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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 Integrating urban and national forest inventory data in support of rural–urban assessments / James A. Westfall in Forestry, an international journal of forest research, vol 91 n° 5 (December 2018)
[article]
Titre : Integrating urban and national forest inventory data in support of rural–urban assessments Type de document : Article/Communication Auteurs : James A. Westfall, Auteur ; Paul L. Patterson, Auteur ; Christopher B. Edgar, Auteur Année de publication : 2018 Article en page(s) : pp 641 - 649 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] agrégation de données
[Termes IGN] Austin (Texas)
[Termes IGN] intégration de données
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] inventaire forestier local
[Termes IGN] Texas (Etats-Unis)
[Termes IGN] variance
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Due to the interest in status and trends in forest resources, many countries conduct a national forest inventory (NFI). To better understand the characteristics of woody vegetation in areas that are typically not forested, there is an increasing emphasis on urban inventory efforts where all trees both within and outside forest areas are measured. Often, these two inventories are entirely independent endeavours from data collection through analytical reporting. To holistically explore landscape-scale phenomena across the rural–urban gradient, there is a need to combine information from both sources. In this paper, methods for combining these two data sources are examined using data from an urban inventory conducted in Austin, Texas, USA, and NFI data collected in the same and surrounding areas. Approaches to aggregating areas based on sampling intensity and plot design combinations are of considerable importance for the validity of the estimation. An additional complexity can also arise due to temporal discrepancies between the two data sources. Thus, it is imperative to accurately identify all the existing sampling intensity/plot design combinations within the population of interest. Once this difficulty is surmounted, there still exist aggregation methods that will produce erroneous results. Statistically valid variance estimation arises from maintaining independence of the two samples. This approach satisfies both the proportional allocation among strata requirement as well as the necessary partitioning of the two plot designs. Difficulty in interpretation of results can also be encountered due to differences in measurement protocols across aggregated areas. Thus, analysts should have an in-depth understanding of data sources and the differences between them to avoid unintended errors. The need for rural–urban assessments are expected to increase dramatically as urban areas expand and issues such as land conversion, wildland fire and invasive species spread become of further importance. Numéro de notice : A2018-638 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpy023 Date de publication en ligne : 20/07/2018 En ligne : https://doi.org/10.1093/forestry/cpy023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93247
in Forestry, an international journal of forest research > vol 91 n° 5 (December 2018) . - pp 641 - 649[article]International benchmarking of terrestrial laser scanning approaches for forest inventories / Xinlian Liang in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)
[article]
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 , Auteur 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]Réservation
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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 Predicting tree diameter distributions from airborne laser scanning, SPOT 5 satellite, and field sample data in the perm region, Russia / Jussi Peuhkurinen in Forests, vol 9 n° 10 (October 2018)
[article]
Titre : Predicting tree diameter distributions from airborne laser scanning, SPOT 5 satellite, and field sample data in the perm region, Russia Type de document : Article/Communication Auteurs : Jussi Peuhkurinen, Auteur ; Timo Tokola, Auteur ; Kseniia Plevak, Auteur ; Sanna Sirparanta, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies sibirica
[Termes IGN] Alnus incana
[Termes IGN] Betula pendula
[Termes IGN] classification barycentrique
[Termes IGN] diamètre des arbres
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image SPOT 5
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Picea abies
[Termes IGN] Pinus sibirica
[Termes IGN] Pinus sylvestris
[Termes IGN] placette d'échantillonnage
[Termes IGN] Populus tremula
[Termes IGN] Russie
[Termes IGN] Salix caprea
[Termes IGN] Tilia cordata
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) A tree list is a list of trees in the area of interest containing, for example, the species, diameter, height, and stem volume of each tree. Tree lists can be used to derive various characteristics of the growing stock, and are therefore versatile and informative sources of data for several forest management purposes. Especially in heterogonous and unmanaged forest structures with multiple species, tree list estimates imputed from local reference field data can provide an alternative to mean value estimates of growing stock (e.g., basal area, total stem volume, mean tree diameter, mean tree height, and number of trees). In this study, reference field plots, airborne laser scanning (ALS) data, and SPOT 5 satellite (Satellite Pour l’Observation de la Terre) imagery were used for tree list imputation applying the k most similar neighbors (k-MSN) estimation method in the West Ural taiga region of the Russian Federation for diameter distribution estimation. In k-MSN, weighted average of k field reference plots with highest similarity between field reference plot and target (forest grid cell, or field plot) based on ALS and SPOT 5 features were used to predict the mean values of growing stock and tree lists for the target object simultaneously. Diameter distributions were then constructed from the predicted tree lists. The prediction of mean values and diameter distributions was tested in 18 independent validation plots of 0.25–0.5 ha in size, whose species specific diameter distributions were measured in the field and grouped into three functional groups (Pines, Spruce/Fir, Broadleaf Group), each containing several species. In terms of root mean squared error relative to mean of validation plots, the accuracy of estimation was 0.14 and 0.17 for basal area and total stem volume, respectively. Reynolds error index values and visual inspection showed encouraging results in evaluating the goodness-of-fit statistics of the estimated diameter distributions. Although estimation accuracy was worse for functional group mean values and diameter distributions, the results indicate that it is possible to predict diameter distributions in forests of the test area with the tested methodology and materials. Numéro de notice : A2018-476 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f9100639 Date de publication en ligne : 13/10/2018 En ligne : https://doi.org/10.3390/f9100639 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91176
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