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Abstract:

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.

Registro:

Documento: Artículo
Título:Assessing multi-temporal Landsat 7 ETM+ images for estimating above-ground biomass in subtropical dry forests of Argentina
Autor:Gasparri, N.I.; Parmuchi, M.G.; Bono, J.; Karszenbaum, H.; Montenegro, C.L.
Filiación:Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Instituto de Ecología Regional (IER), Facultad de Ciencias Naturales e Instituto Miguel Lillo, Universidad Nacional de Tucumán (UNT), C.C. 34, 4107, Yerba Buena, Tucumán, Argentina
Unidad de Manejo del Sistema de Evaluación Forestal (UMSEF), Dirección de Bosques, Secretaría de Ambiente y Desarrollo Sustentable (SAyDS), San Martín 451, C1004AAI, Buenos Aires, Argentina
Instituto de Astronomía y Física del Espacio (IAFE-CONICET), Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina
Palabras clave: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
Año:2010
Volumen:74
Número:10
Página de inicio:1262
Página de fin:1270
DOI: http://dx.doi.org/10.1016/j.jaridenv.2010.04.007
Título revista:Journal of Arid Environments
Título revista abreviado:J. Arid Environ.
ISSN:01401963
CODEN:JAEND
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01401963_v74_n10_p1262_Gasparri

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Citas:

---------- APA ----------
Gasparri, N.I., Parmuchi, M.G., Bono, J., Karszenbaum, H. & Montenegro, C.L. (2010) . Assessing multi-temporal Landsat 7 ETM+ images for estimating above-ground biomass in subtropical dry forests of Argentina. Journal of Arid Environments, 74(10), 1262-1270.
http://dx.doi.org/10.1016/j.jaridenv.2010.04.007
---------- CHICAGO ----------
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" . Journal of Arid Environments 74, no. 10 (2010) : 1262-1270.
http://dx.doi.org/10.1016/j.jaridenv.2010.04.007
---------- MLA ----------
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" . Journal of Arid Environments, vol. 74, no. 10, 2010, pp. 1262-1270.
http://dx.doi.org/10.1016/j.jaridenv.2010.04.007
---------- VANCOUVER ----------
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. J. Arid Environ. 2010;74(10):1262-1270.
http://dx.doi.org/10.1016/j.jaridenv.2010.04.007