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A Swedish case study on the prediction of detailed product recovery from individual stem profiles based on airborne laser scanning / Andreas Barth in Annals of Forest Science, vol 72 n° 1 (January 2015)
[article]
Titre : A Swedish case study on the prediction of detailed product recovery from individual stem profiles based on airborne laser scanning Type de document : Article/Communication Auteurs : Andreas Barth, Auteur ; Johan Möller, Auteur ; Lars Wilhelmsson, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 47 - 56 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] gestion prévisionnelle
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Suède
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] troncRésumé : (auteur) Context : Improved and cost-efficient predictions of detailed product recovery from logging operations may increase efficiency and improve value chains based on modern cut-to-length harvesting (CTL).
Aims : The objective of this study was to investigate and evaluate the use of individual tree data estimates from two inventory techniques: (a) established airborne laser scanner inventory (ALS case) and (b) traditional field inventory (BAU case) for predicting product recovery in a Swedish case study.
Methods : Statistics from previous harvester production files within the region were used to generate realistic levels of simulated stem defects. Bucking simulations were performed to optimise log products according to stem profiles, stem defects, and an operational price list expressing the demand of the industry customer. All simulation results at the stand level were compared to operational harvester production data that were used to provide an accurate measure of the ‘true’ product recovery. The total harvested area was 139 ha including 16 forest stands. Seven groups of log products were included in the analysis. The predicted versus real top diameter distributions of sawlogs were evaluated using an error index to express deviations.
Results : At the stand level, the average error index values were 0.15 and 0.18 for the ALS and BAU approaches, respectively. As a consequence of an overall bias of the ALS tree lists the opposite was found at the total wood flow level, with the field-based data yielding a lower error index.
Conclusions : The volume predictions for different log product groups were slightly more accurate in the ALS case than in the BAU case.Numéro de notice : A2015-381 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s13595-014-0400-6 Date de publication en ligne : 13/08/2014 En ligne : https://doi.org/10.1007/s13595-014-0400-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76870
in Annals of Forest Science > vol 72 n° 1 (January 2015) . - pp 47 - 56[article]A three-dimensional model-based approach to the estimation of the tree top height by fusing low-density LiDAR data and very high resolution optical images / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)
[article]
Titre : A three-dimensional model-based approach to the estimation of the tree top height by fusing low-density LiDAR data and very high resolution optical images Type de document : Article/Communication Auteurs : Claudia Paris, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2015 Article en page(s) : pp 467 - 480 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arbre (flore)
[Termes IGN] données lidar
[Termes IGN] fusion d'images
[Termes IGN] hauteur des arbres
[Termes IGN] image optique
[Termes IGN] modélisation 3DRésumé : (Auteur) Light detection and ranging (LiDAR) technology has been extensively used for estimating forest attributes. Although high-spatial-density LiDAR data can be used to accurately derive attributes at single tree level, low-density LiDAR data are usually acquired for reducing the cost. However, a low density strongly affects the estimation accuracy due to the underestimation of the tree top and the possible loss of crowns that are not hit by any LiDAR point. In this paper, we propose a 3-D model-based approach to the estimation of the tree top height based on the fusion between low-density LiDAR data and high-resolution optical images. In the proposed approach, the integration of the two remotely sensed data sources is first exploited to accurately detect and delineate the single tree crowns. Then, the LiDAR vertical measures are associated to those crowns hit by at least one LiDAR point and used together with the radius of the crown and the tree apex location derived from the optical image for reconstructing the tree top height by a properly defined parametric model. For the remaining crowns detected only in the optical image, we reconstruct the tree top height by proposing a k-nearest neighbor trees technique that estimates the height of the missed trees as the average of the k reconstructed height values of the trees having most similar crown properties. The proposed technique has been tested on a coniferous forest located in the Italian Alps. The experimental results confirmed the effectiveness of the proposed method. Numéro de notice : A2015-035 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2324016 En ligne : https://doi.org/10.1109/TGRS.2014.2324016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75117
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 1 (January 2015) . - pp 467 - 480[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015011 RAB Revue Centre de documentation En réserve L003 Disponible Towards an enhanced understanding of airborne LiDAR measurements of forest vegetation / Aarne Hovi (2015)
Titre : Towards an enhanced understanding of airborne LiDAR measurements of forest vegetation Type de document : Thèse/HDR Auteurs : Aarne Hovi, Auteur Editeur : Vantaa [Finlande] : Finnish Society of Forest Science Année de publication : 2015 Collection : Dissertationes forestales, ISSN 1795-7389 num. 200 Format : 21 x 30 cm ISBN/ISSN/EAN : 978-951-651-489-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de sensibilité
[Termes IGN] composition d'un peuplement forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] forme d'onde
[Termes IGN] identification automatique
[Termes IGN] photogrammétrie terrestre
[Termes IGN] signal laserRésumé : (auteur) This thesis presents basic research on how airborne LiDAR measurements of forest vegetation are influenced by the interplay of the geometric-optical properties of vegetation, sensor function and acquisition settings. Within the work, examining the potential of waveform (WF) recording sensors was of particular interest.
