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Estimación de biomasa aérea en Colombia a partir de imágenes MODIS

Aerial biomass estimation in Colombia based on MODIS images

dc.creatorAnaya Acevedo, J. A.spa
dc.creatorChuvieco Salinero, Emiliospa
dc.creatorPalacios Orueta, Aliciaspa
dc.date.accessioned2017-06-15T22:05:18Z
dc.date.available2017-06-15T22:05:18Z
dc.date.created2008
dc.identifier.citationAnaya, J. A., Chuvieco, E., & Palacios, A. (2008). Estimación de biomasa aérea en Colombia a partir de imágenes MODIS. Revista de Teledetección, 2008 (30), 5-22.spa
dc.identifier.issn19888740
dc.identifier.urihttp://hdl.handle.net/11407/3412
dc.descriptionSe propone un método para aumentar el nivel de detalle en estimaciones regionales de biomasa aérea basado en productos MODIS y mediciones de biomasa aérea en campo. El área de estudio se delimita entre 10 grados norte y 3 grados sur con un área de 1,139,012 km2 correspondiente al área continental de Colombia. La vegetación se clasificó en pastizales, bosques secundarios y bosques primarios con el fin de mejorar las estimaciones. Se utilizó como variable explicativa de biomasa en bosques primarios y bosques secundarios la proporción de arbolado por píxel de MOD44 (VCF) siguiendo una relación exponencial, mientras que el índice de vegetación EVI (MOD13A1) se utilizó como variable explicativa de biomasa en pastizales siguiendo una relación lineal. La biomasa aérea en pastizales es altamente dinámica en el tiempo y por tanto se estimó su variación con intervalos de 16 días para el año 2004. Por su parte los bosques secundarios tienen una dificultad adicional al no poder separarse de los bosques primarios con el producto MOD44 (VCF) y presentar valores de biomasa muy inferiores, por lo que se utilizaron mapas auxiliares de vegetación. Los intervalos de confianza de la regresión exponencial aumentan al aumentar la biomasa por tanto la incertidumbre es muy alta para la biomasa total: entre 3,473 y 23,693 millones de toneladas con una media de 16,467. Sin embargo la diferencia de los resultados con estudios previos es mínima.spa
dc.descriptionThis paper presents a method to increase level of detail for above ground biomass estimates at a regional scale. The methodology and materials are based on MODIS products and field measurements corresponding to the continental area of Colombia, covering from 4 degrees south up to 12 degrees north of the Equator with a total of 1,139,012 km2 . Vegetation was classified in three broad classes: grasslands, secondary forests and primary forests which have been proved to enhance biomass estimates. MOD44 (VCF) was used as explanatory variable for primary and secondary forests following an exponential relationship, while EVI (MOD13A1) was used as explanatory variable for grasslands following a linear relationship; biomass for this vegetation class was estimated every 16 days given its large variation throughout the year. Vegetation maps where used to separate primary forests from secondary forest, since the latter shown lower biomass levels. Despite the uncertainty our biomass results are within the estimates of previous studies. Confidence intervals of the exponential regression are larger as the biomass values increases, for this reason the uncertainty is quite high ranging from 3,473 to 23,693 millions of tons with a mean of 16,467.spa
dc.language.isospa
dc.publisherAsociación Española De Teledetecciónspa
dc.relation.isversionofhttp://www.aet.org.es/revistas/revista30/numero30_1.pdfspa
dc.sourceRevista de Teledetecciónspa
dc.subjectBiomasaspa
dc.subjectTrópicospa
dc.subjectModisspa
dc.subjectVCFspa
dc.subjectEVIspa
dc.subjectBiomassspa
dc.subjectTropicsspa
dc.subjectModisspa
dc.subjectVCFspa
dc.subjectEVIspa
dc.titleEstimación de biomasa aérea en Colombia a partir de imágenes MODISspa
dc.titleAerial biomass estimation in Colombia based on MODIS imagesspa
dc.typeArticleeng
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.publisher.programIngeniería Ambientalspa
dc.publisher.facultyFacultad de Ingenieríasspa
dc.creator.affiliationAnaya Acevedo, J. A.; Universidad de Medellínspa
dc.creator.affiliationChuvieco Salinero, Emilio; Universidad de Alcaláspa
dc.creator.affiliationPalacios Orueta, Alicia; Universidad Politécnica de Madrid, Españaspa
dc.relation.ispartofesRevista de Teledetección. 2008. 30: 5-22spa
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