Détail de l'auteur
Auteur Gilles Le Moguédec |
Documents disponibles écrits par cet auteur (3)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesModeling and propagating inventory-based sampling uncertainty in the large-scale forest demographic model “MARGOT” / Timothée Audinot in Natural Resource Modelling, vol 35 n° 3 (August 2022)
Titre : Modeling and propagating inventory-based sampling uncertainty in the large-scale forest demographic model “MARGOT” Type de document : Article/Communication Auteurs : Timothée Audinot Année de publication : 2022 Projets : ModForTrans / Bontemps, Jean-Daniel, ARBRE / AgroParisTech (2007 -) Article en page(s) : n° e12352 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] incertitude des données
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modélisation de la forêt
[Termes IGN] propagation d'incertitude
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Models based on national forest inventory (NFI) data intend to project forests under management and policy scenarios. This study aimed at quantifying the influence of NFI sampling uncertainty on parameters and simulations of the demographic model MARGOT. Parameter variance–covariance structure was estimated from bootstrap sampling of NFI field plots. Parameter variances and distributions were further modeled to serve as a plug-in option to any inventory-based initial condition. Forty-year time series of observed forest growing stock were compared with model simulations to balance model uncertainty and bias. Variance models showed high accuracies. The Gamma distribution best fitted the distributions of transition, mortality and felling rates, while the Gaussian distribution best fitted tree recruitment fluxes. Simulation uncertainty amounted to 12% of the model bias at the country scale. Parameter covariance structure increased simulation uncertainty by 5.5% in this 12%. This uncertainty appraisal allows targeting model bias as a modeling priority. Numéro de notice : A2022-576 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/nrm.12352 Date de publication en ligne : 08/08/2022 En ligne : https://doi.org/10.1111/nrm.12352 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101333
in Natural Resource Modelling > vol 35 n° 3 (August 2022) . - n° e12352[article]
Titre : Improving the Fagacées growth model with an expanded common beech (Fagus sylvatica L.) data series from France and Germany Type de document : Article/Communication Auteurs : Gilles Le Moguédec, Auteur ; Sidonie Artru, Auteur ; Axel Albrecht, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] allométrie
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt équienne
[Termes IGN] France (administrative)
[Termes IGN] hauteur des arbres
[Termes IGN] jeu de données
[Termes IGN] modèle de croissance végétale
[Termes IGN] modélisation de la forêt
[Termes IGN] Quercus (genre)
[Termes IGN] République fédérale d'Allemagne
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message: The Fagacées growth model was originally designed for application in the Northern half of France. It is a robust model with potential applicability to a larger area, though this potential has not yet been verified. We added new data to the original parameterization data set and our results show that the Fagacées formalism can be generalized.
Context: The Fagacées growth and yield model was designed for the management of pure even-aged stands of European beech and served as a prototype to build models for other tree species.
Aims: The objective of this study was to improve the growth components of the Fagacées model with additional data from North-Western France to South-Western Germany.
Material and methods: Our model was calibrated on several forest inventory data sets. The first one (F) is the original data set that was used to elaborate the equations in the Fagacées model. The second one (F+) is the original data set extended with additional measurements on the same sites and on new sites in Northern France. The third (G) adds complementary data from a forest network in Southwestern Germany. The last one (A) is the aggregate of all these data sets.
Results: Fitting the original model equations on the extended F+ dataset led us to modify the equation for stand basal area increment. This new equation also fit the German dataset well. The other equations could be applied to all datasets, some with the same parameter values and some after recalibrating according to the dataset.
Conclusion: We conclude that the general form of the model’s equations is appropriate for application to other regions, but that a recalibration of the equations is preferable in order to reflect local conditions. The advantage of our approach is that fewer data are required to recalibrate an existing equation than to establish an entirely new one.Numéro de notice : A2021-695 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-021-01086-9 Date de publication en ligne : 20/09/2021 En ligne : https://doi.org/10.1007/s13595-021-01086-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98525
in Annals of Forest Science > vol 78 n° 4 (December 2021) . - n° 84[article]
Titre : Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach Type de document : Article/Communication Auteurs : Stéphane Momo Takoudjou, Auteur ; Pierre Ploton, Auteur ; Bonaventure Sonké, Auteur ; Jan Hackenberg Année de publication : 2018 Projets : 3-projet - voir note / AgroParisTech (2007 -) Article en page(s) : pp 905 - 916 Note générale : bibliographie
Funding Information : Global Environment Facility (Grant Number: TF010038), World Bank and French Government scholarshipLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Afrique centrale
[Termes IGN] biomasse aérienne
[Termes IGN] Cameroun
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] modèle de croissance végétale
[Termes IGN] puits de carbone
[Termes IGN] volume en boisMots-clés libres : Quantitative Structure Model Résumé : (auteur) Calibration of local, regional or global allometric equations to estimate biomass at the tree level constitutes a significant burden on projects aiming at reducing Carbon emissions from forest degradation and deforestation. The objective of this contribution is to assess the precision and accuracy of Terrestrial Laser Scanning (TLS) for estimating volumes and above‐ground biomass (AGB) of the woody parts of tropical trees, and for the calibration of allometric models.
We used a destructive dataset of 61 trees, with diameters and AGB of up to 186.6 cm and 60 Mg respectively, which were scanned, felled and weighed in the semi‐deciduous forests of eastern Cameroon. We present an operational approach based on available software allowing the retrieving of TLS volume with low bias and high accuracy for large tropical trees. Edition of the obtained models proved necessary, mainly to account for the complexity of buttressed parts of tree trunks, which were separately modelled through a meshing approach, and to bring a few corrections in the topology and geometry of branches, thanks to the amapstudio‐scan software.
Over the entire dataset, TLS‐derived volumes proved highly reliable for branches larger than 5 cm in diameter. The volumes of the remaining woody parts estimated for stumps, stems and crowns as well as for the whole tree proved very accurate (RMSE below 2.81% and R² above of .98) and unbiased. Once converted into AGB using mean local‐specific wood density values, TLS estimates allowed calibrating a biomass allometric model with coefficients statistically undistinguishable from those of a model based on destructive data. The Unedited Quantitative Structure Model (QSM) however leads to systematic overestimations of woody volumes and subsequently to significantly different allometric parameters.
We can therefore conclude that a non‐destructive TLS approach can now be used as an operational alternative to traditional destructive sampling to build the allometric equations, although attention must be paid to the quality of QSM model adjustments to avoid systematic bias.Numéro de notice : A2018-205 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.1111/2041-210X.12933 Date de publication en ligne : 07/11/2017 En ligne : https://doi.org/10.1111/2041-210X.12933 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93819
in Methods in ecology and evolution > vol 9 n° 4 (April 2018) . - pp 905 - 916[article]
