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Termes IGN > 1-Candidats > semis de points
semis de points
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- Ensemble de points répartis de façon régulière ou quelconque sur une zone géographique donnée. (Glossaire de cartographie / CFC) Ces points peuvent être issus d'images ou de données lidar ...
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A functional regression model for inventories supported by aerial laser scanner data or photogrammetric point clouds / Magnussen, Steen in Remote sensing of environment, vol 184 (October 2016)
[article]
Titre : A functional regression model for inventories supported by aerial laser scanner data or photogrammetric point clouds Type de document : Article/Communication Auteurs : Magnussen, Steen, Auteur ; Erik Naesset, Auteur ; Gerald Kändler, Auteur ; P. Adler, Auteur ; Jean-Pierre Renaud , Auteur ; Terje Gobakken, Auteur Année de publication : 2016 Article en page(s) : pp 496 - 505 Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes IGN] Allemagne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] inférence
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modèle de régression
[Termes IGN] Norvège
[Termes IGN] restitution
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Forest inventories, with a probability sampling of a target variable Y and a potentially very large number of auxiliary variables (X) obtained from an aerial laser scanner or photogrammetry, are faced with the issue of model and variable selection when a model for linking Y to X is formulated. To bypass this step we propose a generic functional regression model (FRM) for use in both a design- and a model-based framework of inference. We demonstrate applications of FRM with inventory data from France, Germany, and Norway. The generic FRM achieved results that were comparable to those obtained with more traditional approaches based on model and variable selections. The proposed FRM generates interpretable regression coefficients and enables testing of practically relevant hypotheses regarding estimated models. Numéro de notice : A2016-706 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.07.035 En ligne : http://dx.doi.org/10.1016/j.rse.2016.07.035 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82077
in Remote sensing of environment > vol 184 (October 2016) . - pp 496 - 505[article]Interurban visibility diagnosis from point clouds / Oscar Iglesias in European journal of remote sensing, vol 49 n° 1 (2016)
[article]
Titre : Interurban visibility diagnosis from point clouds Type de document : Article/Communication Auteurs : Oscar Iglesias, Auteur ; Lucia Diaz-Vilarino, Auteur ; Higinio González-Jorge, Auteur ; Henrique Lorenzo, Auteur Année de publication : 2016 Article en page(s) : pp 673 - 690 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] sécurité routière
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] télémétrie laser terrestre
[Termes IGN] visibilitéRésumé : (auteur) We present an approach for automatic visibility analysis in interurban roads from point clouds. The methodology is based on a ray-tracing algorithm followed by an occlusion detection to identify potential obstacles between the driver and the theoretical position of pedestrians and cyclists. As a result, the area of visibility from each driver position is obtained. The method compares the performance and suitability of point clouds acquired from both Airborne and Mobile Laser Scanning. The methodology is tested in six real case studies. In most cases, results obtained from MLS are more accurate since the point clouds are acquired from a perspective similar to driver and they have higher resolution. Numéro de notice : A2016-828 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164935 En ligne : http://dx.doi.org/10.5721/EuJRS20164935 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82708
in European journal of remote sensing > vol 49 n° 1 (2016) . - pp 673 - 690[article]A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data / Hamid Hamraz in International journal of applied Earth observation and geoinformation, vol 52 (October 2016)
[article]
Titre : A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data Type de document : Article/Communication Auteurs : Hamid Hamraz, Auteur ; Marco A. Contreras, Auteur ; Jun Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 532 - 541 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuillu
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Kentucky (Etats-Unis)
[Termes IGN] pente
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) This paper presents a non-parametric approach for segmenting trees from airborne LiDAR data in deciduous forests. Based on the LiDAR point cloud, the approach collects crown information such as steepness and height on-the-fly to delineate crown boundaries, and most importantly, does not require a priori assumptions of crown shape and size. The approach segments trees iteratively starting from the tallest within a given area to the smallest until all trees have been segmented. To evaluate its performance, the approach was applied to the University of Kentucky Robinson Forest, a deciduous closed-canopy forest with complex terrain and vegetation conditions. The approach identified 94% of dominant and co-dominant trees with a false detection rate of 13%. About 62% of intermediate, overtopped, and dead trees were also detected with a false detection rate of 15%. The overall segmentation accuracy was 77%. Correlations of the segmentation scores of the proposed approach with local terrain and stand metrics was not significant, which is likely an indication of the robustness of the approach as results are not sensitive to the differences in terrain and stand structures. Numéro de notice : A2016-705 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2016.07.006 En ligne : http://dx.doi.org/10.1016/j.jag.2016.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82075
