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Toward the development of total volume and biomass functions using terrestrial lidar and NFI data / Cédric Vega (2019)
Titre : Toward the development of total volume and biomass functions using terrestrial lidar and NFI data Type de document : Article/Communication Auteurs : Cédric Vega , Auteur ; Jan Hackenberg , Auteur ; Lina Jarboui , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2019 Conférence : Conference 2019, A century of national forest inventories – informing past, present and future decisions 19/05/2019 21/05/2019 Oslo Norvège programme sans actes Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière
[Termes IGN] données lidar
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestier
Résumé : (auteur) Introduction : The diversification of wood usages and the information needs for international reporting require detailed information on total tree volume and biomass. National Forest Inventories have traditionally estimated merchantable volume based on diameter and height measures and allometric models, but they need to get new efficient ways to estimate of total tree volume and biomass (Vallet et al. 2006). In France, current approaches suffer from databases restricted to a limited number of species or tree size range (Henry et al. 2010), and their long term validity could be limited by the impact of climate change on tree growth (Charru et al. 2017). Terrestrial Laser Scanning (TLS) is seen as a promising tool to model tree geometry and estimate total tree volume and biomass without- or limited - destructive measurements. Various approaches have been proposed in the litterature to extract tree attributes, from single measurements (i.e. dbh) to full tree reconstruction (Liang et al. 2018). The latter were initially developed for tree-level processing and relied on of very high density points clouds. Such point clouds were found suitable to estimate total tree volume and biomass. The challenge for NFIs is to acquire and process TLS data acquired over a large number of forest plots at a marginal cost. The purpose of this presentation is to provide experience feedback on the development of such a paradigm in the French NFI.
Materials and methods: The TLS processing chain included both data acquisition protocols and point cloud processing methods. The acquisition part started in 2010 with 4 scan positions per plot, without any additional field measurements. After scanning ~ 1,500 plots, this setup was revised in 2016 to improve the point cloud quality and validation data. The current setup includes 9 scans per plot in a 10 m circle. The traditional volume table protocol is currently applied to obtain additional measurements along the main stem. The point cloud processing chain was implemented under Computree processing platform in the framework of the H2020-project DIABOLO, to extract individual tree geometry and volume. It is based on the SimpleTree approach (Hackenberg et al. 2015), and includes the following main steps: terrain modelling, tree localisation and segmentation, tree reconstruction and consolidation, and volume computation. It was tested on both NFI (25 plots) data and detailed databases based on destructive sample from various sources (Lin2Value, Emerge projects, 76 trees).
Results: The developed method allowed to estimate total tree volume with a mean error of -0.1 m3(±0.4 SD) and a RMSE of 23.47%. In terms of NFI measurements, the DBH and Diameter at 2.6 m were estimated with a precision of 0.24 cm (±0.4 SD) or 0.27 cm (± 1.95 SD) and RMSE of respectively 5.82 % and 8.93 %. As regards cut height and total tree heights, errors were 0.78 m (± 2.5 SD) and 1.48 m (± 1.93 SD). The corresponding RMSE were 27.91 % and 13.84 % respectively(Hackenberg et al. 2017).
Conclusion: The current TLS data acquisition and processing chain provides promising results towardthe development of total volume and biomass functions for NFIs. Future work will focus on improving the field validation protocols and the reconstruction method of the upper canopy, where the point density is limited due to distance and occlusions.
Numéro de notice : C2019-061 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink :
c2019-071-towards an improved forest inventory _JarbouiAdobe Acrobat PDF
Towards an improved forest inventory using terrestrial laser scanning / Lina Jarboui (2019)
Titre : Towards an improved forest inventory using terrestrial laser scanning Type de document : Article/Communication Auteurs : Lina Jarboui , Auteur ; Cédric Vega , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2019 Conférence : Conference 2019 Terrestrial laser scanning in forest ecology : Expanding the Horizon 01/05/2019 01/05/2019 Gent Belgique programme sans actes Langues : Anglais (eng) Descripteur : [Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lasergrammétrie
[Termes IGN] télémétrie laser terrestre
[Vedettes matières IGN] Inventaire forestier
Résumé : (auteur) International reporting and societal demand require information on total wood volume and biomass. National Forest Inventories collect most of the time information on the main stem. Volume and biomass equations exist to estimate totals from the stem. However, they are most often based on small databases that do not represent all the forest conditions. Acquiring total volume and biomass data require costly and time consuming destructive measurements that are not suited to NFI protocols. Terrestrial Lidar data allow to generate very detailed and accurate information on the plot structure. The geometric reconstruction of tree point cloud provides the necessary information to produce innovative total volume and biomass functions. French NFI developed acquisition and processing protocols to satisfy these objectives. Numéro de notice : C2019-071 Affiliation des auteurs : LIF (2012-2019) Thématique : FORET Nature : Poster nature-HAL : Poster-avec-CL DOI : sans Permalink :
Towards an improved forest inventory using TLS - posterAdobe Acrobat PDF