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Stem volume and above-ground biomass estimation of individual pine trees from LiDAR data: contribution of full-waveform signals / Tristan Allouis in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 6 n° 2 part 3 (April 2013)  

Public [article]  inIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing > vol 6 n° 2 part 3 (April 2013) . - pp 924 - 934 Titre : Stem volume and above-ground biomass estimation of individual pine trees from LiDAR data: contribution of full-waveform signals Type de document : Article/Communication Auteurs : Tristan Allouis, Auteur ; Sylvie Durrieu, Auteur ; Cédric Vega , Auteur ; Pierre Couteron, Auteur Année de publication : 2013 Article en page(s) : pp 924 - 934 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] estimation statistique [Termes descripteurs IGN] forme d'onde pleine [Termes descripteurs IGN] modèle mathématique [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] signal lidar [Termes descripteurs IGN] volume en bois Résumé : (auteur) The diameter at breast height (DBH) is the most extensively measured parameter in the field for estimating stem volume and aboveground biomass of individual trees. However, DBH can not be measured from airborne or spaceborne light detection and ranging (LiDAR) data. Consequently, volume and biomass must be estimated from LiDAR data using other tree metrics. The objective of this paper is to examine whether full-waveform (FW) LiDAR data can improve volume and biomass estimation of individual pine trees, when compared to usual discrete-return LiDAR data. Sets of metrics are derived from canopy height model (CHM-only metrics), from the vertical distribution of discrete-returns (CHM+DR metrics), and from full-waveform LiDAR data (CHM+FW metrics). In each set, the most relevant and non-collinear metrics were selected using a combination of methods using best subset and variance inflation factor, in order to produce predictive models of volume and biomass. CHM-only metrics (tree height and tree bounding volume [tree height x crown area] provided volume and biomass estimates of individual trees with an error (mean error ± standard deviation) of 2% ± 26% and -15% ±49%, which is equivalent to previous studies. CHM+FW metrics did not improve stem volume estimates (5% ± 31%), but they increased the accuracy of aboveground biomass estimates ( -4%±31%). The approach is limited by the delineation of individual trees. However, the results highlight the potential of full-waveform LiDAR data to improve aboveground biomass estimates through a better integration of branch and leaf biomass than with discrete-return LiDAR data. Numéro de notice : A2013-053 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/JSTARS.2012.2211863 date de publication en ligne : 27/09/2012 En ligne : http://doi.org/10.1109/JSTARS.2012.2211863 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84586 [article]