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Auteur Jan Hackenberg
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Affiner la recherche Interroger des sources externesImproving quantitative structure models with an Huxley protocol based filter / Jan Hackenberg in Applied geomatics, vol 15 n° inconnu (2023)
Titre : Improving quantitative structure models with an Huxley protocol based filter Type de document : Article/Communication Auteurs : Jan Hackenberg , Auteur ; Jean-Daniel Bontemps
Année de publication : 2023 Note générale : bibliographie
preprint https://doi.org/10.21203/rs.3.rs-2818844/v1Langues : Anglais (eng) Descripteur : [Termes IGN] données localisées 3D
[Termes IGN] modélisation de la forêt
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Quantitative structure models (QSMs) are topological ordered cylinder models of trees which describe the branching structure up to the tips.
Methods : We present unpublished tree describing parameters which can be derived [rein a single Quantitative Structure Model QSM. The parameters are used to build two Radius correction filters.
Results : For validation we use QSMs produced from an open point cloud data set of tree clouds with the SimpleForest software. We coin-pare the QSM volume against the harvested reference data for 65 felled trees. We also found QSM data of Tree QSM, a competitive and broadly accepted QSM modeling tool. Our RMSE was less than 40 % of the TreeQSM RMSE. For other error measures, the r2adi and the CCC, the relative improvement looked even better with reaching only 27 % and 21 % of the TreeQSM errors respectively.
Conclusions: In forest ecology we should use the here presented pipeline to build accurate CPIs for reasons of: Quality - With the invention of the QSM Radius filter techniques we improve tree volume prediction capabilities utilizing QSMs. Quantity - More data can be collected with QSMs than with traditional methods. Here we use models build on more than ten thousand measurements.Numéro de notice : A2023-178 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET/INFORMATIQUE/MATHEMATIQUE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103320
in Applied geomatics > vol 15 n° inconnu (2023)[article]
Titre : Gaining insight into the allometric scaling of trees by utilizing 3d reconstructed tree models - a SimpleForest study Type de document : Article/Communication Auteurs : Jan Hackenberg Editeur : BioRxiv Année de publication : 2022 Projets : 1-Pas de projet / Importance : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données allométriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle de croissance végétale
[Termes IGN] modélisation de la forêt
[Termes IGN] volume en bois
[Vedettes matières IGN] ForesterieRésumé : (auteur) Forestry utilizes volume predictor functions utilizing as input the diameter at breast height. Some of those functions take the power form Y = a ∗ Xb. In fact this function is fundamental for the biology field of allometric scaling theories founded round about a century ago. The theory describes the relationships between organs/body parts and the complete body of organisms.
With digital methods we can generate 3d forest point clouds non destructively in short time frames. SimpleForest is one free available tool which generates fully automated ground and tree models from high resoluted forest plots. Generated topological ordered cylinder models are called commonly QSMs.
We use SimpleForest QSMs an build a function which estimates the total supported wood volume at any given point of the tree. As input we use the supported soft wood volume for those query points. Instead of measuring directly the soft wood volume we use as a proxy the number of supported twigs. We argue with the pipe model theory for the correctness of the proxy.
We can use the named relationship to also filter our QSMs made of an open data set of tree clouds. The filter corrects overestimated radii. And we compare the corrected QSM volume against the harvested reference data for 66 felled trees. We also found QSM data of TreeQSM, a competitive and broadly accepted QSM modeling tool. Our RMSE was less than 40% of the tree QSM RMSE. And for other error measures, the r2adj. and the CCC, the relative improvement looked even better with 27% and 21% respectively.
