Models of forest variables estimation using multispectral images
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
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/1380 |
Resumo: | Remote sensing techniques for vegetation monitoring has been more used and improved. These techniques are good alternative to be used as as basis for forest inventories. The present study aims to estimate forest variables using multispectral images associated with data from field survey. The studied area was a tropical rain forest of approximately 44,728.5 ha. A forest inventory 100% was carried out providing the volume of tree species with circumference at 1.30 m above soil level (CBH) higher than 110 cm. The used satellite was Landsat 7, scene 227/069. A radiometric correction was performed to obtain the reflectance values. Three plots sizes (40, 80, 120 m radius) were assessed for linear models adjustment. The area spectral behave presented low response on visible region (TM1, TM2 and TM3), increasing on near-infrared (TM4). TM4 band presented higher correlation with CBH (R: -0.5203). The best model to estimate showed a R²aj = 0.387 and Syx = 30.199%, estimating an average volume of 39,61 m³ ha-1. The results showed viability to use satellite images to evaluate dendrometric variables. |
id |
EMBRAPA-5_8a058952f110ad7c1028f0af97b3fbeb |
---|---|
oai_identifier_str |
oai:pfb.cnpf.embrapa.br/pfb:article/1380 |
network_acronym_str |
EMBRAPA-5 |
network_name_str |
Pesquisa Florestal Brasileira (Online) |
repository_id_str |
|
spelling |
Models of forest variables estimation using multispectral imagesModelos para estimativa de variáveis florestais com a utilização de imagens multiespectraisLandsatInventários florestaisEstimativa de volumeLandsatForest inventoryVolume estimationRemote sensing techniques for vegetation monitoring has been more used and improved. These techniques are good alternative to be used as as basis for forest inventories. The present study aims to estimate forest variables using multispectral images associated with data from field survey. The studied area was a tropical rain forest of approximately 44,728.5 ha. A forest inventory 100% was carried out providing the volume of tree species with circumference at 1.30 m above soil level (CBH) higher than 110 cm. The used satellite was Landsat 7, scene 227/069. A radiometric correction was performed to obtain the reflectance values. Three plots sizes (40, 80, 120 m radius) were assessed for linear models adjustment. The area spectral behave presented low response on visible region (TM1, TM2 and TM3), increasing on near-infrared (TM4). TM4 band presented higher correlation with CBH (R: -0.5203). The best model to estimate showed a R²aj = 0.387 and Syx = 30.199%, estimating an average volume of 39,61 m³ ha-1. The results showed viability to use satellite images to evaluate dendrometric variables.Técnicas de sensoriamento remoto em monitoramento vegetacional vêm sendo cada vez mais utilizadas e melhoradas. A utilização dessas técnicas é uma alternativa potencial para embasar inventários florestais. O presente trabalho tem por objetivo estimar variáveis florestais utilizando imagens multiespectrais associadas a informações obtidas em levantamento de campo. Foi estudada uma área de floresta tropical com aproximadamente 44.728,5 ha. Foi feito um inventário florestal 100%, fornecendo a volumetria das árvores com circunferência a 1,30 m acima do solo (CAP) superior a 110 cm. Foi utilizada a cena 227/069 do Landsat 7, sendo feita correção radiométrica da imagem, obtendo-se os valores de reflectância. Foram avaliados três tamanhos de parcelas circulares (40, 80 e 120 m de raio) para ajuste dos modelos lineares. O comportamento espectral da área apresentou respostas baixas na região do visível (TM1, TM2 e TM3), aumentando no infravermelho próximo (TM4). A banda TM4 apresentou maior correlação com o CAP (R: -0,5203). O melhor modelo para estimativa do volume exibiu R²aj = 0,387 e Syx = 30,199%, estimando um volume médio de 39,61 m³ ha-1. Os resultados demonstraram viabilidade do uso de imagens de satélites para estimativa de variáveis dendrométricas.Embrapa Florestas2017-06-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/138010.4336/2017.pfb.37.90.1380Pesquisa Florestal Brasileira; v. 37 n. 90 (2017): abr./jun.; 171-181Pesquisa Florestal Brasileira; Vol. 37 No. 90 (2017): abr./jun.; 171-1811983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1380/571Copyright (c) 2017 Igor Eloi Silva Machado, Micael Moreira Santos, Marcos Giongo, Edmar Vinicius de Carvalho, Eduardo Ganassoli Netohttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessMachado, Igor Eloi SilvaSantos, Micael MoreiraGiongo, MarcosCarvalho, Edmar Vinicius deGanassoli Neto, Eduardo2018-01-07T19:01:10Zoai:pfb.cnpf.embrapa.br/pfb:article/1380Revistahttps://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:2018-01-07T19:01:10Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Models of forest variables estimation using multispectral images Modelos para estimativa de variáveis florestais com a utilização de imagens multiespectrais |
title |
Models of forest variables estimation using multispectral images |
spellingShingle |
Models of forest variables estimation using multispectral images Machado, Igor Eloi Silva Landsat Inventários florestais Estimativa de volume Landsat Forest inventory Volume estimation |
title_short |
Models of forest variables estimation using multispectral images |
title_full |
Models of forest variables estimation using multispectral images |
title_fullStr |
Models of forest variables estimation using multispectral images |
title_full_unstemmed |
Models of forest variables estimation using multispectral images |
title_sort |
Models of forest variables estimation using multispectral images |
author |
Machado, Igor Eloi Silva |
author_facet |
Machado, Igor Eloi Silva Santos, Micael Moreira Giongo, Marcos Carvalho, Edmar Vinicius de Ganassoli Neto, Eduardo |
author_role |
author |
author2 |
Santos, Micael Moreira Giongo, Marcos Carvalho, Edmar Vinicius de Ganassoli Neto, Eduardo |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Machado, Igor Eloi Silva Santos, Micael Moreira Giongo, Marcos Carvalho, Edmar Vinicius de Ganassoli Neto, Eduardo |
dc.subject.por.fl_str_mv |
Landsat Inventários florestais Estimativa de volume Landsat Forest inventory Volume estimation |
topic |
Landsat Inventários florestais Estimativa de volume Landsat Forest inventory Volume estimation |
description |
Remote sensing techniques for vegetation monitoring has been more used and improved. These techniques are good alternative to be used as as basis for forest inventories. The present study aims to estimate forest variables using multispectral images associated with data from field survey. The studied area was a tropical rain forest of approximately 44,728.5 ha. A forest inventory 100% was carried out providing the volume of tree species with circumference at 1.30 m above soil level (CBH) higher than 110 cm. The used satellite was Landsat 7, scene 227/069. A radiometric correction was performed to obtain the reflectance values. Three plots sizes (40, 80, 120 m radius) were assessed for linear models adjustment. The area spectral behave presented low response on visible region (TM1, TM2 and TM3), increasing on near-infrared (TM4). TM4 band presented higher correlation with CBH (R: -0.5203). The best model to estimate showed a R²aj = 0.387 and Syx = 30.199%, estimating an average volume of 39,61 m³ ha-1. The results showed viability to use satellite images to evaluate dendrometric variables. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-06-30 |
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/1380 10.4336/2017.pfb.37.90.1380 |
url |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1380 |
identifier_str_mv |
10.4336/2017.pfb.37.90.1380 |
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/1380/571 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 |
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. 37 n. 90 (2017): abr./jun.; 171-181 Pesquisa Florestal Brasileira; Vol. 37 No. 90 (2017): abr./jun.; 171-181 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_ |
1783370936099012608 |