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Auteur Raphaël Pélissier |
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Affiner la recherche Interroger des sources externesUsing terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach / Stéphane Momo Takoudjou in Methods in ecology and evolution, vol 9 n° 4 (April 2018)
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 Note générale : bibliographie
Funding Information : Global Environment Facility (Grant Number: TF010038), World Bank and French Government scholarshipLangues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Afrique centrale
[Termes descripteurs IGN] AMAPstudio - Scan
[Termes descripteurs IGN] biomasse aérienne
[Termes descripteurs IGN] Cameroun
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] données localisées 3D
[Termes descripteurs IGN] forêt tropicale
[Termes descripteurs IGN] modèle de croissance
[Termes descripteurs IGN] puits de carbone
[Termes descripteurs IGN] volume en bois
[Vedettes matières IGN] Végétation et changement climatiqueMots-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 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)[article]
Titre : Aboveground-biomass estimation of a complex tropical forest in India using Lidar Type de document : Article/Communication Auteurs : Cédric Vega Année de publication : 2015 Article en page(s) : pp 10607 - 10625 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes descripteurs IGN] biomasse aérienne
[Termes descripteurs IGN] canopée
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] données localisées 3D
[Termes descripteurs IGN] forêt tropicale
[Termes descripteurs IGN] Inde
[Termes descripteurs IGN] profil en travers
[Termes descripteurs IGN] semis de points
[Termes descripteurs IGN] structure d'un peuplement forestier
[Termes descripteurs IGN] texture
[Termes descripteurs IGN] volume en boisRésumé : (auteur) Light Detection and Ranging (Lidar) is a state of the art technology to assess forest aboveground biomass (AGB). To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level using point distributional approach (DM), canopy volume profile approach (CVP), 2D canopy grain approach (FOTO), and further evaluated the potential of a topographical complexity index (TCI) to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP) and horizontal (FOTO) structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure. Numéro de notice : A2015--081 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs70810607 date de publication en ligne : 18/08/2015 En ligne : https://doi.org/10.3390/rs70810607 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84559
in Remote sensing > vol 7 n° 8 (August 2015) . - pp 10607 - 10625[article]Documents numériques
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