Study I focused upon discrete return LiDAR measurements of understory trees. It showed that transmission losses influenced the intensity of observations and echo triggering probabilities, and also skewed the distribution of echoes towards those triggered by highly reflective or dense targets. The intensity data were of low value for species identification, but the abundance of understory trees could be predicted based on echo height distributions.
In study II, a method of close-range terrestrial photogrammetry was developed. Images were shown as being useful for visualizations and even the geometric quality control of LiDAR data. The strength of backscattering was shown to correlate with the projected area extracted from the images.
In study III, a LiDAR simulation model was developed and validated against real measurements. The model was able to be used for sensitivity analyses to illustrate how plant structure or different pulse properties influence the WF data. Both simulated and real data showed that WF data were able to capture small-scale variations in the structural and optical properties of juvenile forest vegetation.
Study IV illustrated the potential of WF data in the species classification of larger trees. The WF features that separated tree species were also dependent on other variables such as tree size and phenology. Inherent between-tree differences in structure were quantified and the effects of pulse density on the features were examined.
Overall, the thesis provides basic findings on how LiDAR pulses interact with forest vegetation, and serves to link theory with real observations. The results contribute to an improved understanding of LiDAR measurements and their limitations, and thus provide support for further improvements in both data interpretation methods and specific sensor design.Numéro de notice : 14979 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : PhD : Forest sciences : University of Helsinki : 2015 En ligne : http://www.metla.fi/dissertationes/df200.htm Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78367 Tropical forest structure characterization using airborne lidar data: an individual tree level approach / António Ferraz (dec 2015)
Titre : Tropical forest structure characterization using airborne lidar data: an individual tree level approach Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet , Auteur ; Victoria Meyer, Auteur Editeur : Washington DC [Maryland - Etats-Unis] : American Geophysical Union AGU Année de publication : dec 2015 Conférence : AGU 2015 Fall Meeting 14/10/2015 18/12/2015 San Francisco Californie - Etats-Unis Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] biomasse aérienne
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] Panama
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (auteur) Fine scale tropical forest structure characterization has been performed by means of field measurements techniques that record both the specie and the diameter at the breast height (dbh) for every tree within a given area. Due to dense and complex vegetation, additional important ecological variables (e.g. the tree height and crown size) are usually not measured because they are hardly recognized from the ground. The poor knowledge on the 3D tropical forest structure has been a major limitation for the understanding of different ecological issues such as the spatial distribution of carbon stocks, regeneration and competition dynamics and light penetration gradient assessments. Airborne laser scanning (ALS) is an active remote sensing technique that provides georeferenced distance measurements between the aircraft and the surface. It provides an unstructured 3D point cloud that is a high-resolution model of the forest. This study presents the first approach for tropical forest characterization at a fine scale using remote sensing data. The multi-modal lidar point cloud is decomposed into 3D clusters that correspond to single trees by means of a technique called Adaptive Mean Shift Segmentation (AMS3D). The ability of the corresponding individual tree metrics (tree height, crown area and crown volume) for the estimation of above ground biomass (agb) over the 50 ha CTFS plot in Barro Colorado Island is here assessed. We conclude that our approach is able to map the agb spatial distribution with an error of nearly 12% (RMSE=28 Mg ha-1) compared with field-based estimates over 1ha plots. Numéro de notice : C2015-033 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://agu.confex.com/agu/fm15/meetingapp.cgi/Paper/75802 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83298 Use of remotely sensed auxiliary data for improving sample-based forest inventories / Svetlana Saarela (2015)
