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Auteur Cédric Vega
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Research Director at LIF (Laboratoire d'Inventaire Forestier) since 2014
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RegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science, vol 76 n° 2 (June 2019)
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Titre : RegisTree: a registration algorithm to enhance forest inventory plot georeferencing Type de document : Article/Communication Auteurs : Maryem Fadili , Auteur ; Jean-Pierre Renaud , Auteur ; Jérôme Bock, Auteur ; Cédric Vega , Auteur Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] placette d'échantillonnage
[Termes IGN] superposition de donnéesRésumé : (auteur) Key message : The accuracy of remote sensing-based models of forest attributes could be improved by controlling the spatial registration of field and remote sensing data. We have demonstrated the potential of an algorithm matching plot-level field tree positions with lidar canopy height models and derived local maxima to achieve a precise registration automatically.
Context : The accuracy of remote sensing-based estimates of forest parameters depends on the quality of the spatial registration of the training data.
Aims : This study introduces an algorithm called RegisTree to correct field plot positions by matching a spatialized field tree height map with lidar canopy height models (CHMs).
Methods : RegisTree is based on a point (field positions) to surface (CHM) adjustment approach modified to ensure that at least one field tree position corresponds to CHM local maxima.
Results : RegisTree has been validated with respect to positioning errors and the performance of lidar-derived estimation of plot volume. Overall, RegisTree enabled to register field plots surveyed in a range of forest conditions with a precision of 1.5 m (± 1.23 m), but a higher performance for conifer plots, and a limited efficiency in homogeneous stands, having similar heights. Improved plot positions were found to have a limited impact on volume predictions under the range of tested conditions, with a gain up to 1.3%.
Conclusion : RegisTree could be used to improve the forest plot position from field surveys collected with low-grade GPS and to contribute to the development of processing chains of 3D remote sensing-based models of forest parameters.Numéro de notice : A2019-339 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0814-2 Date de publication en ligne : 02/04/2019 En ligne : http://dx.doi.org/10.1007/s13595-019-0814-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93373
in Annals of Forest Science > vol 76 n° 2 (June 2019) . - n° 30[article]Bridging the gap: toward a French MS-NFI for territories / Jean-Pierre Renaud (2019)
Titre : Bridging the gap: toward a French MS-NFI for territories Type de document : Article/Communication Auteurs : Jean-Pierre Renaud , Auteur ; Dinesh Babu Irulappa-Pillai-Vijayakumar , Auteur ; François Morneau , Auteur ; Cédric Vega , Auteur Editeur : Paris [France] : Office national des forêts ONF 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] carte forestière
[Termes IGN] classification barycentrique
[Termes IGN] densité de la végétation
[Termes IGN] données auxiliaires
[Termes IGN] données de terrain
[Termes IGN] feuillu
[Termes IGN] forêt tempérée
[Termes IGN] image aérienne
[Termes IGN] image Landsat
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] placette d'échantillonnage
[Termes IGN] surface terrière
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Introduction: National forest inventories are designed to produce statistics about forest attributes at a national to regional scales. Beyond these administrative units, the amount of points become limiting in terms of precision. In France, the establishment of regional programs for forest and wood (PRFB) require estimates at a smaller scale. The multisource inventory approaches allowed to bridge this gap (Tomppo et al. 2008). The methods rely on the combination of field plot information with auxiliary data (Kangas et al. 2018). The objective was to set up a multisource inventory workflow for the French Forest and to evaluate the gain in precision obtain at different administrative levels. Materials and methods: This research was conducted over a 7500 km2 area located in centre of France, of which 50 % is covered by forests dominated by broadleaved species. The forest area included 775 NFI plots collected during the 2009-2014 period. The auxiliary data were acquired in 2013-2014 and selected to fulfil the following criteria: Relevant, i.e. well correlated with the forest attributed under survey; Actualized Regularly for updating; Exhaustive over