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A new small area estimation algorithm to balance between statistical precision and scale / Cédric Vega in International journal of applied Earth observation and geoinformation, vol 97 (May 2021)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 97 (May 2021) . - n° 102303 Titre : A new small area estimation algorithm to balance between statistical precision and scale Type de document : Article/Communication Auteurs : Cédric Vega , Auteur ; Jean-Pierre Renaud, Auteur ; Ankit Sagar , Auteur ; Olivier Bouriaud , Auteur Année de publication : 2021 Projets : LUE / Université de Lorraine, DIABOLO / Packalen, Tuula, ARBRE/CHM-era / Jolly, Anne Article en page(s) : n° 102303 Note générale : bibliographie This research was funded by The French Environmental Management Agency (ADEME), grant number 16-60-C0007. The methods and algorithms for processing photogrammetric data were supported by DIABOLO project from the European Union’s Horizon 2020 research and innovation program under grant agreement No 633464, as well as CHM-ERA project from the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). Ankit Sagar received the financial support of the French PIA project “Lorraine Université d’Excellence”, reference ANR-15-IDEX-04-LUE, through the project Impact DeepSurf. Langues : Anglais (eng) Descripteur : [Termes IGN] arbre BSP [Termes IGN] capital sur pied [Termes IGN] données auxiliaires [Termes IGN] données de terrain [Termes IGN] estimation bayesienne [Termes IGN] inventaire forestier national (données France) [Termes IGN] réduction d'échelle [Termes IGN] seuillage [Termes IGN] surface terrière [Vedettes matières IGN] Sylviculture Résumé : (auteur) Combining national forest inventory (NFI) data with auxiliary information allows downscaling and improving the precision of NFI estimates for small domains, where normally too few field plots are available to produce reliable estimates. In most situations, small domains represent administrative units that could greatly vary in size and forested area. In small and poorly sampled domains, the precision of estimates often drop below expected standards. To tackle this issue, we introduce a downscaling algorithm generating the smallest possible groups of domains satisfying prescribed sampling density and estimation error. The binary space partitioning algorithm recursively divides the population of domains in two groups while the prescribed precision conditions are fulfilled. The algorithm was tested on two major forest attributes (i.e. growing stock and basal area) in an area of 7,500 km2 dominated by hardwood forests in the centre of France. The estimation domains consisted in 157 municipalities. The field data included 819 NFI plots surveyed during a 5 years period. The auxiliary data consisted in 48 metrics derived from a forest map, photogrammetric models and Landsat images. A model-assisted framework was used for estimation. For each forest attribute, the best model was selected using a best-subset approach using a Bayesian Information Criteria. The retained models explained 58% and 41% of the observed variance for the growing stocks and basal areas respectively. The performance of the algorithm was evaluated using a minimum of 3 NFI points per domain and estimation errors varying from 10 to 50%. For a target estimation error set to 10%, the algorithm led to a limited number of estimation domains ( The algorithm provides a flexible estimation framework for small area estimation. The key advantages of the approach are relying on its capacity to produce estimations based on a preselected precision threshold and to produce results over the whole area of interest, avoiding areas without any estimates. The algorithm could also be used on any kind of polygon layers (not only administrative ones), provided that the field sampling design enable estimation. This makes the proposed algorithm a convenient tool notably for decision makers and forest managers. Numéro de notice : A2021-067 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2021.102303 date de publication en ligne : 25/01/2021 En ligne : https://doi.org/10.1016/j.jag.2021.102303 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96992 [article]

Increasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators / Dinesh Babu Irulappa Pillai Vijayakumar in Remote sensing, vol 11 n° 8 (August 2019)  

Public [article]  inRemote sensing > vol 11 n° 8 (August 2019) . - n° 991 Titre : Increasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators Type de document : Article/Communication Auteurs : Dinesh Babu Irulappa Pillai Vijayakumar , Auteur ; Jean-Pierre Renaud, Auteur ; François Morneau , Auteur ; Ronald E. McRoberts, Auteur ; Cédric Vega , Auteur Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 991 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre caducifolié [Termes IGN] classification barycentrique [Termes IGN] feuillu [Termes IGN] image Landsat-8 [Termes IGN] inférence statistique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier national (données France) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] Orléans, forêt d' (Loiret) [Termes IGN] photogrammétrie numérique [Termes IGN] Pinus pinaster [Termes IGN] Pinus sylvestris [Termes IGN] Quercus pedunculata [Termes IGN] Quercus sessiliflora [Termes IGN] Sologne (France) [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Multisource forest inventory methods were developed to improve the precision of national forest inventory estimates. These methods rely on the combination of inventory data and auxiliary information correlated with forest attributes of interest. As these methods have been predominantly tested over coniferous forests, the present study used this approach for heterogeneous and complex deciduous forests in the center of France. The auxiliary data considered included a forest type map, Landsat 8 spectral bands and derived vegetation indexes, and 3D variables derived from photogrammetric canopy height models. On a subset area, changes in canopy height estimated from two successive photogrammetric models were also used. A model-assisted inference framework, using a k nearest-neighbors approach, was used to predict 11 field inventory variables simultaneously. The results showed that among the auxiliary variables tested, 3D metrics improved the precision of dendrometric estimates more than other auxiliary variables. Relative efficiencies (RE) varying from 2.15 for volume to 1.04 for stand density were obtained using all auxiliary variables. Canopy height changes also increased RE from 3% to 26%. Our results confirmed the importance of 3D metrics as auxiliary variables and demonstrated the value of canopy change variables for increasing the precision of estimates of forest structural attributes such as density and quadratic mean diameter. Numéro de notice : A2019-382 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11080991 date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.3390/rs11080991 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93456 [article]

Comparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data / Joris Ravaglia in Forests, vol 10 n° 7 (July 2019)  

Public [article]  inForests > vol 10 n° 7 (July 2019) . - 19 p. Titre : Comparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data Type de document : Article/Communication Auteurs : Joris Ravaglia, Auteur ; Richard A. Fournier, Auteur ; Alexandra Bac, Auteur ; Cédric Vega , Auteur ; Jean-François Côté, Auteur ; Alexandre Piboule, Auteur ; Ulysse Rémillard, Auteur Année de publication : 2019 Projets : ARBRE / AgroParisTech Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] Canada [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] diamètre des arbres [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] feuillu [Termes IGN] France (administrative) [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Pinophyta [Termes IGN] semis de points [Termes IGN] transformation de Hough [Termes IGN] volume en bois Résumé : (auteur) Terrestrial laser scanners provide accurate and detailed point clouds of forest plots, which can be used as an alternative to destructive measurements during forest inventories. Various specialized algorithms have been developed to provide automatic and objective estimates of forest attributes from point clouds. The STEP (Snakes for Tuboid Extraction from Point cloud) algorithm was developed to estimate both stem diameter at breast height and stem diameters along the bole length. Here, we evaluate the accuracy of this algorithm and compare its performance with two other state-of-the-art algorithms that were designed for the same purpose (i.e., the CompuTree and SimpleTree algorithms). We tested each algorithm against point clouds that incorporated various degrees of noise and occlusion. We applied these algorithms to three contrasting test sites: (1) simulated scenes of coniferous stands in Newfoundland (Canada), (2) test sites of deciduous stands in Phalsbourg (France), and (3) coniferous plantations in Quebec, Canada. In most cases, the STEP algorithm predicted diameter at breast height with higher R2 and lower RMSE than the other two algorithms. The STEP algorithm also achieved greater accuracy when estimating stem diameter in occluded and noisy point clouds, with mean errors in the range of 1.1 cm to 2.28 cm. The CompuTree and SimpleTree algorithms respectively produced errors in the range of 2.62 cm to 6.1 cm and 1.03 cm to 3.34 cm, respectively. Unlike CompuTree or SimpleTree, the STEP algorithm was not able to estimate trunk diameter in the uppermost portions of the trees. Our results show that the STEP algorithm is more adapted to extract DBH and stem diameter automatically from occluded and noisy point clouds. Our study also highlights that SimpleTree and CompuTree require data filtering and results corrections. Conversely, none of these procedures were applied for the implementation of the STEP algorithm. Numéro de notice : A2019-337 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f10070599 date de publication en ligne : 18/07/2019 En ligne : https://doi.org/10.3390/f10070599 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93367 [article]

RegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 76 n° 2 (June 2019) . - n° 30 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 données Résumé : (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 [article]

Bridging the gap: toward a French MS-NFI for territories / Jean-Pierre Renaud (2019)

Public 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 forestier Résumé : (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)  

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Toward the development of total volume and biomass functions using terrestrial lidar and NFI data / Cédric Vega (2019)

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Towards an improved forest inventory using terrestrial laser scanning / Lina Jarboui (2019) 

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Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF / Jules Morel in Computers and graphics, vol 74 (August 2018)  

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Un inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa Pillai Vijayakumar (2018) 

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Méthodes d'inventaire multisource : améliorer la précision des estimations de l'IFN et atteindre l'échelle des territoires [diaporama] / Cédric Vega (2018)  

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Stand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science [en ligne], vol 74 n° 4 (December 2017)  

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Terrain 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])  

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Preface for the SilviLaser 2015 special section / Sylvie Durrieu in Remote sensing of environment, vol 194 (June 2017)  

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Evaluation des ressources forestières pour la bioéconomie : quels nouveaux besoins et comment y répondre ? / Jean-Christophe Hervé in Innovations Agronomiques, vol 56 (Mars 2017)    

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