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Reconstruction en 3D des bâtiments à partir des données Lidar / M. A. Missomi in Géomatique expert, n° 112 (septembre - octobre 2016)
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Titre : Reconstruction en 3D des bâtiments à partir des données Lidar Type de document : Article/Communication Auteurs : M. A. Missomi, Auteur ; D. Yousfi, Auteur Année de publication : 2016 Article en page(s) : pp 28 - 33 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] acquisition de données
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] outil d'aide à la décision
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] segmentation d'imageRésumé : (auteur) [introduction] L'utilisation des mesures effectuées avec des laser aéroportés basés sur le principe de la technologie Lidar (LIght Detection and Ranging) présente un énorme potentiel pour la cartographie 3D à grande échelle. La précision spatiale et le niveau de détail de l'information des données lidar permettent non seulement d'extraire des informations spatiales détaillées sur les objets urbains mais aussi de les reconstituer en trois dimensions. L'utilisation relativement récente de cette technologie en milieu urbain apporte des solutions inédites et efficaces pour étudier de nombreux aspects de l'environnement urbain sous différents angles. Numéro de notice : A2016-762 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82361
in Géomatique expert > n° 112 (septembre - octobre 2016) . - pp 28 - 33[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 265-2016051 RAB Revue Centre de documentation En réserve L003 Disponible IFN-001-P001888 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt Slicing 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)
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Titre : Slicing method for curved façade and window extraction from point clouds Type de document : Article/Communication Auteurs : S.M. Iman Zolanvari, Auteur ; Debra F. Laefer, Auteur Année de publication : 2016 Article en page(s) : pp 334 - 346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse structurale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] façade
[Termes IGN] fenêtre (bâtiment)
[Termes IGN] modèle numérique
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de points
[Termes IGN] surveillance d'ouvrage
[Termes IGN] traitement de semis de pointsRésumé : (Auteur) Laser scanning technology is a fast and reliable method to survey structures. However, the automatic conversion of such data into solid models for computation remains a major challenge, especially where non-rectilinear features are present. Since, openings and the overall dimensions of the buildings are the most critical elements in computational models for structural analysis, this article introduces the Slicing Method as a new, computationally-efficient method for extracting overall façade and window boundary points for reconstructing a façade into a geometry compatible for computational modelling. After finding a principal plane, the technique slices a façade into limited portions, with each slice representing a unique, imaginary section passing through a building. This is done along a façade’s principal axes to segregate window and door openings from structural portions of the load-bearing masonry walls. The method detects each opening area’s boundaries, as well as the overall boundary of the façade, in part, by using a one-dimensional projection to accelerate processing. Slices were optimised as 14.3 slices per vertical metre of building and 25 slices per horizontal metre of building, irrespective of building configuration or complexity. The proposed procedure was validated by its application to three highly decorative, historic brick buildings. Accuracy in excess of 93% was achieved with no manual intervention on highly complex buildings and nearly 100% on simple ones. Furthermore, computational times were less than 3 sec for data sets up to 2.6 million points, while similar existing approaches required more than 16 hr for such datasets. Numéro de notice : A2016-787 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.06.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.06.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82502
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 334 - 346[article]A 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)
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Titre : A local structure and direction-aware optimization approach for three-dimensional tree modeling Type de document : Article/Communication Auteurs : Zhen Wang, Auteur ; Liqiang Zhang, Auteur ; Tian Fang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 4749 - 4757 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] optimisation (mathématiques)
[Termes IGN] reconstruction 3D
[Termes IGN] semis de points
