TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA

Detalhes bibliográficos
Autor(a) principal: Santos, Francisco
Data de Publicação: 2011
Outros Autores: Ramos, Alice
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/3544
Resumo: Olive transpiration T can be predicted by combining MODIS remotely sensed vegetation indices (EVI* and NDVI*), tree ground-based transpiration derived from sap flow measurements and maximum daily air temperature ta. The feasibility of developing a single predictive equation of olive orchard transpiration through the relationship between sap flow based transpiration (T) and remotely sensed Enhanced and Normalized Difference Vegetation Indexes (EVI and NDVI) of an irrigated orchard in southern Portugal was tested. A correlation matrix relating T as the dependent variable to VIs and micrometeorological data as independent variables was constructed. Regression equations were then developed from the micrometeorological variable that most closely correlated with ground transpiration T data, and finally predictive multivariate equations were derived from EVI*- ta and NDVI*- ta, being the maximum air temperature ta the ground-measured micrometeorological variable found most closely correlated with field T. Such predictive responses were validated with olive sap flow ground based transpiration data, being the measured and predicted T based on EVI*-Ta within 11% of the 1:1 line. The robustness of the method is attributed to spectral vegetation indices being able to describe well vegetation amount and condition and strongly correlate with micrometeorological variables that drive olive transpiration. The predictive responses were used here to calculate and propose crop coefficients that can be made routinely operational and available to guide irrigation. The modeling study also shows that the method can offer a reliable way for verification and scaling up of sap flow measurements to wider olive growing areas, and for providing data for other applications.
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spelling TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATATranspirationcrop coefficientMODISEVINDVIvegetation indicesOlea europaeaolive treesOlive transpiration T can be predicted by combining MODIS remotely sensed vegetation indices (EVI* and NDVI*), tree ground-based transpiration derived from sap flow measurements and maximum daily air temperature ta. The feasibility of developing a single predictive equation of olive orchard transpiration through the relationship between sap flow based transpiration (T) and remotely sensed Enhanced and Normalized Difference Vegetation Indexes (EVI and NDVI) of an irrigated orchard in southern Portugal was tested. A correlation matrix relating T as the dependent variable to VIs and micrometeorological data as independent variables was constructed. Regression equations were then developed from the micrometeorological variable that most closely correlated with ground transpiration T data, and finally predictive multivariate equations were derived from EVI*- ta and NDVI*- ta, being the maximum air temperature ta the ground-measured micrometeorological variable found most closely correlated with field T. Such predictive responses were validated with olive sap flow ground based transpiration data, being the measured and predicted T based on EVI*-Ta within 11% of the 1:1 line. The robustness of the method is attributed to spectral vegetation indices being able to describe well vegetation amount and condition and strongly correlate with micrometeorological variables that drive olive transpiration. The predictive responses were used here to calculate and propose crop coefficients that can be made routinely operational and available to guide irrigation. The modeling study also shows that the method can offer a reliable way for verification and scaling up of sap flow measurements to wider olive growing areas, and for providing data for other applications.Institute for Olive Tree and Subtropical Plants of Chania (NAGREF)2012-01-13T17:01:50Z2012-01-132011-10-31T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/3544http://hdl.handle.net/10174/3544engF.L.Santos, A.F. Ramos, Transpiration and crop coefficients for irrigated olives based on remotely sensed vegetation indices and ground-based temperature data, Olivebioteq2011, International Conference for Olive Tree and Olive Products, Chania, Crete, October 31, 2011.fls@uevora.ptalice_f_ramos@yahoo.com580Santos, FranciscoRamos, Aliceinfo: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:RCAAP2024-01-03T18:40:48Zoai:dspace.uevora.pt:10174/3544Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:58:59.654872Repositório 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 TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
title TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
spellingShingle TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
Santos, Francisco
Transpiration
crop coefficient
MODIS
EVI
NDVI
vegetation indices
Olea europaea
olive trees
title_short TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
title_full TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
title_fullStr TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
title_full_unstemmed TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
title_sort TRANSPIRATION AND CROP COEFFICIENTS FOR IRRIGATED OLIVES WITH PREDICTIVE EQUATIONS DERIVED FROM MODIS REMOTELY SENSED VEGETATION INDICES AND GROUND-BASED TEMPERATURE DATA
author Santos, Francisco
author_facet Santos, Francisco
Ramos, Alice
author_role author
author2 Ramos, Alice
author2_role author
dc.contributor.author.fl_str_mv Santos, Francisco
Ramos, Alice
dc.subject.por.fl_str_mv Transpiration
crop coefficient
MODIS
EVI
NDVI
vegetation indices
Olea europaea
olive trees
topic Transpiration
crop coefficient
MODIS
EVI
NDVI
vegetation indices
Olea europaea
olive trees
description Olive transpiration T can be predicted by combining MODIS remotely sensed vegetation indices (EVI* and NDVI*), tree ground-based transpiration derived from sap flow measurements and maximum daily air temperature ta. The feasibility of developing a single predictive equation of olive orchard transpiration through the relationship between sap flow based transpiration (T) and remotely sensed Enhanced and Normalized Difference Vegetation Indexes (EVI and NDVI) of an irrigated orchard in southern Portugal was tested. A correlation matrix relating T as the dependent variable to VIs and micrometeorological data as independent variables was constructed. Regression equations were then developed from the micrometeorological variable that most closely correlated with ground transpiration T data, and finally predictive multivariate equations were derived from EVI*- ta and NDVI*- ta, being the maximum air temperature ta the ground-measured micrometeorological variable found most closely correlated with field T. Such predictive responses were validated with olive sap flow ground based transpiration data, being the measured and predicted T based on EVI*-Ta within 11% of the 1:1 line. The robustness of the method is attributed to spectral vegetation indices being able to describe well vegetation amount and condition and strongly correlate with micrometeorological variables that drive olive transpiration. The predictive responses were used here to calculate and propose crop coefficients that can be made routinely operational and available to guide irrigation. The modeling study also shows that the method can offer a reliable way for verification and scaling up of sap flow measurements to wider olive growing areas, and for providing data for other applications.
publishDate 2011
dc.date.none.fl_str_mv 2011-10-31T00:00:00Z
2012-01-13T17:01:50Z
2012-01-13
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/10174/3544
http://hdl.handle.net/10174/3544
url http://hdl.handle.net/10174/3544
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv F.L.Santos, A.F. Ramos, Transpiration and crop coefficients for irrigated olives based on remotely sensed vegetation indices and ground-based temperature data, Olivebioteq2011, International Conference for Olive Tree and Olive Products, Chania, Crete, October 31, 2011.
fls@uevora.pt
alice_f_ramos@yahoo.com
580
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute for Olive Tree and Subtropical Plants of Chania (NAGREF)
publisher.none.fl_str_mv Institute for Olive Tree and Subtropical Plants of Chania (NAGREF)
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
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