Titre : Use of remotely sensed auxiliary data for improving sample-based forest inventories Type de document : Thèse/HDR Auteurs : Svetlana Saarela, Auteur Editeur : Vantaa [Finlande] : Finnish Society of Forest Science Année de publication : 2015 Collection : Dissertationes forestales, ISSN 1795-7389 num. 201 Format : 21 x 30 cm ISBN/ISSN/EAN : 978-951-6514911-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse multivariée
[Termes IGN] données auxiliaires
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] échantillonnage de données
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] image Landsat
[Termes IGN] inférence statistique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] placette d'échantillonnage
[Termes IGN] tronc
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Over the past decades it has been shown that remotely sensed auxiliary data have a potential to increase the precision of key estimators in sample-based forest surveys. This thesis was motivated by the increasing availability of remotely sensed data, and the objectives were to investigate how this type of auxiliary data can be used for improving both the design and the estimators in sample-based surveys. Two different modes of inference were studied: model-based inference and design-based inference. Empirical data for the studies were acquired from a boreal forest area in the Kuortane region of western Finland. The data comprised a combination of auxiliary information derived from airborne LiDAR and Landsat data, and field sample plot data collected using a modification of the 10th Finnish National Forest Inventory. The studied forest attribute was growing stock volume.
The results of this thesis are important for the development of forest inventories to meet the requirements which stem from an increasing number of international commitments and agreements related to forests.Numéro de notice : 14978 Affiliation des auteurs : non IGN Thématique : FORET Nature : Thèse étrangère Note de thèse : PhD : Forest sciences : University of Helsinki : 2015 En ligne : Over the past decades it has been shown that remotely sensed auxiliary data have [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78366 Visualisation homogène du littoral à partir de données géographiques hétérogènes spatio-temporelles / Antoine Masse (2015)PermalinkEvaluating tree detection and segmentation routines on very high resolution UAV LiDAR data / Luke Wallace in IEEE Transactions on geoscience and remote sensing, vol 52 n° 12 (December 2014)PermalinkModélisation 3D d'arbre pour comprendre le climat urbain : un projet multidisciplinaire ambitieux / Tania Landes in XYZ, n° 141 (décembre 2014 - février 2015)PermalinkNoisy data smoothing in DEM construction using least squares support vector machines / C. Chen in Transactions in GIS, vol 18 n° 6 (December 2014)PermalinkPerceptually shaded slope maps for the visualization of digital surface models / Thomas J. Pingel in Cartographica, vol 49 n° 4 (Winter 2014)PermalinkPTrees: A point-based approach to forest tree extraction from lidar data / Cédric Vega in International journal of applied Earth observation and geoinformation, vol 33 (December 2014)PermalinkSegmentation semi-automatique pour le traitement de données 3D denses : application au patrimoine architectural / Florent Poux in XYZ, n° 141 (décembre 2014 - février 2015)PermalinkUtilisation des drones pour la surveillance des ouvrages de production d'EDF dans le domaine du génie civil / Rémy Boudon in XYZ, n° 141 (décembre 2014 - février 2015)PermalinkAccuracy test of point-based and object-based urban building feature classification and extraction applying airborne LiDAR data / T. Tang in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)PermalinkAn assessment of the repeatability of automatic forest inventory metrics derived from UAV-borne laser scanning data / Luke Wallace in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)Permalink