[Termes IGN] squelettisationRésumé : (Auteur) Modeling 3-D trees from terrestrial laser scanning (TLS) point clouds remains a challenging task for several well-known reasons, including their complex structure and severe occlusions. In order to accurately reconstruct 3-D tree models from TLS point clouds that typically suffer from significant occlusions, in this paper, a novel local structure and direction-aware approach is presented to successfully complete missing structures of trees. In this method, we first extract the coarse tree skeleton from the input point cloud, and thus, the branch dominant direction and the point density of each branch are obtained. By a skeleton-based Laplacian algorithm, the point cloud is further shrunk into a skeleton point cloud to highlight the branch dominant direction of each branch. For obtaining even more accurate point densities, a dictionary-based algorithm is utilized to learn and reconstruct the local structure. Finally, the branch dominant direction and point density are integrated into an iterative optimization process to recover the missing data. Extensive experimental results have shown that the proposed method is very robust to incomplete data sets, and it is capable of accurately reconstructing 3-D trees, which are partially, or even to a large extent, missing from the input point cloud. Numéro de notice : A2016-890 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2551286 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2551286 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83070
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4749 - 4757[article]Unsupervised classification of airborne laser scanning data to locate potential wildlife habitats for forest management planning / Jari Vauhkonen in Forestry, an international journal of forest research, vol 89 n° 4 (August 2016)
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Titre : Unsupervised classification of airborne laser scanning data to locate potential wildlife habitats for forest management planning Type de document : Article/Communication Auteurs : Jari Vauhkonen, Auteur ; Joni Imponen, Auteur Année de publication : 2016 Article en page(s) : pp 350 - 363 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Aves
[Termes IGN] biodiversité végétale
[Termes IGN] classification non dirigée
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] exploration de données géographiques
[Termes IGN] gestion de la vie sauvage
[Termes IGN] gestion forestière durable
[Termes IGN] habitat d'espèce
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) To account for ecological objectives in forest management planning, potential habitats need to be mapped, characterized and evaluated for utility in alternative management practices. Airborne laser scanning (ALS) is increasingly used to derive predictive maps of habitat quality. Unlike ecologically driven approaches that require spatially and temporally co-located training data of the specific species, we tested whether indicative information on the habitat potential could be obtained by means of an unsupervised classification of ALS data. Based on a literature review, altogether five ALS features quantifying vegetation height, cover and diversity were expected to capture the essential variation in the habitat requirements of western capercaillie (Tetrao urogallus L.) and hazel grouse (Tetrastes bonasia L.), which are the most important game birds occurring in the studied area. The features were extracted from sparse density, leaf-off ALS data at a resolution of 256 m2 and partitioned using an unsupervised k-means algorithm. By analysing the persistence of the cluster ensemble formed by the partitioning, altogether 158 plots in 16 structural classes were assigned for field measurements to determine which real-world forest phenomena affected the clustering. The clustering was found to stratify the area mainly in terms of size-related attributes such as timber volume and basal area. The understorey, shrub and herb layers had less correspondence with the clustering, indicating that an unsupervised classification is not directly suitable for habitat mapping. The result was improved using empirical threshold values for the ALS features determined according to the plots labelled as the most potential habitats in the field measurements. This semi-supervised classification of the data indicated 4 per cent of the total forest area as suitable for the specific species, which appears a reasonable estimate of the core area of the habitats considered. Overall, the partitioning formed aggregated, stand-like spatial patterns, even though the neighbourhoods of the individual 256 m2 cells were not considered at all. The result could be further refined by spatial optimization to produce indicative maps for forest management planning with ALS as the sole data source. Numéro de notice : A2016--155 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1093/forestry/cpw011 En ligne : https://doi.org/10.1093/forestry/cpw011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85780
in Forestry, an international journal of forest research > vol 89 n° 4 (August 2016) . - pp 350 - 363[article]Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas / Xiaoqian Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)
