Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina

Autores
Gasparri, Nestor Ignacio; Parmuchi, Maria Gabriela; Bono, Julieta; Karszenbaum, Haydee; Montenegro, Celina Laura
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Above-ground biomass (AGB) is important to estimate total carbon pools in forests, where it has a key role in the global carbon cycle. We assessed correlations between spectral information and ground data to estimate AGB in the Semiarid Chaco, Argentina. Ground data (DBH, height and species of trees) were obtained from 15 samples (0.8 ha each) and AGB was estimated. Multi-temporal Landsat images were used to obtain spectral data (single bands/vegetation indexes) of the samples. Correlation tests between AGB and spectral bands and between AGB and vegetation indexes were performed for all dates. A strong correlation was found between spectral indexes and AGB in the early dry season (fall e May 12, 2002)
while poorer results were obtained for summer and winter. This would result from a differential phenological response of trees, shrubs and grasses to environmental conditions. A biomass predictive model was fitted using the NDVI of May 12, 2002 and a biomass map was obtained applying this regression. There was a rain-related regional pattern of AGB decrease in an eastewest direction, and a land-use related local pattern. Our results offer a great potential for increasing the understanding of dry Chaco forest structure and for improving carbon pools estimates.

Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Parmuchi, Maria Gabriela. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; Argentina
Fil: Bono, Julieta. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; Argentina
Fil: Karszenbaum, Haydee. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Montenegro, Celina Laura. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; Argentina
Materia
Above-Ground Biomass
Chaco
Dry Forest
Regression Model
Remote Sensing
Vegetation Index
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/19025
Acceder
id CONICETDig_19200523942beb4dc9df126b258ace54
oai_identifier_str oai:ri.conicet.gov.ar:11336/19025
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of ArgentinaGasparri, Nestor IgnacioParmuchi, Maria GabrielaBono, JulietaKarszenbaum, HaydeeMontenegro, Celina LauraAbove-Ground BiomassChacoDry ForestRegression ModelRemote SensingVegetation Indexhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Above-ground biomass (AGB) is important to estimate total carbon pools in forests, where it has a key role in the global carbon cycle. We assessed correlations between spectral information and ground data to estimate AGB in the Semiarid Chaco, Argentina. Ground data (DBH, height and species of trees) were obtained from 15 samples (0.8 ha each) and AGB was estimated. Multi-temporal Landsat images were used to obtain spectral data (single bands/vegetation indexes) of the samples. Correlation tests between AGB and spectral bands and between AGB and vegetation indexes were performed for all dates. A strong correlation was found between spectral indexes and AGB in the early dry season (fall e May 12, 2002)<br />while poorer results were obtained for summer and winter. This would result from a differential phenological response of trees, shrubs and grasses to environmental conditions. A biomass predictive model was fitted using the NDVI of May 12, 2002 and a biomass map was obtained applying this regression. There was a rain-related regional pattern of AGB decrease in an eastewest direction, and a land-use related local pattern. Our results offer a great potential for increasing the understanding of dry Chaco forest structure and for improving carbon pools estimates. <br />Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Parmuchi, Maria Gabriela. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; ArgentinaFil: Bono, Julieta. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; ArgentinaFil: Karszenbaum, Haydee. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Montenegro, Celina Laura. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; ArgentinaElsevier2010-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/19025Gasparri, Nestor Ignacio; Parmuchi, Maria Gabriela; Bono, Julieta; Karszenbaum, Haydee; Montenegro, Celina Laura; Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina; Elsevier; Journal of Arid Environments; 74; 10; 1-2010; 1262-12700140-1963CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0140196310001059info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jaridenv.2010.04.007info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:34:55Zoai:ri.conicet.gov.ar:11336/19025instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:34:55.462CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
title Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
spellingShingle Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
Gasparri, Nestor Ignacio
Above-Ground Biomass
Chaco
Dry Forest
Regression Model
Remote Sensing
