Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques

Detalhes bibliográficos
Autor(a) principal: Danelichen,Victor Hugo de Morais
Data de Publicação: 2014
Outros Autores: Biudes,Marcelo Sacardi, Souza,Maísa Caldas, Machado,Nadja Gomes, Silva,Bernardo Barbosa da, Nogueira,José de Souza
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Meteorologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862014000400001
Resumo: The direct estimation of the soil heat flux (G) by remote sensing data is not possible. For this, several models have been proposed empirically from the relation of G measures and biophysical parameters of various types of coverage or not vegetated in different places on earth. Thus, the objective of this study was to evaluate the relation between G/Rn ratio and biophysical variables obtained by satellite sensors and evaluate the parameterization of different models to estimate G spatially in three sites with different soil cover types. The net radiation (Rn) and G were measured directly in two pastures at Miranda Farm and Experimental Farm and and Monodominant Forest of Cambará. Rn, G, and G/Rn ratio and MODIS products, such as albedo (α), surface temperature (LST), vegetation index (NDVI) and leaf area index (LAI) varied seasonally at all sites and inter-sites. The sites were different from each other by presenting different relation between measures of Rn, G and G/Rn ratio and biophysical parameters. Among the original models, the model proposed by Bastiaanssen (1995) showed the best performance with r = 0.76, d = 0.95, MAE = 5.70 W m-2 and RMSE = 33.68 W m-2. As the reparameterized models, correlation coefficients had no significant change, but the coefficient Willmott (d) increased and the MAE and RMSE had a small decrease.
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spelling Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniquesMato Grossopasturemonodominant forestorbital sensorsThe direct estimation of the soil heat flux (G) by remote sensing data is not possible. For this, several models have been proposed empirically from the relation of G measures and biophysical parameters of various types of coverage or not vegetated in different places on earth. Thus, the objective of this study was to evaluate the relation between G/Rn ratio and biophysical variables obtained by satellite sensors and evaluate the parameterization of different models to estimate G spatially in three sites with different soil cover types. The net radiation (Rn) and G were measured directly in two pastures at Miranda Farm and Experimental Farm and and Monodominant Forest of Cambará. Rn, G, and G/Rn ratio and MODIS products, such as albedo (α), surface temperature (LST), vegetation index (NDVI) and leaf area index (LAI) varied seasonally at all sites and inter-sites. The sites were different from each other by presenting different relation between measures of Rn, G and G/Rn ratio and biophysical parameters. Among the original models, the model proposed by Bastiaanssen (1995) showed the best performance with r = 0.76, d = 0.95, MAE = 5.70 W m-2 and RMSE = 33.68 W m-2. As the reparameterized models, correlation coefficients had no significant change, but the coefficient Willmott (d) increased and the MAE and RMSE had a small decrease.Sociedade Brasileira de Meteorologia2014-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862014000400001Revista Brasileira de Meteorologia v.29 n.4 2014reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/0102-778620120568info:eu-repo/semantics/openAccessDanelichen,Victor Hugo de MoraisBiudes,Marcelo SacardiSouza,Maísa CaldasMachado,Nadja GomesSilva,Bernardo Barbosa daNogueira,José de Souzaeng2014-11-24T00:00:00Zoai:scielo:S0102-77862014000400001Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2014-11-24T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false
dc.title.none.fl_str_mv Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
title Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
spellingShingle Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
Danelichen,Victor Hugo de Morais
Mato Grosso
pasture
monodominant forest
orbital sensors
title_short Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
title_full Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
title_fullStr Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
title_full_unstemmed Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
title_sort Estimation of soil heat flux in a neotropical Wetland region using remote sensing techniques
author Danelichen,Victor Hugo de Morais
author_facet Danelichen,Victor Hugo de Morais
Biudes,Marcelo Sacardi
Souza,Maísa Caldas
Machado,Nadja Gomes
Silva,Bernardo Barbosa da
Nogueira,José de Souza
author_role author
author2 Biudes,Marcelo Sacardi
Souza,Maísa Caldas
Machado,Nadja Gomes
Silva,Bernardo Barbosa da
Nogueira,José de Souza
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Danelichen,Victor Hugo de Morais
Biudes,Marcelo Sacardi
Souza,Maísa Caldas
Machado,Nadja Gomes
Silva,Bernardo Barbosa da
Nogueira,José de Souza
dc.subject.por.fl_str_mv Mato Grosso
pasture
monodominant forest
orbital sensors
topic Mato Grosso
pasture
monodominant forest
orbital sensors
description The direct estimation of the soil heat flux (G) by remote sensing data is not possible. For this, several models have been proposed empirically from the relation of G measures and biophysical parameters of various types of coverage or not vegetated in different places on earth. Thus, the objective of this study was to evaluate the relation between G/Rn ratio and biophysical variables obtained by satellite sensors and evaluate the parameterization of different models to estimate G spatially in three sites with different soil cover types. The net radiation (Rn) and G were measured directly in two pastures at Miranda Farm and Experimental Farm and and Monodominant Forest of Cambará. Rn, G, and G/Rn ratio and MODIS products, such as albedo (α), surface temperature (LST), vegetation index (NDVI) and leaf area index (LAI) varied seasonally at all sites and inter-sites. The sites were different from each other by presenting different relation between measures of Rn, G and G/Rn ratio and biophysical parameters. Among the original models, the model proposed by Bastiaanssen (1995) showed the best performance with r = 0.76, d = 0.95, MAE = 5.70 W m-2 and RMSE = 33.68 W m-2. As the reparameterized models, correlation coefficients had no significant change, but the coefficient Willmott (d) increased and the MAE and RMSE had a small decrease.
publishDate 2014
dc.date.none.fl_str_mv 2014-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862014000400001
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862014000400001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0102-778620120568
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Meteorologia
publisher.none.fl_str_mv Sociedade Brasileira de Meteorologia
dc.source.none.fl_str_mv Revista Brasileira de Meteorologia v.29 n.4 2014
reponame:Revista Brasileira de Meteorologia (Online)
instname:Sociedade Brasileira de Meteorologia (SBMET)
instacron:SBMET
instname_str Sociedade Brasileira de Meteorologia (SBMET)
instacron_str SBMET
institution SBMET
reponame_str Revista Brasileira de Meteorologia (Online)
collection Revista Brasileira de Meteorologia (Online)
repository.name.fl_str_mv Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)
repository.mail.fl_str_mv ||rbmet@rbmet.org.br
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