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scientifique

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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 2 (February 2016) . - pp 679 - 696 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 3D Résumé : (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 [article]

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065-2016021	SL	Revue	Centre de documentation	Revues en salle	Disponible

Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology / Jan U.H. Eitel in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 229 – 240 Titre : Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology Type de document : Article/Communication Auteurs : Jan U.H. Eitel, Auteur ; Troy Magney, Auteur ; Lee Alexander Vierling, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 229 – 240 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] agriculture de précision [Termes IGN] biochimie [Termes IGN] distribution binomiale [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] données lidar Résumé : (Auteur) Advanced technologies for improved nitrogen (N) fertilizer management are paramount for sustainably meeting future food demands. Green laser systems that measure pulse return intensity can provide more reliable information about foliar N than can traditional passive remote sensing devices during the critical early crop growth stages (e.g., before canopy closure when vegetation and soil signals are spectrally mixed) when further decisions regarding N management can be made. However, current green laser systems are not designed for agricultural applications and only employ a single green laser wavelength, which may limit applications because many factors that require normalization techniques can affect pulse return intensity. Here, we describe the design of a tractor-mountable, green (532 nm)- and red (658 nm) dual wavelength laser system and evaluate the potential of an additional red reference wavelength to improve laser based estimates of foliar N by calculating laser spectral indices based on ratio combinations of green laser return intensity (GLRI) and red laser return intensity (RLRI). We hypothesized that such laser spectral indices aid in accounting for factors that confound laser based foliar N estimates including variations in leaf angle, measurement distance, soil returns, and mixed edge returns. Leaf level measurements in winter wheat (Triticum aestivum) revealed that the two laser spectral indices improved the relationship with foliar N (r2 > 0.71, RMSE Numéro de notice : A2014-531 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.09.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.09.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74144 [article]

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081-2014111	RAB	Revue	Centre de documentation	En réserve L003	Disponible