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A local projection-based approach to individual tree detection and 3-D crown delineation in multistoried coniferous forests using high-density airborne LiDAR data / Aravind Harikumar in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 2 (February 2019) . - pp 1168 - 1182 Titre : A local projection-based approach to individual tree detection and 3-D crown delineation in multistoried coniferous forests using high-density airborne LiDAR data Type de document : Article/Communication Auteurs : Aravind Harikumar, Auteur ; Francesca Bovolo, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2019 Article en page(s) : pp 1168 - 1182 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] arbre dominant [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] forêt [Termes descripteurs IGN] houppier [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] projection [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] Trente Résumé : (Auteur) Accurate crown detection and delineation of dominant and subdominant trees are crucial for accurate inventorying of forests at the individual tree level. The state-of-the-art tree detection and crown delineation methods have good performance mostly with dominant trees, whereas exhibits a reduced accuracy when dealing with subdominant trees. In this paper, we propose a novel approach to accurately detect and delineate both the dominant and subdominant tree crowns in conifer-dominated multistoried forests using small footprint high-density airborne Light Detection and Ranging data. Here, 3-D candidate cloud segments delineated using a canopy height model segmentation technique are projected onto a novel 3-D space where both the dominant and subdominant tree crowns can be accurately detected and delineated. Tree crowns are detected using 2-D features derived from the projected data. The delineation of the crown is performed at the voxel level with the help of both the 2-D features and 3-D texture information derived from the cloud segment. The texture information is modeled by using 3-D Gray Level Co-occurrence Matrix. The performance evaluation was done on a set of six circular plots for which reference data are available. The high detection and delineation accuracies obtained over the state of the art prove the performance of the proposed method. Numéro de notice : A2019-112 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2865014 date de publication en ligne : 10/09/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2865014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92452 [article]