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Incorporating crown shape information for identifying ash tree species / Haijian Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 8 (août 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 8 (août 2018) . - pp 495 - 503 Titre : Incorporating crown shape information for identifying ash tree species Type de document : Article/Communication Auteurs : Haijian Liu, Auteur ; Changshan Wu, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Fraxinus (genre) [Termes IGN] fusion de données [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Milwaukee [Termes IGN] photo-interprétation assistée par ordinateur [Termes IGN] zone urbaine Résumé : (Auteur) Identifying ash trees from other common deciduous trees is challenging due to subtle spectral differences of foliage among species. Although many researchers have integrated lidar-derived tree height and crown size metrics to improve tree species classification accuracy, these simple biophysical attributes provide inadequate explanatory power in distinguishing ash trees (Fraxinus, spp.) in urban ecosystems. To address this issue, shape-related features, including crown shape index (SI) and coefficient of variation (CV) of crown height, were extracted from lidar data, and fused with treetopbased spectra for ash tree species identification in Milwaukee City, Wisconsin, United States. Analysis results indicate shape features including SI and CV play a big role in improving the accuracy for ash tree identification. Specifically, Fusion of CV and treetop-based spectra improved the overall accuracy from 81.9 percent to 89 percent, and McNemar tests indicated the differences in accuracy between CV fusion and tree height fusion was statistically significant (p = 0.016). Numéro de notice : A2018-360 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.8.495 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.14358/PERS.84.8.495 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90600 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2018081	RAB	Revue	Centre de documentation	En réserve L003	Disponible