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Titre : Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas Type de document : Article/Communication Auteurs : Xiaoqian Zhao, Auteur ; Qinghua Guo, Auteur ; Yanjun Su, Auteur ; Baolin Xue, Auteur Année de publication : 2016 Article en page(s) : pp 79 – 91 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] filtrage numérique d'image
[Termes IGN] forêt
[Termes IGN] semence
[Termes IGN] test de performance
[Termes IGN] Triangulated Irregular NetworkRésumé : (auteur) Filtering of light detection and ranging (LiDAR) data into the ground and non-ground points is a fundamental step in processing raw airborne LiDAR data. This paper proposes an improved progressive triangulated irregular network (TIN) densification (IPTD) filtering algorithm that can cope with a variety of forested landscapes, particularly both topographically and environmentally complex regions. The IPTD filtering algorithm consists of three steps: (1) acquiring potential ground seed points using the morphological method; (2) obtaining accurate ground seed points; and (3) building a TIN-based model and iteratively densifying TIN. The IPTD filtering algorithm was tested in 15 forested sites with various terrains (i.e., elevation and slope) and vegetation conditions (i.e., canopy cover and tree height), and was compared with seven other commonly used filtering algorithms (including morphology-based, slope-based, and interpolation-based filtering algorithms). Results show that the IPTD achieves the highest filtering accuracy for nine of the 15 sites. In general, it outperforms the other filtering algorithms, yielding the lowest average total error of 3.15% and the highest average kappa coefficient of 89.53%. Numéro de notice : A2016-582 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.03.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.03.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81723
in ISPRS Journal of photogrammetry and remote sensing > vol 117 (July 2016) . - pp 79 – 91[article]Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland / Eetu Kotivuori in Silva fennica, vol 50 n° 4 (2016)
PermalinkA novel computer-aided tree species identification method based on burst wind segmentation of 3D bark textures / Alice Ahlem Othmani in Machine Vision and Applications, vol 27 n° 5 (July 2016)
PermalinkOpenBIM framework for a collaborative historic preservation system / Shawn E. O'Keeffe in International journal of 3-D information modeling, vol 5 n° 4 (October - December 2016)
PermalinkThe story of DB4GeO – A service-based geo-database architecture to support multi-dimensional data analysis and visualization / Martin Breunig in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)
PermalinkSimultaneous detection and tracking of pedestrian from panoramic laser scanning data / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)
PermalinkContext-dependent detection of non-linearly distributed points for vegetation classification in airborne LiDAR / Denis Horvat in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)
PermalinkEstimations dendrométriques pour l’aménagement forestier à l’aide de LiDAR aéroporté : premier démonstrateur en forêts littorales dunaires / Alain Munoz in Rendez-vous techniques, n° 50 (Hiver 2016)
PermalinkExpérience pratique de la réalisation du projet démonstrateur « LiDAR forestier » / Didier Canteloup in Rendez-vous techniques, n° 50 (Hiver 2016)
PermalinkInformation géographique environnementale et conception d'infrastructure : quel détail pour l'information partagée ? / Charles-Edouard Tolmer in XYZ, n° 147 (juin - août 2016)
PermalinkiTowns, framework web pour la donnée géographique 3D / Vincent Picavet in XYZ, n° 147 (juin - août 2016)
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PermalinkNew 3D Map Solution Covering Norway / Kenneth Øyen-Eriksen in GIM international, vol 30 n° 6 (June 2016)
PermalinkNewly recorded Neolithic earthen long barrows in south-western Poland: unexpected discoveries, expanded perspectives, new interprétations / Agnieszka Przybył in Préhistoires méditerranéennes, n° spécial (2014)
PermalinkUsing classification trees to predict forest structure types from LiDAR data / Chiara Torresan in Annals of forest research, vol 59 n° 2 (July - December 2016)
PermalinkHigh-precision positioning of radar scatterers / Prabu Dheenathayalan in Journal of geodesy, vol 90 n° 5 (May 2016)
PermalinkPermalinkLaser scanning in engineering surveying : methods of measurement and modeling of structures / Grzegorz Lenda in Reports on geodesy and geoinformatics, vol 100 (May 2016)
PermalinkMultisensor and multispectral Lidar characterization and classification of a forest environment / Christopher Hopkinson in Canadian journal of remote sensing, vol 42 n° 5 ([01/05/2016])
PermalinkRobust approximation of the Medial Axis Transform of LiDAR point clouds as a tool for visualisation / Ravi Peters in Computers & geosciences, vol 90 part A (May 2016)
PermalinkTerrestrial laser scanning in forest inventories / Xinlian Liang in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)
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