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Auteur Pedro Javier Herrera |
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Basal area and diameter distribution estimation using stereoscopic hemispherical images / Mariola Sánchez-González in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)
[article]
Titre : Basal area and diameter distribution estimation using stereoscopic hemispherical images Type de document : Article/Communication Auteurs : Mariola Sánchez-González, Auteur ; Miguel Cabrera, Auteur ; Pedro Javier Herrera, Auteur Année de publication : 2016 Article en page(s) : pp 605 - 616 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement d'images
[Termes IGN] courbe de Pearson
[Termes IGN] diamètre des arbres
[Termes IGN] image hémisphérique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle stéréoscopique
[Termes IGN] placette d'échantillonnage
[Termes IGN] surface terrière
[Termes IGN] tronc
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) In recent years, proximal sensing data has increasingly been used to optimize forest inventories. In this paper, we present a forest inventory methodology based on stereoscopic hemispherical images. An automated pixel-based approach and a user-guided “region growing” approach have been developed for image matching. To estimate the basal area, number of trees and mean diameter, the sampling probability is determined for each tree. The accuracy and precision of the estimates derived from stereoscopic hemispherical images was analyzed for a set of National Forest Inventory plots. The results revealed that tree matching depends on the species, the distance to the target tree and the diameter. The Pearson correlation coefficient was 0.86 for the mean diameter and 0.89 for the basal area, whereas for the number of trees per hectare it was 0.59. The proposed methods may be used in large scale forest inventories as a cost-efficient way of obtaining data on diameter distribution and basal area from field surveys following a two-stage scheme combined with remote sensing techniques. Numéro de notice : A2016-607 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.8.605 En ligne : http://dx.doi.org/10.14358/PERS.82.8.605 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81805
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 8 (August 2016) . - pp 605 - 616[article]