Vegetation Index
title_short Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
title_full Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
title_fullStr Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
title_full_unstemmed Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
title_sort Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina
dc.creator.none.fl_str_mv Gasparri, Nestor Ignacio
Parmuchi, Maria Gabriela
Bono, Julieta
Karszenbaum, Haydee
Montenegro, Celina Laura
author Gasparri, Nestor Ignacio
author_facet Gasparri, Nestor Ignacio
Parmuchi, Maria Gabriela
Bono, Julieta
Karszenbaum, Haydee
Montenegro, Celina Laura
author_role author
author2 Parmuchi, Maria Gabriela
Bono, Julieta
Karszenbaum, Haydee
Montenegro, Celina Laura
author2_role author
author
author
author
dc.subject.none.fl_str_mv Above-Ground Biomass
Chaco
Dry Forest
Regression Model
Remote Sensing
Vegetation Index
topic Above-Ground Biomass
Chaco
Dry Forest
Regression Model
Remote Sensing
Vegetation Index
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Above-ground biomass (AGB) is important to estimate total carbon pools in forests, where it has a key role in the global carbon cycle. We assessed correlations between spectral information and ground data to estimate AGB in the Semiarid Chaco, Argentina. Ground data (DBH, height and species of trees) were obtained from 15 samples (0.8 ha each) and AGB was estimated. Multi-temporal Landsat images were used to obtain spectral data (single bands/vegetation indexes) of the samples. Correlation tests between AGB and spectral bands and between AGB and vegetation indexes were performed for all dates. A strong correlation was found between spectral indexes and AGB in the early dry season (fall e May 12, 2002)<br />while poorer results were obtained for summer and winter. This would result from a differential phenological response of trees, shrubs and grasses to environmental conditions. A biomass predictive model was fitted using the NDVI of May 12, 2002 and a biomass map was obtained applying this regression. There was a rain-related regional pattern of AGB decrease in an eastewest direction, and a land-use related local pattern. Our results offer a great potential for increasing the understanding of dry Chaco forest structure and for improving carbon pools estimates. <br />
Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Parmuchi, Maria Gabriela. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; Argentina
Fil: Bono, Julieta. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; Argentina
Fil: Karszenbaum, Haydee. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Montenegro, Celina Laura. Secretaría de Ambiente y Desarrollo Sustentable. Dirección de Bosques; Argentina
description Above-ground biomass (AGB) is important to estimate total carbon pools in forests, where it has a key role in the global carbon cycle. We assessed correlations between spectral information and ground data to estimate AGB in the Semiarid Chaco, Argentina. Ground data (DBH, height and species of trees) were obtained from 15 samples (0.8 ha each) and AGB was estimated. Multi-temporal Landsat images were used to obtain spectral data (single bands/vegetation indexes) of the samples. Correlation tests between AGB and spectral bands and between AGB and vegetation indexes were performed for all dates. A strong correlation was found between spectral indexes and AGB in the early dry season (fall e May 12, 2002)<br />while poorer results were obtained for summer and winter. This would result from a differential phenological response of trees, shrubs and grasses to environmental conditions. A biomass predictive model was fitted using the NDVI of May 12, 2002 and a biomass map was obtained applying this regression. There was a rain-related regional pattern of AGB decrease in an eastewest direction, and a land-use related local pattern. Our results offer a great potential for increasing the understanding of dry Chaco forest structure and for improving carbon pools estimates. <br />
publishDate 2010
dc.date.none.fl_str_mv 2010-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/19025
Gasparri, Nestor Ignacio; Parmuchi, Maria Gabriela; Bono, Julieta; Karszenbaum, Haydee; Montenegro, Celina Laura; Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina; Elsevier; Journal of Arid Environments; 74; 10; 1-2010; 1262-1270
0140-1963
CONICET Digital
CONICET
url http://hdl.handle.net/11336/19025
identifier_str_mv Gasparri, Nestor Ignacio; Parmuchi, Maria Gabriela; Bono, Julieta; Karszenbaum, Haydee; Montenegro, Celina Laura; Assessing multi-temporal Landsat 7 ETM + images for estimating above-ground biomass in subtropical dry forests of Argentina; Elsevier; Journal of Arid Environments; 74; 10; 1-2010; 1262-1270
0140-1963
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0140196310001059
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jaridenv.2010.04.007
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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