Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery

Detalhes bibliográficos
Autor(a) principal: Fernandes, Maria Rosário
Data de Publicação: 2020
Outros Autores: Aguiar, Francisca C., Martins, Maria João, Rico, Nuno, Ferreira, Maria Teresa, Correia, Alexandra C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/20299
Resumo: This study aims to estimate the total biomass aboveground and soil carbon stocks in a Mediterranean riparian forest and identify the contribution of the different species and ecosystem compartments to the overall riparian carbon reservoir. We used a combined field and object-based image analysis (OBIA) approach, based on unmanned aerial vehicle (UAV) multispectral imagery, to assess C stock of three dominant riparian species. A linear discriminator was designed, based on a set of spectral variables previously selected in an optimal way, permitting the classification of the species corresponding to every object in the study area. This made it possible to estimate the area occupied by each species and its contribution to the tree aboveground biomass (AGB). Three uncertainty levels were considered, related to the trade-o between the number of unclassified and misclassified objects, leading to an error control associated with the estimated tree AGB.We found that riparian woodlands dominated by Acacia dealbata Link showed the highest average carbon stock per unit area (251 90 tC ha1) followed by Alnus glutinosa (L.) Gaertner (162 12 tC ha1) and by Salix salviifolia Brot. (73 17 tC ha1), which are mainly related to the stem density, vegetation development and successional stage of the different stands. The woody tree compartment showed the highest inputs (79%), followed by the understory vegetation (12%) and lastly by the soil mineral layer (9%). Spectral vegetation indices developed to suppress saturation effects were consistently selected as important variables for species classification. The total tree AGB in the study area varies from 734 to 1053 tC according to the distinct levels of uncertainty. This study provided the foundations for the assessment of the riparian carbon sequestration and the economic value of the carbon stocks provided by similar Mediterranean riparian forests, a highly relevant ecosystem service for the regulation of climate change effects
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spelling Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imageryabove ground biomass (AGB)carbon stocksecosystem servicesriparian allometric equationsunmanned aerial vehicle (UAV)This study aims to estimate the total biomass aboveground and soil carbon stocks in a Mediterranean riparian forest and identify the contribution of the different species and ecosystem compartments to the overall riparian carbon reservoir. We used a combined field and object-based image analysis (OBIA) approach, based on unmanned aerial vehicle (UAV) multispectral imagery, to assess C stock of three dominant riparian species. A linear discriminator was designed, based on a set of spectral variables previously selected in an optimal way, permitting the classification of the species corresponding to every object in the study area. This made it possible to estimate the area occupied by each species and its contribution to the tree aboveground biomass (AGB). Three uncertainty levels were considered, related to the trade-o between the number of unclassified and misclassified objects, leading to an error control associated with the estimated tree AGB.We found that riparian woodlands dominated by Acacia dealbata Link showed the highest average carbon stock per unit area (251 90 tC ha1) followed by Alnus glutinosa (L.) Gaertner (162 12 tC ha1) and by Salix salviifolia Brot. (73 17 tC ha1), which are mainly related to the stem density, vegetation development and successional stage of the different stands. The woody tree compartment showed the highest inputs (79%), followed by the understory vegetation (12%) and lastly by the soil mineral layer (9%). Spectral vegetation indices developed to suppress saturation effects were consistently selected as important variables for species classification. The total tree AGB in the study area varies from 734 to 1053 tC according to the distinct levels of uncertainty. This study provided the foundations for the assessment of the riparian carbon sequestration and the economic value of the carbon stocks provided by similar Mediterranean riparian forests, a highly relevant ecosystem service for the regulation of climate change effectsMDPIRepositório da Universidade de LisboaFernandes, Maria RosárioAguiar, Francisca C.Martins, Maria JoãoRico, NunoFerreira, Maria TeresaCorreia, Alexandra C.2020-09-15T11:50:19Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/20299engForests 2020, 11, 37610.3390/f11040376info: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:RCAAP2023-11-05T01:31:12Zoai:www.repository.utl.pt:10400.5/20299Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:05:04.515736Repositório 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 Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
title Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
spellingShingle Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
Fernandes, Maria Rosário
above ground biomass (AGB)
carbon stocks
ecosystem services
riparian allometric equations
unmanned aerial vehicle (UAV)
title_short Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
title_full Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
title_fullStr Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
title_full_unstemmed Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
title_sort Carbon stock estimation in a Mediterranean riparian forest: a case study combining field data and UAV imagery
author Fernandes, Maria Rosário
author_facet Fernandes, Maria Rosário
Aguiar, Francisca C.
Martins, Maria João
Rico, Nuno
Ferreira, Maria Teresa
Correia, Alexandra C.
author_role author
author2 Aguiar, Francisca C.
Martins, Maria João
Rico, Nuno
Ferreira, Maria Teresa
Correia, Alexandra C.
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Fernandes, Maria Rosário
Aguiar, Francisca C.
Martins, Maria João
Rico, Nuno
Ferreira, Maria Teresa
Correia, Alexandra C.
dc.subject.por.fl_str_mv above ground biomass (AGB)
carbon stocks
ecosystem services
riparian allometric equations
unmanned aerial vehicle (UAV)
topic above ground biomass (AGB)
carbon stocks
ecosystem services
riparian allometric equations
unmanned aerial vehicle (UAV)
description This study aims to estimate the total biomass aboveground and soil carbon stocks in a Mediterranean riparian forest and identify the contribution of the different species and ecosystem compartments to the overall riparian carbon reservoir. We used a combined field and object-based image analysis (OBIA) approach, based on unmanned aerial vehicle (UAV) multispectral imagery, to assess C stock of three dominant riparian species. A linear discriminator was designed, based on a set of spectral variables previously selected in an optimal way, permitting the classification of the species corresponding to every object in the study area. This made it possible to estimate the area occupied by each species and its contribution to the tree aboveground biomass (AGB). Three uncertainty levels were considered, related to the trade-o between the number of unclassified and misclassified objects, leading to an error control associated with the estimated tree AGB.We found that riparian woodlands dominated by Acacia dealbata Link showed the highest average carbon stock per unit area (251 90 tC ha1) followed by Alnus glutinosa (L.) Gaertner (162 12 tC ha1) and by Salix salviifolia Brot. (73 17 tC ha1), which are mainly related to the stem density, vegetation development and successional stage of the different stands. The woody tree compartment showed the highest inputs (79%), followed by the understory vegetation (12%) and lastly by the soil mineral layer (9%). Spectral vegetation indices developed to suppress saturation effects were consistently selected as important variables for species classification. The total tree AGB in the study area varies from 734 to 1053 tC according to the distinct levels of uncertainty. This study provided the foundations for the assessment of the riparian carbon sequestration and the economic value of the carbon stocks provided by similar Mediterranean riparian forests, a highly relevant ecosystem service for the regulation of climate change effects
publishDate 2020
dc.date.none.fl_str_mv 2020-09-15T11:50:19Z
2020
2020-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/20299
url http://hdl.handle.net/10400.5/20299
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Forests 2020, 11, 376
10.3390/f11040376
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 MDPI
publisher.none.fl_str_mv MDPI
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
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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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
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