the whole territory; and Economical (RARE2). In this regard, we used the following data sources: Landsat images, 3D models derived from aerial photographs and a forest thematic map. We further evaluated the contribution of 3D models acquired 5 years apart in a subset area. The multisource approach relies on the non-parametric k-nearest neighbours (k-nn) approach owing to its multivariate capabilities. The k-nn was optimised for variable selection, number of neighbours (k) and distance metrics. Its performance was tested under a model-assisted framework using estimators from Mandallaz (2013) for various administrative levels. Results: Among the auxiliary variables tested, the 3D data source from aerial photographs performed best, as compared to Landsat, or forest thematic maps. The best combination of data included all sources and provide relative efficiencies (RE) varying from 2.05 for volume to 1.03 for stand density. Over the subset area, the diachronic data allow to improve the RE from 3-26 %. The diachronic data markedly improved the efficiency in estimations of forest type volumes, basal area and stand density. Similar RE were obtained for small area estimation at the scale of Canton and Municipalities. Conclusion: Our results confirmed the importance of 3D models of forest canopies and demonstrated the interest of canopy changes to improve precision of some forest attributes such as production volume and density, which are associated with fluxes. Numéro de notice : C2019-064 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96975 DIABOLO policy brief. Responding to European, national and regional challenges with harmonised forest information / Tuula Packalen (2019)
Titre : DIABOLO policy brief. Responding to European, national and regional challenges with harmonised forest information Type de document : Ouvrage divers Auteurs : Tuula Packalen, Auteur ; Markus Lier, Auteur ; Kari T. Korhonen, Auteur ; Anu Ruusila, Auteur ; Torgny Lind, Auteur ; Laurent Saint André, Auteur ; Cédric Vega , Auteur ; Jean-Christophe Hervé (1961-2017) , Auteur ; Iciar A. Alberdi, Auteur ; Matthias Dees, Auteur ; Pawan Datta, Auteur ; Charles Harper, Auteur ; Alexandra Freudenschuss, Auteur ; Klemens Schadauer, Auteur Editeur : Natural Resources Institute Finland Luke Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Importance : 8 p. Format : 21 x 30 cm Langues : Anglais (eng) Résumé : (documentaire) Cette plaquette de 8 pages présente le projet DIABOLO, Distributed integrated and harmonised forest information for bioeconomy outlooks, ses enjeux et ses "Work package". Numéro de notice : 17553 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Plaquette / brochure DOI : sans En ligne : http://urn.fi/URN:NBN:fi-fe201902215830 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93459 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 forestierRésumé : (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 : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96978 Documents numériques
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c2019-071-towards an improved forest inventory _JarbouiAdobe Acrobat PDF
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 forestierRésumé : (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 : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97420 Documents numériques
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Towards an improved forest inventory using TLS - posterAdobe Acrobat PDF Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF / Jules Morel in Computers and graphics, vol 74 (August 2018)PermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkMéthodes d'inventaire multisource : améliorer la précision des estimations de l'IFN et atteindre l'échelle des territoires [diaporama] / Cédric Vega (2018)PermalinkStand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science, vol 74 n° 4 (December 2017)PermalinkTerrain model reconstruction from terrestrial LiDAR data using radial basis functions / Jules Morel in IEEE Computer graphics and applications, vol 37 n° 5 ([01/09/2017])PermalinkPreface for the SilviLaser 2015 special section / Sylvie Durrieu in Remote sensing of environment, vol 194 (June 2017)PermalinkEvaluation des ressources forestières pour la bioéconomie : quels nouveaux besoins et comment y répondre ? / Jean-Christophe Hervé in Innovations Agronomiques, vol 56 (Mars 2017)PermalinkMatching plot-level tree maps with 3D remote sensing data for assessing and estimating forest parameters / Cédric Vega (2017)PermalinkPermalinkOn the interest of penetration depth, canopy area and volume metrics to improve Lidar-based models of forest parameters / Cédric Vega in Remote sensing of environment, vol 175 (15 March 2016)Permalink