in International journal of applied Earth observation and geoinformation > vol 52 (October 2016) . - pp 532 - 541[article]The D-FCM partitioned D-BSP tree for massive point cloud data access and rendering / Yi Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 120 (october 2016)
[article]
Titre : The D-FCM partitioned D-BSP tree for massive point cloud data access and rendering Type de document : Article/Communication Auteurs : Yi Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 25 - 36 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse en composantes principales
[Termes IGN] arbre BSP
[Termes IGN] classification floue
[Termes IGN] densité des points
[Termes IGN] semis de points
[Termes IGN] traitement de semis de points
[Termes IGN] valeur propreRésumé : (Auteur) The spatial partitioning of massive point cloud data involves dividing the space into a multi-tree structure step by step, so as to achieve the purpose of fast access and to render the point cloud. The current methods are based on spatial regularity and equal division, which is not consistent with the irregular and non-uniform distribution of most point clouds. This paper presents a directional fuzzy c-means (D-FCM) method for irregular spatial partitioning. The distance metric is weighted by a direction coefficient, which is determined by the eigenvalue of the point cloud. The orientation of each node is adaptively calculated by principal component analysis of the point cloud, and Karhunen-Loeve (KL) transform is applied to the points coordinates in node. A binary space partitioning (BSP) tree structure is used to partition the point cloud data node by node, and a directional BSP (D-BSP) tree is formed. The D-BSP tree structure was tested with point clouds of 0.1 million to over 2 billion points (up to 60 GB). The experimental results showed that the D-BSP tree can ensure that the bounding boxes are close to the actual spatial distribution of the point cloud, it can completely expand along the spatial configuration of the point cloud without generating unnecessary partitioning, and it can achieve a higher rendering speed with less memory requirement. Numéro de notice : A2016-795 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.08.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.08.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82529
in ISPRS Journal of photogrammetry and remote sensing > vol 120 (october 2016) . - pp 25 - 36[article]Lidar detection of individual tree size in tropical forests / António Ferraz in Remote sensing of environment, vol 183 (15 September 2016)
[article]
Titre : Lidar detection of individual tree size in tropical forests Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet , Auteur ; Victoria Meyer, Auteur Année de publication : 2016 Projets : 1-Pas de projet / Article en page(s) : pp 318 - 333 Note générale : Bibliographie
António Ferraz's research was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, administrated by Oak Ridge Associated Universities under contract with NASA(grant number NNH15CO48B).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] arbre (flore)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Panama
[Termes IGN] semis de points
[Termes IGN] télédétection aérienneRésumé : (Auteur) Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1ha, 2.25 ha, 4ha, and 6.25 ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from16.9% at 1ha for the worst model to 5.0% at 6.25ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~4 ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies. Numéro de notice : A2016--103 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.05.028 Date de publication en ligne : 21/06/2016 En ligne : http://doi.org/10.1016/j.rse.2016.05.028 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84669
in Remote sensing of environment > vol 183 (15 September 2016) . - pp 318 - 333[article]Dynamic occlusion detection and inpainting of in situ captured terrestrial laser scanning point clouds sequence / Chi Chen in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkEfficient terrestrial laser scan segmentation exploiting data structure / Hamid Mahmoudabadi in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkIdentification of stable areas in unreferenced laser scans for deformation measurement / Daniel Wujanz in Photogrammetric record, vol 31 n° 155 (September - November 2016)PermalinkInternational benchmarking of the individual tree detection methods for modeling 3-D canopy structure for silviculture and forest ecology using airborne laser scanning / Yunsheng Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkSlicing method for curved façade and window extraction from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)Permalink3D building reconstruction from ALS data using unambiguous decomposition into elementary structures / Malgorzata Jarząbek-Rychard in ISPRS Journal of photogrammetry and remote sensing, vol 118 (August 2016)PermalinkAirborne lidar estimation of aboveground forest biomass in the absence of field inventory / António Ferraz in Remote sensing, vol 8 n° 8 (August 2016)PermalinkA local structure and direction-aware optimization approach for three-dimensional tree modeling / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkClassifying buildings from point clouds and images / Evangelos Maltezos in GIM international [en ligne], vol 30 n° 7 (July 2016)PermalinkA hierarchical approach to three-dimensional segmentation of LiDAR data at single-tree level in a multilayered forest / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)Permalink