cienciaflorestal/article/view/65702 |
identifier_str_mv |
10.5902/1980509865702 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/65702/60972 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2023 Ciência Florestal http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2023 Ciência Florestal http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Ciência Florestal; Vol. 33 No. 2 (2023): Publicação Contínua; e65702 Ciência Florestal; v. 33 n. 2 (2023): Publicação Contínua; e65702 1980-5098 0103-9954 reponame:Ciência Florestal (Online) instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Ciência Florestal (Online) |
collection |
Ciência Florestal (Online) |
repository.name.fl_str_mv |
Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br |
_version_ |
1799944135928446976 |