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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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Aerial lidar point cloud voxelization with its 3D ground filtering application / Liying Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 2 (February 2017)
[article]
Titre : Aerial lidar point cloud voxelization with its 3D ground filtering application Type de document : Article/Communication Auteurs : Liying Wang, Auteur ; Yan Xu, Auteur ; Yu Li, Auteur Année de publication : 2017 Article en page(s) : pp 95 - 107 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] adjacence
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] modèle conceptuel de données
[Termes IGN] semis de points
[Termes IGN] visualisation 3D
[Termes IGN] voxelRésumé : (Auteur) Compared to raster grid, Triangulated Irregular Network (TIN), and point cloud, the benefit of voxel representation lies in that the implicit notion of adjacency and the true 3D representation can be presented simultaneously. A binary voxel-based data (BVD) model is proposed to reconstruct aerial lidar point cloud and based on the constructed model 3D ground filtering (V3GF) is developed for separating ground points from unground ones. The proposed V3GF algorithm selects the lowest voxels with a value of 1 as ground seeds and then labels them and their 3D connected set as ground voxels. The ISPRS benchmark dataset are used to compare the performance of V3GF with those of eight other publicized filtering methods. Results indicate that the V3GF improves on Axelsson's performance on five samples in terms of total error. The average Kappa coefficients for sites with relatively flat urban areas, rough slope and discontinuous surfaces are 92.49 percent, 72.23 percent and 61.27 percent, respectively. Numéro de notice : A2017-038 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.83.2.95 En ligne : https://doi.org/10.14358/PERS.83.2.95 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84139
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 2 (February 2017) . - pp 95 - 107[article]Characterizing vegetation canopy structure using airborne remote sensing data / Debsunder Dutta in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)
[article]
Titre : Characterizing vegetation canopy structure using airborne remote sensing data Type de document : Article/Communication Auteurs : Debsunder Dutta, Auteur ; Kunxuan Wang, Auteur ; Esther Lee, Auteur Année de publication : 2017 Article en page(s) : pp 1160 - 1178 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] canopée
[Termes IGN] densité de la végétation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuille (végétation)
[Termes IGN] forêt ripicole
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] voxelRésumé : (Auteur) Vegetation canopy structure plays an important role in the partitioning of incident solar radiation, photosynthesis, transpiration, and other scalar fluxes. The vertical foliage distribution of the plant canopy is represented by leaf area density (LAD), which is defined as the one-sided leaf area per unit volume. Airborne light detection and ranging (LiDAR) offers the possibility to characterize the 3-D variation of LAD over space, which still remains a challenge to estimate. Moreover, the low density of point cloud data generally offered by airborne LiDAR may be insufficient for accurate LAD estimation in dense overlapping forest canopies. We develop a method for the estimation of the LAD profile using a combination of airborne LiDAR and hyperspectral data using a feature-based data fusion approach. After identifying vegetation species using hyperspectral data, point cloud LiDAR data is used in a “tree-shaped” voxel approach to characterize the LAD of trees in a riparian forest setting. We also propose a set of relationships on simple geometry of overlap for the construction of tree shaped voxels. In a forest setting with overlapping canopies, the results indicate that the tree-shaped voxels are better able to attribute the LAD to the upper and middle parts of the overall canopy as well as individual tall and short trees compared with traditional cylindrical voxels. Numéro de notice : A2017-147 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2620478 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2620478 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84635
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 2 (February 2017) . - pp 1160 - 1178[article]Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics / David Kelbe in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)
[article]
Titre : Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics Type de document : Article/Communication Auteurs : David Kelbe, Auteur ; Jan Van Aardt, Auteur ; Paul Romanczyk, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 729 - 741 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] acquisition de données
[Termes IGN] carte de confiance
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt
[Termes IGN] mesure géométrique
[Termes IGN] New York (Etats-Unis ; état)
[Termes IGN] numérisation
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] superpositionRésumé : (Auteur) Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in order to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. This paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm. Numéro de notice : A2017-142 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2614251 En ligne : https://doi.org/10.1109/TGRS.2016.2614251 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84630
