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Aplicación de la teledetección en la estimación de las emisiones extraordinarias de CO2 por quemas de áreas insulares en el complejo litoral de Río Paraná (R. Argentina)

Authors: Sione, Walter Fabian; Aceñolaza, Pablo Gilberto; Zamboni, Lisandra Pamela; del Valle, Hector Francisco; Serafini, Maria Cristina; Gallardo Lancho, Juan F.;

Aplicación de la teledetección en la estimación de las emisiones extraordinarias de CO2 por quemas de áreas insulares en el complejo litoral de Río Paraná (R. Argentina)

Abstract

Los ambientes insulares del Complejo Litoral del Río Paraná (R. Argentina) están sujetos a incendios con recurrencia controlada por factores antropogénicos, climáticos y topográficos, con consecuencias a escala local, regional y global. Como resultado se producen variaciones en las emisiones de gases de efecto invernadero. Entre Marzo y Junio de 2008 se produjeron una serie de incendios extraordinarios que afectaron principalmente pastizales y juncales, ubicados en las porciones internas del Complejo. El objetivo de este trabajo fue estimar las emisiones de CO2 que se produjeron durante el citado período mediante la utilización de la teledetección e información de campo. A partir del uso de compuestos de imágenes MODIS, Landsat y CBERS, se determinaron 10 unidades de cobertura utilizando el índice de vegetación EVI (Enhanced Vegetation Index-MODIS), cuatro de las cuales correspondieron a vegetación herbácea. El área quemada (4550 km2) se determinó mediante la aplicación del índice BAI (Burnt Area Index). Las estimaciones de las emisiones de CO2 se realizaron en base a datos de biomasa herbácea propios, datos de campo y bibliográficos, utilizando un modelo paramétrico que incluye como variables la proporción de biomasa quemada (0,6), la relación de carbono total (Ct) fijado en biomasa (0,46) y la relación Ct/CO2 (1:3,67). Los incendios del Complejo Litoral del Río Paraná produjeron emisiones de CO2 cercanos a los 20 Mg C-CO2 ha-1 para juncales y pajonales del Delta, mientras que para las áreas del pre-Delta se calcularon emisiones entre 18 y 34 Mg C-CO2 ha-1 para canutillares y cortaderales. Las emisiones totales estimadas para el período fueron superiores a 7,7 Tg C-CO2. Estos niveles de emisión de CO2 son comparables a lo anualmente producido por una ciudad argentina de unos dos millones de habitantes.

Fires in wetland environments at the Paraná River Littoral Complex (Argentina) present recurrence controlled by anthropogenic, climatic and topographic factors, with local and global consequences. As a result, variations in the emissions of greenhouse gases can be found. During the period March/June 2008 there were a series of extraordinary fires that affected mainly grassland in the entire Littoral Complex. The aim of this study was to estimate CO2 emissions that occurred during the burning period of herbaceous plant communities in the area. To perform that, vegetation units were characterized from an unsupervised classification of the EVI index (Enhanced Vegetation Index, MODIS); as a result of, ten coverage units were identified; four of them corresponded to herbaceous vegetation. The burnt area (4550 km2) was determined by applying the index BAI (Burnt Area Index). Estimations of CO2 emissions were made based on data from herbaceous biomass, bibliographic and field data, using a parametric model that includes as variables: the proportion of burnt biomass (0.6), the relation of total C fixed in the biomass (Ct: 0.46), and the relation Ct/CO2 (3.67). Fires in the Paraná-river Littoral Complex produced CO2 emissions close to 20 Mg C ha-1 for grasses and bushlands, while for the pre-Delta areas the emissions were estimate between 18 and 34 Mg C ha-1. Estimated emissions for the evaluated period were higher than 7,7 Tg C-CO2; these levels of CO2 emissions are comparable to the annually produced by an Argentinean city with two millions inhabitants.

Fil: Aceñolaza, Pablo Gilberto. Universidad Autónoma de Entre Rí­os. Facultad de Ciencia y Tecnología. Centro Regional de Geomática; Argentina. Provincia de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Universidad Autónoma de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; Argentina. Universidad Nacional de Entre Ríos; Argentina

Fil: Gallardo Lancho, Juan F.. Consejo Superior de Investigaciones Cientificas. Instituto de Recursos Naturales y Agrobiología de Sevilla.; España

Fil: Zamboni, Lisandra Pamela. Universidad Autónoma de Entre Rí­os. Facultad de Ciencia y Tecnología. Centro Regional de Geomática; Argentina

Fil: Sione, Walter Fabian. Universidad Autónoma de Entre Rí­os. Facultad de Ciencia y Tecnología. Centro Regional de Geomática; Argentina

Fil: del Valle, Hector Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina

Fil: Serafini, Maria Cristina. Universidad Nacional de Luján; Argentina

Country
Argentina
Keywords

BAI, Imaginery, Percepción remota, EVI, Fires, AMBIENTES FLUVIALES, Incendios, MODIS, https://purl.org/becyt/ford/1.5, PERCEPCIÓN REMOTA, INCENDIOS, https://purl.org/becyt/ford/1, Ambientes fluviales, Riparian ecosystems

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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