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Auteur Guang Zheng |
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Assessing the contribution of woody materials to forest angular gap fraction and effective leaf area index using terrestrial laser scanning data / Guang Zheng in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)
[article]
Titre : Assessing the contribution of woody materials to forest angular gap fraction and effective leaf area index using terrestrial laser scanning data Type de document : Article/Communication Auteurs : Guang Zheng, Auteur ; Lixia Ma, Auteur ; Wei He, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1475 - 1487 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] bois sur pied
[Termes IGN] classification automatique
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] indice foliaire
[Termes IGN] Leaf Area Index
[Termes IGN] photosynthèse
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) The spatial distribution of the photosynthetic components of a forest canopy plays a key role in ecological related processes such as gas exchange, photosynthesis, and evapotranspiration through affecting radiation regimes of the forest canopy. However, quantitative evaluation of woody materials' contribution to effective leaf area index (LAIe) using 3-D terrestrial laser scanning (TLS) is a challenging work. In this paper, we first identified the differences between directional gap fraction (DGF) and angular gap fraction (AGF) and then developed a local geometric feature-based approach to automatically classify a TLS forest point cloud data (PCD) into three different classes, including nonphotosynthetic canopy components (i.e., stem and branch points), photosynthetic canopy components (i.e., leaf and grass points), and bare ground. In addition, we proposed a new approach named “radial hemispherical point cloud slicing” algorithm to investigate the 3-D spatial distribution of foliage elements and retrieve LAIe from a given forest PCD. Our results showed that nonphotosynthetic canopy components contributed from 19% to 54% to LAIe depending on various forest densities. Moreover, TLS-based LAIe estimates can explain 74.27% variations of digital-hemispherical-photography-based LAIe values with a linear regression statistical model. This paper provides a theoretical foundation for LAI estimation based on the PCD generated using the TLS system and facilitates the application of TLS on retrieving 3-D forest canopy structural biophysical parameters. Numéro de notice : A2016-132 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2481492 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2481492 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80019
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 3 (March 2016) . - pp 1475 - 1487[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016031 SL Revue Centre de documentation Revues en salle Disponible Improved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial Lidar point cloud data of forest canopies / Lixia Ma in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)
[article]
Titre : Improved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial Lidar point cloud data of forest canopies Type de document : Article/Communication Auteurs : Lixia Ma, Auteur ; Guang Zheng, Auteur ; Jan U.H. Eitel, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 679 - 696 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] canopée
[Termes IGN] classification automatique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuillu
[Termes IGN] Leaf Area Index
[Termes IGN] photosynthèse
[Termes IGN] Pinophyta
[Termes IGN] reconnaissance de formes
[Termes IGN] semis de points
[Termes IGN] télémétrie laser sur satellite
[Termes IGN] zone saillante 3DRésumé : (Auteur) Accurate separation of photosynthetic and nonphotosynthetic components in a forest canopy from 3-D terrestrial laser scanning (TLS) data is a challenging but of key importance to understand the spatial distribution of the radiation regime, photosynthetic processes, and carbon and water exchanges of the forest canopy. The objective of this paper was to improve current methods for separating photosynthetic and nonphotosynthetic components in TLS data of forest canopies by adding two additional filters only based on its geometric information. By comparing the proposed approach with the eigenvalues plus color information-based method, we found that the proposed approach could effectively improve the overall producer's accuracy from 62.12% to 95.45%, and the overall classification producer's accuracy would increase from 84.28% to 97.80% as the forest leaf area index (LAI) decreases from 4.15 to 3.13. In addition, variations in tree species had negligible effects on the final classification accuracy, as shown by the overall producer's accuracy for coniferous (93.09%) and broadleaf (94.96%) trees. To remove quantitatively the effects of the woody materials in a forest canopy for improving TLS-based LAI estimates, we also computed the “woody-to-total area ratio” based on the classified linear class points from an individual tree. Automatic classification of the forest point cloud data set will facilitate the application of TLS on retrieving 3-D forest canopy structural parameters, including LAI and leaf and woody area ratios. Numéro de notice : A2016-114 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2459716 En ligne : https://doi.org/10.1109/TGRS.2015.2459716 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79992
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 2 (February 2016) . - pp 679 - 696[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016021 SL Revue Centre de documentation Revues en salle Disponible