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Automatic estimation of olive tree dendrometric parameters based on airborne laser scanning data using alpha-shape and principal component analysis

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Automatic estimation of olive tree dendrometric parameters based on airborne laser scanning data using alpha-shape and principal component analysis

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dc.contributor.author Hadas, Edyta es_ES
dc.contributor.author Borkowski, Andrzej es_ES
dc.contributor.author Estornell Cremades, Javier es_ES
dc.contributor.author Tymkow, Przemyslaw es_ES
dc.date.accessioned 2018-11-21T21:05:57Z
dc.date.available 2018-11-21T21:05:57Z
dc.date.issued 2017 es_ES
dc.identifier.issn 1548-1603 es_ES
dc.identifier.uri http://hdl.handle.net/10251/112971
dc.description.abstract [EN] The aim of this study is to present an automatic approach for olive tree dendrometric parameter estimation from airborne laser scanning (ALS) data. The proposed method is based on a unique combination of the alpha-shape algorithm applied to normalized point cloud and principal component analysis. A key issue of the alpha-shape algorithm is to define the ¿ parameter, as it directly affects the crown delineation results. We propose to adjust this parameter based on a group of representative trees in an orchard for which the classical field measurements were performed. The best value of the ¿ parameter is one whose correlation coefficient of dendrometric parameters between field measurements and estimated values is the highest. We determined crown diameters as principal components of ALS points representing a delineated crown. The method was applied to a test area of an olive orchard in Spain. The tree dendrometric parameters estimated from ALS data were compared with field measurements to assess the quality of the developed approach. We found the method to be equally good or even superior to previously investigated semi-automatic methods. The average error is 19% for tree height, 53% for crown base height, and 13% and 9% for the length of the longer diameter and perpendicular diameter, respectively. es_ES
dc.language Inglés es_ES
dc.publisher Taylor & Francis es_ES
dc.relation.ispartof GIScience & Remote Sensing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Remote sensing es_ES
dc.subject Airborne laser scanning es_ES
dc.subject Alpha-shape es_ES
dc.subject Principal component analysis es_ES
dc.subject Agriculture es_ES
dc.subject Trees es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.title Automatic estimation of olive tree dendrometric parameters based on airborne laser scanning data using alpha-shape and principal component analysis es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1080/15481603.2017.1351148 es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.description.bibliographicCitation Hadas, E.; Borkowski, A.; Estornell Cremades, J.; Tymkow, P. (2017). Automatic estimation of olive tree dendrometric parameters based on airborne laser scanning data using alpha-shape and principal component analysis. GIScience & Remote Sensing. 54(6):898-917. doi:10.1080/15481603.2017.1351148 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1080/15481603.2017.1351148 es_ES
dc.description.upvformatpinicio 898 es_ES
dc.description.upvformatpfin 917 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 54 es_ES
dc.description.issue 6 es_ES
dc.relation.pasarela S\349688 es_ES


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