Assessing soil carbon stocks under pastures through orbital remote sensing

Detalhes bibliográficos
Autor(a) principal: Szakács,Gabor Gyula Julius
Data de Publicação: 2011
Outros Autores: Cerri,Carlos Clemente, Herpin,Uwe, Bernoux,Martial
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162011000500010
Resumo: The growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC) stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI) measured in the field (LAIfield) and derived by satellite (LAIsatellite) as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+) sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804) and LAIsatellite (R² = 0.9812) was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale.
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spelling Assessing soil carbon stocks under pastures through orbital remote sensingBrazilleaf Area Indexsoil organic carbonpasture degradationspectral reflectanceclimate changeThe growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC) stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI) measured in the field (LAIfield) and derived by satellite (LAIsatellite) as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+) sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804) and LAIsatellite (R² = 0.9812) was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale.Escola Superior de Agricultura "Luiz de Queiroz"2011-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162011000500010Scientia Agricola v.68 n.5 2011reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/S0103-90162011000500010info:eu-repo/semantics/openAccessSzakács,Gabor Gyula JuliusCerri,Carlos ClementeHerpin,UweBernoux,Martialeng2011-10-03T00:00:00Zoai:scielo:S0103-90162011000500010Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2011-10-03T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Assessing soil carbon stocks under pastures through orbital remote sensing
title Assessing soil carbon stocks under pastures through orbital remote sensing
spellingShingle Assessing soil carbon stocks under pastures through orbital remote sensing
Szakács,Gabor Gyula Julius
Brazil
leaf Area Index
soil organic carbon
pasture degradation
spectral reflectance
climate change
title_short Assessing soil carbon stocks under pastures through orbital remote sensing
title_full Assessing soil carbon stocks under pastures through orbital remote sensing
title_fullStr Assessing soil carbon stocks under pastures through orbital remote sensing
title_full_unstemmed Assessing soil carbon stocks under pastures through orbital remote sensing
title_sort Assessing soil carbon stocks under pastures through orbital remote sensing
author Szakács,Gabor Gyula Julius
author_facet Szakács,Gabor Gyula Julius
Cerri,Carlos Clemente
Herpin,Uwe
Bernoux,Martial
author_role author
author2 Cerri,Carlos Clemente
Herpin,Uwe
Bernoux,Martial
author2_role author
author
author
dc.contributor.author.fl_str_mv Szakács,Gabor Gyula Julius
Cerri,Carlos Clemente
Herpin,Uwe
Bernoux,Martial
dc.subject.por.fl_str_mv Brazil
leaf Area Index
soil organic carbon
pasture degradation
spectral reflectance
climate change
topic Brazil
leaf Area Index
soil organic carbon
pasture degradation
spectral reflectance
climate change
description The growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC) stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI) measured in the field (LAIfield) and derived by satellite (LAIsatellite) as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+) sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804) and LAIsatellite (R² = 0.9812) was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale.
publishDate 2011
dc.date.none.fl_str_mv 2011-10-01
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=S0103-90162011000500010
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162011000500010
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0103-90162011000500010
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 Escola Superior de Agricultura "Luiz de Queiroz"
publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
dc.source.none.fl_str_mv Scientia Agricola v.68 n.5 2011
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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