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

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...

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Autores principales: Gasparri, N.I., Parmuchi, M.G., Bono, J., Karszenbaum, H., Montenegro, C.L.
Formato: JOUR
Materias:
Above-ground biomass
Chaco
Dry forest
Regression model
Remote sensing
Vegetation index
aboveground biomass
carbon cycle
correlation
data set
dry forest
ground-based measurement
height determination
image analysis
land use
Landsat
phenology
regression analysis
remote sensing
seasonality
vegetation index
vegetation mapping
Argentina
Chaco [Argentina]
Poaceae
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01401963_v74_n10_p1262_Gasparri
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_01401963_v74_n10_p1262_Gasparri
record_format dspace
spelling todo:paper_01401963_v74_n10_p1262_Gasparri2023-10-03T14:58:19Z Assessing multi-temporal Landsat 7 ETM+ images for estimating above-ground biomass in subtropical dry forests of Argentina Gasparri, N.I. Parmuchi, M.G. Bono, J. Karszenbaum, H. Montenegro, C.L. Above-ground biomass Chaco Dry forest Regression model Remote sensing Vegetation index aboveground biomass carbon cycle correlation data set dry forest ground-based measurement height determination image analysis land use Landsat phenology regression analysis remote sensing seasonality vegetation index vegetation mapping Argentina Chaco [Argentina] Poaceae 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 - 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 east-west 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. © 2010 Elsevier Ltd. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01401963_v74_n10_p1262_Gasparri
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Above-ground biomass
Chaco
Dry forest
Regression model
Remote sensing
Vegetation index
aboveground biomass
carbon cycle
correlation
data set
dry forest
ground-based measurement
height determination
image analysis
land use
Landsat
phenology
regression analysis
remote sensing
seasonality
vegetation index
vegetation mapping
Argentina
Chaco [Argentina]
Poaceae
spellingShingle Above-ground biomass
Chaco
Dry forest
Regression model
Remote sensing
Vegetation index
aboveground biomass
carbon cycle
correlation
data set
dry forest
ground-based measurement
height determination
image analysis
land use
Landsat
phenology
regression analysis
remote sensing
seasonality
vegetation index
vegetation mapping
Argentina
Chaco [Argentina]
Poaceae
Gasparri, N.I.
Parmuchi, M.G.
Bono, J.
Karszenbaum, H.
Montenegro, C.L.
Assessing multi-temporal Landsat 7 ETM+ images for estimating above-ground biomass in subtropical dry forests of Argentina
topic_facet Above-ground biomass
Chaco
Dry forest
Regression model
Remote sensing
Vegetation index
aboveground biomass
carbon cycle
correlation
data set
dry forest
ground-based measurement
height determination
image analysis
land use
Landsat
phenology
regression analysis
remote sensing
seasonality
vegetation index
vegetation mapping
Argentina
Chaco [Argentina]
Poaceae
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 - 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 east-west 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. © 2010 Elsevier Ltd.
format JOUR
author Gasparri, N.I.
Parmuchi, M.G.
Bono, J.
Karszenbaum, H.
Montenegro, C.L.
author_facet Gasparri, N.I.
Parmuchi, M.G.
Bono, J.
Karszenbaum, H.
Montenegro, C.L.
author_sort Gasparri, N.I.
title Assessing multi-temporal Landsat 7 ETM+ images for estimating above-ground biomass in subtropical dry forests of Argentina
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
url http://hdl.handle.net/20.500.12110/paper_01401963_v74_n10_p1262_Gasparri
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