Show simple item record

dc.contributorEscuela Superior y Tecnica de Ingenieros de Minases_ES
dc.contributor.authorHerrero-Huerta, Mónica
dc.contributor.authorLindenbergh, Roderik
dc.contributor.authorRodríguez-Gonzálvez, Pablo
dc.contributor.otherIngeniería Cartografica, Geodesica y Fotogrametriaes_ES
dc.date2018-04-24
dc.date.accessioned2018-12-27T00:05:38Z
dc.date.available2018-12-27T00:05:38Z
dc.date.issued2018-12-27
dc.identifier.citationPLoS ONE 13(4): e0196004es_ES
dc.identifier.urihttp://hdl.handle.net/10612/9277
dc.descriptione0196004es_ES
dc.description.abstractIn an urban context, tree data are used in city planning, in locating hazardous trees and in environmental monitoring. This study focuses on developing an innovative methodology to automatically estimate the most relevant individual structural parameters of urban trees sampled by a Mobile LiDAR System at city level. These parameters include the Diameter at Breast Height (DBH), which was estimated by circle fitting of the points belonging to different height bins using RANSAC. In the case of non-circular trees, DBH is calculated by the maximum distance between extreme points. Tree sizes were extracted through a connectivity analysis. Crown Base Height, defined as the length until the bottom of the live crown, was calculated by voxelization techniques. For estimating Canopy Volume, procedures of mesh generation and α-shape methods were implemented. Also, tree location coordinates were obtained by means of Principal Component Analysis. The workflow has been validated on 29 trees of different species sampling a stretch of road 750 m long in Delft (The Netherlands) and tested on a larger dataset containing 58 individual trees. The validation was done against field measurements. DBH parameter had a correlation R2 value of 0.92 for the height bin of 20 cm which provided the best results. Moreover, the influence of the number of points used for DBH estimation, considering different height bins, was investigated. The assessment of the other inventory parameters yield correlation coefficients higher than 0.91. The quality of the results confirms the feasibility of the proposed methodology, providing scalability to a comprehensive analysis of urban treeses_ES
dc.languageenges_ES
dc.subjectCartografíaes_ES
dc.titleAutomatic tree parameter extraction by a Mobile LiDAR System in an urban contextes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.peerreviewedSIes_ES


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record