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Estimación de biomasa aérea de <i>Eucalyptus grandis</i> y <i>Pinus</i> spp. usando imágenes Sentinel1A y Sentinel2A en Colombia

dc.contributor.authorTovar Blanco, Adriana Lizethspa
dc.contributor.authorLizarazo Salcedo, Iván Albertospa
dc.contributor.authorRodríguez Eraso, Nellyspa
dc.date.accessioned2020-01-01 00:00:00
dc.date.accessioned2023-09-19T21:10:22Z
dc.date.available2020-01-01 00:00:00
dc.date.available2023-09-19T21:10:22Z
dc.date.issued2020-01-01
dc.identifier.issn0120-0739
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/44469
dc.description.abstractLa estimación de la biomasa aérea usando sistemas de aprendizaje automático es útil para conocer de forma rápida y sistemática la productividad en bosques y plantaciones. En este estudio la biomasa aérea (AGB) se estimó para las plantaciones forestales de Eucalyptus grandis y Pinus spp. ubicadas en el sector centro-oriental del departamento del Cauca (Colombia). Las variables de mayor incidencia en AGB para E. grandis fueron las bandas SWIR y las texturas de la polarización VV; mientras que para P. spp fueron CorrelaciónVV, GNDVI y B2. Los modelos obtenidos combinando datos ópticos y SAR muestran mejores resultados con un coeficiente de determinación R2 = 0.27 y un error cuadrado promedio EMC = 42.75 t.ha-1 en E. grandis, y R2 = 0.36 y EMC = 141.71 t.ha-1 en Pinus spp. El estudio demostró el potencial de combinar datos Sentinel para estimar la AGB en plantaciones comerciales y el uso de Randon forest para la construcción de los modelos, pero aún se requiere el estudio del acoplamiento espacial de los datos de campo y su incidencia en las estimaciones de los modelos, así como la pertinencia de adelantar estudios a nivel de especies para evaluar su incertidumbre.  spa
dc.description.abstractAboveground biomass estimation, using machine-learning systems, is useful for rapid and systematic knowledge of productivity in forests and plantations. In this study, forest aboveground biomass (AGB) was estimated for plantations of Eucalyptus grandis and Pinus spp located in the central-eastern sector of the department of Cauca (Colombia). The variables with the highest incidence in AGB for E. grandis were the SWIR bands and the VV polarization textures, while for Pinus spp. were Correlationvv, GNDVI and B2. The models obtained by combining optical data and SAR show better results with a determination coefficient R2 = 0.27 and an average square error EMC = 42.75 t.ha-1 in E. grandis, and R2 = 0.36 and EMC = 141.71 t.ha-1 in Pinus spp. The study demonstrated the potential of combining Sentinel data to estimate AGB in commercial plantations and the use of Randon forest for model construction.eng
dc.format.mimetypeapplication/pdfspa
dc.format.mimetypetext/xmlspa
dc.language.isospaspa
dc.publisherUniversidad Distrital Francisco José de Caldasspa
dc.rightsColombia forestal - 2020spa
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/spa
dc.sourcehttps://revistas.udistrital.edu.co/index.php/colfor/article/view/14854spa
dc.subjectRemote sensingeng
dc.subjectcomercial forest plantationeng
dc.subjectRandom Foresteng
dc.subjectSentineleng
dc.subjectC-bandeng
dc.subjectGLCMeng
dc.subjectVegetation indexeng
dc.subjecttextureseng
dc.subjectAGBeng
dc.subjectPercepción remotaspa
dc.subjectplantación forestal comercialspa
dc.subjectRandom Forestspa
dc.subjectSentinelspa
dc.subjectbanda Cspa
dc.subjectGLCMspa
dc.titleEstimación de biomasa aérea de <i>Eucalyptus grandis</i> y <i>Pinus</i> spp. usando imágenes Sentinel1A y Sentinel2A en Colombiaspa
dc.typeArtículo de revistaspa
dc.identifier.doi10.14483/2256201X.14854
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.localJournal articleeng
dc.title.translatedEstimating aboveground biomass of Eucalyptus grandis and Pinus spp. using Sentinel-1A and Sentinel-2A images in Colombiaeng
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa
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