We consider this manuscript as highly impactful because of the magnitude of quality improvement we do. The relation between soft volume and total volume distributions seems to be really strong and tree data can easily also be used as example data for the generic field of allometric scaling.Numéro de notice : P2022-008 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET/MATHEMATIQUE Nature : Preprint nature-HAL : Préprint DOI : 10.1101/2022.05.05.490069 Date de publication en ligne : 05/05/2022 En ligne : https://doi.org/10.1101/2022.05.05.490069 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101945 
Titre : Toward the development of total volume and biomass functions using terrestrial lidar and NFI data Type de document : Article/Communication Auteurs : Cédric Vega 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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Titre : International benchmarking of terrestrial laser scanning approaches for forest inventories Type de document : Article/Communication Auteurs : Xinlian Liang, Auteur ; Juha Hyyppä, Auteur ; Harri Kaartinen, Auteur ; Matti Lehtomäki, Auteur ; Jiri Pyorala, Auteur ; Norbert Pfeifer, Auteur ; Markus Holopainen, Auteur ; Gabor Brolly, Auteur ; Francesco Pirotti, Auteur ; Jan Hackenberg Année de publication : 2018 Projets : DIABOLO / Packalen, Tuula Article en page(s) : pp 137 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithmique
[Termes IGN] benchmark spatial
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] état de l'art
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lasergrammétrie
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The last two decades have witnessed increasing awareness of the potential of terrestrial laser scanning (TLS) in forest applications in both public and commercial sectors, along with tremendous research efforts and progress. It is time to inspect the achievements of and the remaining barriers to TLS-based forest investigations, so further research and application are clearly orientated in operational uses of TLS. In such context, the international TLS benchmarking project was launched in 2014 by the European Spatial Data Research Organization and coordinated by the Finnish Geospatial Research Institute. The main objectives of this benchmarking study are to evaluate the potential of applying TLS in characterizing forests, to clarify the strengths and the weaknesses of TLS as a measure of forest digitization, and to reveal the capability of recent algorithms for tree-attribute extraction. The project is designed to benchmark the TLS algorithms by processing identical TLS datasets for a standardized set of forest attribute criteria and by evaluating the results through a common procedure respecting reliable references. Benchmarking results reflect large variances in estimating accuracies, which were unveiled through the 18 compared algorithms and through the evaluation framework, i.e., forest complexity categories, TLS data acquisition approaches, tree attributes and evaluation procedures. The evaluation framework includes three new criteria proposed in this benchmarking and the algorithm performances are investigated through combining two or more criteria (e.g., the accuracy of the individual tree attributes are inspected in conjunction with plot-level completeness) in order to reveal algorithms’ overall performance. The results also reveal some best available forest attribute estimates at this time, which clarify the status quo of TLS-based forest investigations. Some results are well expected, while some are new, e.g., the variances of estimating accuracies between single-/multi-scan, the principle of the algorithm designs and the possibility of a computer outperforming human operation. With single-scan data, i.e., one hemispherical scan per plot, most of the recent algorithms are capable of achieving stem detection with approximately 75% completeness and 90% correctness in the easy forest stands (easy plots: 600 stems/ha, 20 cm mean DBH). The detection rate decreases when the stem density increases and the average DBH decreases, i.e., 60% completeness with 90% correctness (medium plots: 1000 stem/ha, 15 cm mean DBH) and 30% completeness with 90% correctness (difficult plots: 2000 stems/ha, 10 cm mean DBH). The application of the multi-scan approach, i.e., five scans per plot at the center and four quadrant angles, is more effective in complex stands, increasing the completeness to approximately 90% for medium plots and to approximately 70% for difficult plots, with almost 100% correctness. The results of this benchmarking also show that the TLS-based approaches can provide the estimates of the DBH and the stem curve at a 1–2 cm accuracy that are close to what is required in practical applications, e.g., national forest inventories (NFIs). In terms of algorithm development, a high level of automation is a commonly shared standard, but a bottleneck occurs at stem detection and tree height estimation, especially in multilayer and dense forest stands. The greatest challenge is that even with the multi-scan approach, it is still hard to completely and accurately record stems of all trees in a plot due to the occlusion effects of the trees and bushes in forests. Future development must address the redundant yet incomplete point clouds of forest sample plots and recognize trees more accurately and efficiently. It is worth noting that TLS currently provides the best quality terrestrial point clouds in comparison with all other technologies, meaning that all the benchmarks labeled in this paper can also serve as a reference for other terrestrial point clouds sources. Numéro de notice : A2018-400 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.06.021 Date de publication en ligne : 24/07/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.06.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90829
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 137 - 179[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2018101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018103 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018102 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt
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 / Packalen, Tuula 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]
