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resumen

Resumen
Determining the percentage of tree crown cover is extremely important to establish in advance which forest types can be classified with high resolution sensors such as Landsat. This paper describes the determination of a tree crown coverage threshold to define whether a pixel is classified as a forest or not. The methodology consists in the comparison of forest/non-forest classifications generated from Landsat images with tree crown cover maps obtained [ver mas...]
dc.contributor.authorBanchero, Santiago
dc.contributor.authorVeron, Santiago Ramón
dc.contributor.authorDe Abelleyra, Diego
dc.contributor.authorFerraina, Antonella
dc.contributor.authorPropato, Tamara Sofia
dc.contributor.authorGomez Taffarel, Maria Cielo
dc.contributor.authorDieguez, Hernán
dc.date.accessioned2021-10-15T10:48:27Z
dc.date.available2021-10-15T10:48:27Z
dc.date.issued2021-07-12
dc.identifier.urihttp://hdl.handle.net/20.500.12123/10496
dc.identifier.urihttps://igarss2021.com/call_for_papers.php#
dc.description.abstractDetermining the percentage of tree crown cover is extremely important to establish in advance which forest types can be classified with high resolution sensors such as Landsat. This paper describes the determination of a tree crown coverage threshold to define whether a pixel is classified as a forest or not. The methodology consists in the comparison of forest/non-forest classifications generated from Landsat images with tree crown cover maps obtained from PlanetScope very high resolution images, considering those pixels that exceed a given canopy cover threshold (eg. 5-10-15-...90-95-100%) as forest. The canopy coverage threshold was the one that minimized the difference between the Landsat classification and the maps generated from Planet images.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherIEEE Geoscience and Remote Sensing Societyes_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceInternational Geoscience and Remote Sensing Symposium (IGARSS) Belgium 12-16 july, 2021es_AR
dc.subjectImage Processingeng
dc.subjectTratamiento de Imágeneses_AR
dc.subject.otherVegetation Covereng
dc.subject.otherCubierta Vegetales_AR
dc.subject.otherplanet scopees_AR
dc.subject.otheralcance del planetaes_AR
dc.subject.otherUnsupervised learninges_AR
dc.subject.otherAprendizaje sin supervisiónes_AR
dc.titleWhich pixel is a forest? Tree crown delineation using VHR images to estimate tree cover in landsat based classificationes_AR
dc.typeinfo:ar-repo/semantics/documento de conferenciaes_AR
dc.typeinfo:eu-repo/semantics/conferenceObjectes_AR
dc.typeinfo:eu-repo/semantics/acceptedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.filFil: Banchero, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentinaes_AR
dc.description.filFil: Verón, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires; Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: de Abelleyra, D. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentinaes_AR
dc.description.filFil: Ferraina, A. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires; Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Propato, T. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires; Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Gomez Taffarel, María Cielo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentinaes_AR
dc.description.filFil: Dieguez, Hernán. Universidad de Buenos Aires; Facultad de Agronomía; Argentinaes_AR
dc.subtypeponencia


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