Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)

Detalhes bibliográficos
Autor(a) principal: Noumonvi, Koffi Dodji
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/17944
Resumo: Mestrado MEDfOR - Mediterranean Forestry and Natural Resources Management - Instituto Superior de Agronomia
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spelling Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)Eddy covariancecarbon fluxGPPNEEvegetation indicesMestrado MEDfOR - Mediterranean Forestry and Natural Resources Management - Instituto Superior de AgronomiaThe Eddy covariance method is a widespread method used for measuring carbon fluxes between the atmosphere and the ecosystem. It provides a high temporal resolution of measurements, but it is restricted to an area around the tower called footprint, and other methods are usually used in combination with eddy covariance data in order to estimate carbon fluxes for larger areas. Spectral vegetation indices derived from increasingly available satellite data can be combined with eddy covariance data to estimate carbon fluxes outside of the tower footprint. Following that approach, the present study attempted to model carbon fluxes for a karst grassland in Slovenia. Three types of model were considered: (1) a linear relationship between NEE or GPP and each vegetation index, (2) a linear relationship between GPP and the product of a vegetation index with PAR, and (3) a simplified LUE model assuming a constant LUE. We compared the performance of several vegetation indices from two sources (Landsat and SPOT-Vegetation) as predictors of NEE and GPP, based on three accuracy metrics (R², RMSE and AIC). Two types of aggregation of flux data were explored, midday average fluxes and daily average fluxes. The Vapor Pressure Deficit was used to separate the growing season in two phases, a greening phase and a dry phase, which were considered separately in the modelling process, in addition to the growing season as a whole. The results showed that NDVI was the best predictor of GPP and NEE during the greening phase, whereas water related vegetation indices, namely LSWI and MNDWI were the best predictors during the dry phase, both for midday and daily aggregates. Model type 1 (linear relationship) was found to be the best in many cases. The best regression equations obtained were used to illustrate the mapping of GPP and NEE for the study areaISA/ULCerasoli, SofiaFerlan, MitjaRepositório da Universidade de LisboaNoumonvi, Koffi Dodji2019-05-27T09:37:15Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.5/17944TID:203085922engNoumonvi, K.D. - Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia). Lisboa: ISA, 2018, 36 p.info: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:RCAAP2023-03-06T14:47:35Zoai:www.repository.utl.pt:10400.5/17944Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:03:05.043215Repositório 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 Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
title Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
spellingShingle Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
Noumonvi, Koffi Dodji
Eddy covariance
carbon flux
GPP
NEE
vegetation indices
title_short Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
title_full Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
title_fullStr Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
title_full_unstemmed Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
title_sort Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia)
author Noumonvi, Koffi Dodji
author_facet Noumonvi, Koffi Dodji
author_role author
dc.contributor.none.fl_str_mv Cerasoli, Sofia
Ferlan, Mitja
Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Noumonvi, Koffi Dodji
dc.subject.por.fl_str_mv Eddy covariance
carbon flux
GPP
NEE
vegetation indices
topic Eddy covariance
carbon flux
GPP
NEE
vegetation indices
description Mestrado MEDfOR - Mediterranean Forestry and Natural Resources Management - Instituto Superior de Agronomia
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
2019-05-27T09:37:15Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/17944
TID:203085922
url http://hdl.handle.net/10400.5/17944
identifier_str_mv TID:203085922
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Noumonvi, K.D. - Estimation of carbon fluxes from eddy covariance data and satellite-derived vegetation indices in a karst grassland (Podgorski Kras, Slovenia). Lisboa: ISA, 2018, 36 p.
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 ISA/UL
publisher.none.fl_str_mv ISA/UL
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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