Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images

Detalhes bibliográficos
Autor(a) principal: Macedo, Fabrício
Data de Publicação: 2018
Outros Autores: Sousa, Adélia, Gonçalves, Ana Cristina, Marques da Silva, José, Mesquita, Paulo, Rodrigues, Ricardo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/23599
https://doi.org/10.1080/22797254.2018.1521250
Resumo: The estimation of vegetation parameters, such as above-ground biomass, with high accuracy using remote sensing data, represents a promising approach. The present study develops models to estimate and map above-ground biomass of Mediterranean Quercus rotundifolia stands using one QuickBird satellite image in pan-sharpened mode, with four multispectral bands (blue, green, red and near infrared) and a spatial resolution of 0.70 m. The satellite image was orthorectified, geometrically and radiometrically corrected. Object-oriented classification methods and multi-resolution segmentation were used to derive a vegetation mask per forest species. Data from forest inventory (24 plots) and vegetation indices (NDVI, EVI, SR and SAVI) derived from high spatial resolution satellite images were used for an area of 133 km2, in southern Portugal. The statistical analysis included correlation, variance analysis and linear regression. The linear regression models fitted included the arithmetic mean and the median values of the vegetation indices per inventory plot as explanatory variables. The overall results of the fitted models show a trend of better performance for those with the median value of the vegetation index as the explanatory variable. The best fitted model (R2 = 75.3) was associated with the Simple Ratio (SR) median value as an explanatory variable. A Quercus rotundifolia above-ground biomass map was produced.
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spelling Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite imagesabove-ground biomasshigh spatial resolutionvegetation indiceslinear regressionThe estimation of vegetation parameters, such as above-ground biomass, with high accuracy using remote sensing data, represents a promising approach. The present study develops models to estimate and map above-ground biomass of Mediterranean Quercus rotundifolia stands using one QuickBird satellite image in pan-sharpened mode, with four multispectral bands (blue, green, red and near infrared) and a spatial resolution of 0.70 m. The satellite image was orthorectified, geometrically and radiometrically corrected. Object-oriented classification methods and multi-resolution segmentation were used to derive a vegetation mask per forest species. Data from forest inventory (24 plots) and vegetation indices (NDVI, EVI, SR and SAVI) derived from high spatial resolution satellite images were used for an area of 133 km2, in southern Portugal. The statistical analysis included correlation, variance analysis and linear regression. The linear regression models fitted included the arithmetic mean and the median values of the vegetation indices per inventory plot as explanatory variables. The overall results of the fitted models show a trend of better performance for those with the median value of the vegetation index as the explanatory variable. The best fitted model (R2 = 75.3) was associated with the Simple Ratio (SR) median value as an explanatory variable. A Quercus rotundifolia above-ground biomass map was produced.2018-10-12T16:30:07Z2018-10-122018-10-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/23599http://hdl.handle.net/10174/23599https://doi.org/10.1080/22797254.2018.1521250engMacedo F. L., Sousa A.M.O., Gonçalves A.C., Marques da Silva J.R., Mesquita P.A e Rodrigues, R. A. (2018). Above ground biomass estimation for Quercus rotundifolia using vegetation indices derived from very high spatial resolution satellite images. European Journal of Remote Sensing. 51(1): 933-944.ICAAMfabriciolmacedo@hotmail.comasousa@uevora.ptacag@uevora.ptjmsilva@uevora.ptpmesquita@uevora.ptricardo@agr.feis.unesp.br214Macedo, FabrícioSousa, AdéliaGonçalves, Ana CristinaMarques da Silva, JoséMesquita, PauloRodrigues, Ricardoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:15:52Zoai:dspace.uevora.pt:10174/23599Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:14:25.149678Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
title Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
spellingShingle Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
Macedo, Fabrício
above-ground biomass
high spatial resolution
vegetation indices
linear regression
title_short Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
title_full Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
title_fullStr Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
title_full_unstemmed Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
title_sort Above-ground biomass estimation for Quercus rotundifolia using vegetation indices derived from high spatial resolution satellite images
author Macedo, Fabrício
author_facet Macedo, Fabrício
Sousa, Adélia
Gonçalves, Ana Cristina
Marques da Silva, José
Mesquita, Paulo
Rodrigues, Ricardo
author_role author
author2 Sousa, Adélia
Gonçalves, Ana Cristina
Marques da Silva, José
Mesquita, Paulo
Rodrigues, Ricardo
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Macedo, Fabrício
Sousa, Adélia
Gonçalves, Ana Cristina
Marques da Silva, José
Mesquita, Paulo
Rodrigues, Ricardo
dc.subject.por.fl_str_mv above-ground biomass
high spatial resolution
vegetation indices
linear regression
topic above-ground biomass
high spatial resolution
vegetation indices
linear regression
description The estimation of vegetation parameters, such as above-ground biomass, with high accuracy using remote sensing data, represents a promising approach. The present study develops models to estimate and map above-ground biomass of Mediterranean Quercus rotundifolia stands using one QuickBird satellite image in pan-sharpened mode, with four multispectral bands (blue, green, red and near infrared) and a spatial resolution of 0.70 m. The satellite image was orthorectified, geometrically and radiometrically corrected. Object-oriented classification methods and multi-resolution segmentation were used to derive a vegetation mask per forest species. Data from forest inventory (24 plots) and vegetation indices (NDVI, EVI, SR and SAVI) derived from high spatial resolution satellite images were used for an area of 133 km2, in southern Portugal. The statistical analysis included correlation, variance analysis and linear regression. The linear regression models fitted included the arithmetic mean and the median values of the vegetation indices per inventory plot as explanatory variables. The overall results of the fitted models show a trend of better performance for those with the median value of the vegetation index as the explanatory variable. The best fitted model (R2 = 75.3) was associated with the Simple Ratio (SR) median value as an explanatory variable. A Quercus rotundifolia above-ground biomass map was produced.
publishDate 2018
dc.date.none.fl_str_mv 2018-10-12T16:30:07Z
2018-10-12
2018-10-03T00:00:00Z
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.uri.fl_str_mv http://hdl.handle.net/10174/23599
http://hdl.handle.net/10174/23599
https://doi.org/10.1080/22797254.2018.1521250
url http://hdl.handle.net/10174/23599
https://doi.org/10.1080/22797254.2018.1521250
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Macedo F. L., Sousa A.M.O., Gonçalves A.C., Marques da Silva J.R., Mesquita P.A e Rodrigues, R. A. (2018). Above ground biomass estimation for Quercus rotundifolia using vegetation indices derived from very high spatial resolution satellite images. European Journal of Remote Sensing. 51(1): 933-944.
ICAAM
fabriciolmacedo@hotmail.com
asousa@uevora.pt
acag@uevora.pt
jmsilva@uevora.pt
pmesquita@uevora.pt
ricardo@agr.feis.unesp.br
214
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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