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 2 (February 2017) . - pp 729 - 741[article]Statistical Relational Learning of Grammar Rules for 3D Building Reconstruction / Youness Dehbi in Transactions in GIS, vol 21 n° 1 (February 2017)
[article]
Titre : Statistical Relational Learning of Grammar Rules for 3D Building Reconstruction Type de document : Article/Communication Auteurs : Youness Dehbi, Auteur ; Fabian Hadiji, Auteur ; Gerhard Gröger, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 134 – 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage dirigé
[Termes IGN] arbre de décision
[Termes IGN] modèle sémantique de données
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] restitution lasergrammétrique
[Termes IGN] semis de points
[Termes IGN] traitement d'imageRésumé : (auteur) The automatic interpretation of 3D point clouds for building reconstruction is a challenging task. The interpretation process requires highly structured models representing semantics. Formal grammars can describe structures as well as the parameters of buildings and their parts. We propose a novel approach for the automatic learning of weighted attributed context-free grammar rules for 3D building reconstruction, supporting the laborious manual design of rules. We separate structure from parameter learning. Specific Support Vector Machines (SVMs) are used to generate a weighted context-free grammar and predict structured outputs such as parse trees. The grammar is extended by parameters and constraints, which are learned based on a statistical relational learning method using Markov Logic Networks (MLNs). MLNs enforce the topological and geometric constraints. MLNs address uncertainty explicitly and provide probabilistic inference. They are able to deal with partial observations caused by occlusions. Uncertain projective geometry is used to deal with the uncertainty of the observations. Learning is based on a large building database covering different building styles and façade structures. In particular, a treebank that has been derived from the database is employed for structure learning. Numéro de notice : A2017-163 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12200 En ligne : http://dx.doi.org/10.1111/tgis.12200 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84693
in Transactions in GIS > vol 21 n° 1 (February 2017) . - pp 134 – 150[article]Large Scale Mobile Mapping Project in Belgium Combines 360° Images and LiDAR / Lies Steel in Lidar magazine, vol 7 n° 1 ([27/01/2017])
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Titre : Large Scale Mobile Mapping Project in Belgium Combines 360° Images and LiDAR Type de document : Article/Communication Auteurs : Lies Steel, Auteur Année de publication : 2017 Article en page(s) : 4 p. Langues : Anglais (eng) Descripteur : [Termes IGN] semis de points Résumé : (auteur) [introduction] In January 2017 IMAGE-V, the consortium formed by Teccon and Sweco Belgium, published the last data set of Flanders in 3D LIDAR and high resolution 360° images. This concluded the 2-year project for the Flemish authorities in which the entire road network of Flanders (64.000 kms) was captured not only by 360° images (as had been done before...) but also synchronously by LIDAR point cloud data. All mobile mapping data of Flanders, the northern region of Belgium, is available free of charge for local and regional authorities. A web-based viewer and software plugins for GIS- and CAD-systems allow inspections, measurements and inventarisations in a very efficient and accurate way. Numéro de notice : A2017-035 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : http://www.lidarmag.com/content/view/12138/198/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84081
in Lidar magazine > vol 7 n° 1 [27/01/2017] . - 4 p.[article]Documents numériques
en open access
Large Scale Mobile Mapping ProjectAdobe Acrobat PDF Caractérisation de la végétation de Rennes Métropole par relevé LiDAR en vue de sa modélisation / Clément Doceul (2017)PermalinkComparison of belief propagation and graph-cut approaches for contextual classification of 3D LIDAR point cloud data / Loïc Landrieu (2017)PermalinkContributions méthodologiques pour la caractérisation des milieux par imagerie optique et lidar / Nesrine Chehata (2017)PermalinkEtude de l'impact d'un projet de développement sur les propriétés avoisinantes / Sylvain Jourdan (2017)PermalinkEtude et méthodes d'intégration et d'interaction de données 3D complexes type "nuages de points" vers un web SIG / Victor Lambert (2017)PermalinkFaucon noir : retour d'expérience sur une étude de la biodiversité par drone / Laurent Beaudoin in Revue Française de Photogrammétrie et de Télédétection, n° 213 - 214 (janvier - avril 2017)PermalinkFeasibility of Terrestrial laser scanning for collecting stem volume information from single trees / Ninni Saarinen in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)PermalinkFusing meter-resolution 4-D InSAR point clouds and optical images for semantic urban infrastructure monitoring / Yuanyuan Wang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)PermalinkHandbook on advances in remote sensing and geographic information systems / Margarita N. Favorskaya (2017)PermalinkA hierarchical methodology for urban facade parsing from TLS point clouds / Zhuqiang Li in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)Permalink