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Multisensor and multispectral Lidar characterization and classification of a forest environment / Christopher Hopkinson in Canadian journal of remote sensing, vol 42 n° 5 ([01/05/2016])  

Public [article]  inCanadian journal of remote sensing > vol 42 n° 5 [01/05/2016] . - pp 501 - 520 Titre : Multisensor and multispectral Lidar characterization and classification of a forest environment Type de document : Article/Communication Auteurs : Christopher Hopkinson, Auteur ; Laura Chasmer, Auteur ; Chris Gynan, Auteur ; Craig Mahoney, Auteur ; Michael Sitar, Auteur Année de publication : 2016 Article en page(s) : pp 501 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] erreur systématique [Termes IGN] feuille (végétation) [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] rayonnement proche infrarouge Résumé : (auteur) Airborne LiDAR is increasingly used in forest carbon, ecosystem, and resource monitoring. For practical design and manufacture reasons, the 1064 nm near-infrared (NIR) wavelength has been the most commonly adopted, and most literature in this field represents sampling characteristics in this wavelength. However, due to eye-safety and application-specific needs, other common wavelengths are 1550 nm and 532 nm. All provide canopy structure reconstructions that can be integrated or compared through space and time but the consistency or complementarity of 3D airborne LiDAR data sampled at multiple wavelengths is poorly understood. Here, we report on multispectral LiDAR missions carried out in 2013 and 2015 over a managed forest research site. The 1st used 3 independent sensors, and the 2nd used a single sensor carrying 3 lasers. The experiment revealed differences in proportions of returns at ground level, vertical foliage distributions, and gap probability across wavelengths. Canopy attenuation was greatest at 532 nm, presumably due to leaf tissue absorption. Relative to 1064 nm, foliage was undersampled at midheight percentiles at 1550 nm and 532 nm. Multisensor data demonstrated differences in foliage characterization due to combined influences of wavelength and acquisition configuration. Single-sensor multispectral data were more stable but demonstrated clear wavelength-dependent variation that could be exploited in intensity-based land cover classification without the aid of 3D derivatives. This work sets the stage for improvements in land surface classification and vertical foliage partitioning through the integration of active spectral and structural laser return information. Numéro de notice : A2016--128 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1080/07038992.2016.1196584 En ligne : http://dx.doi.org/10.1080/07038992.2016.1196584 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85114 [article]