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Point cloud server (PCS) : point clouds in-base management and processing / Rémi Cura in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W5 (October 2015)
[article]
Titre : Point cloud server (PCS) : point clouds in-base management and processing Type de document : Article/Communication Auteurs : Rémi Cura, Auteur ; Julien Perret , Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2015 Conférence : ISPRS 2015, Geospatial Week : Laserscanning, ISSDQ, CMRT, ISA, GeoVIS, GeoBigData 28/09/2015 03/10/2015 La Grande Motte France ISPRS OA Annals Article en page(s) : pp 531 - 539 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] code source libre
[Termes IGN] compression de données
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] métadonnées
[Termes IGN] semis de points
[Termes IGN] serveur de données localisées
[Termes IGN] système de gestion de bases de données relationnelles
[Termes IGN] traitement de semis de pointsRésumé : (auteur) In addition to the traditional Geographic Information System (GIS) data such as images and vectors, point cloud data has become more available. It is appreciated for its precision and true three-Dimensional (3D) nature. However, managing the point cloud can be difficult due to scaling problems and specificities of this data type. Several methods exist but are usually fairly specialised and solve only one aspect of the management problem. In this work, we propose a complete and efficient point cloud management system based on a database server that works on groups of points rather than individual points. This system is specifically designed to solve all the needs of point cloud users: fast loading, compressed storage, powerful filtering, easy data access and exporting, and integrated processing. Moreover, the system fully integrates metadata (like sensor position) and can conjointly use point clouds with images, vectors, and other point clouds. The system also offers in-base processing for easy prototyping and parallel processing and can scale well. Lastly, the system is built on open source technologies; therefore it can be easily extended and customised. We test the system will several billion points of point clouds from Lidar (aerial and terrestrial ) and stereo-vision. We demonstrate ~ 400 million pts/h loading speed, user-transparent greater than 2 to 4:1 compression ratio, filtering in the approximately 50 ms range, and output of about a million pts/s, along with classical processing, such as object detection. Numéro de notice : A2015--059 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W5-531-2015 Date de publication en ligne : 20/08/2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W5-531-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82690
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W5 (October 2015) . - pp 531 - 539[article]Adaptive algorithm for large scale DTM interpolation from lidar data for forestry applications in steep forested terrain / Almasi S. Maguya in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
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Titre : Adaptive algorithm for large scale DTM interpolation from lidar data for forestry applications in steep forested terrain Type de document : Article/Communication Auteurs : Almasi S. Maguya, Auteur ; Virpi Junttila, Auteur ; Tuomo Kauranne, Auteur Année de publication : 2013 Article en page(s) : pp 74 - 83 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] fonction spline d'interpolation
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de terrain
[Termes IGN] morphologie mathématique
[Termes IGN] Népal
[Termes IGN] penteRésumé : (Auteur) Light Detection and Ranging (lidar) has become a valuable tool in forest inventory because it yields accurate measurements of tree heights. However, tree height can be accurate only if the height of the ground, i. e., the Digital Terrain Model (dtm) is first accurately established. Although great advances have been made in lidar technology over the past decade, filtering lidar data for Digital Terrain Model (dtm) interpolation is still a challenge, especially in steep and complex terrain with forest cover. Several algorithms proposed in the literature address this challenge but their performance deteriorates with the decreasing point density caused by the presence of forest cover and steep slopes. In this paper, we propose a new adaptive algorithm for dtm interpolation from lidar data in steep terrain with forest cover. The algorithm partitions the input data and estimates a section of the dtm by fitting a linear or quadratic trend surface, or uses cubic spline interpolation depending on the complexity of the section of terrain. The performance of the algorithm is tested in three ways: by visual assessment, by comparison of the tree-height estimates produced using the generated dtm with those obtained using field survey, and by use of International Society for Photogrammetry and Remote Sensing (isprs) test data. Test results show that the algorithm can cope well with steep slopes and low lidar point densities, giving a more accurate estimate of average tree height compared to conventional algorithms. The algorithm can be used for dtm extraction in large scale forest inventory projects in challenging environments–complex terrain and low lidar point densities. Numéro de notice : A2013-608 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.08.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32744
in ISPRS Journal of photogrammetry and remote sensing > vol 85 (November 2013) . - pp 74 - 83[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013111 RAB Revue Centre de documentation En réserve L003 Disponible A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data / Chuanfa Chen in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)
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Titre : A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur Année de publication : 2013 Article en page(s) : pp 1 - 9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse multirésolution
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] interpolation
[Termes IGN] Kappa de Cohen
[Termes IGN] semis de points
[Termes IGN] seuillage de pointsRésumé : (Auteur) We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were used to compare the performance of MHC with those of the 17 other publicized filtering methods. Results indicated that MHC with the average total error and average Cohen’s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods. Numéro de notice : A2013-407 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.05.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.05.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32545
in ISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 1 - 9[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013081 RAB Revue Centre de documentation En réserve L003 Disponible Ground filtering and vegetation mapping using multi-return terrestrial laser scanning / Francesco Pirotti in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
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Titre : Ground filtering and vegetation mapping using multi-return terrestrial laser scanning Type de document : Article/Communication Auteurs : Francesco Pirotti, Auteur ; A. Guarnieri, Auteur ; Antonio Vettore, Auteur Année de publication : 2013 Article en page(s) : pp 56 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] densité de la végétation
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] hauteur de la végétation
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) Discriminating laser scanner data points belonging to ground from points above-ground (vegetation or buildings) is a key issue in research. Methods for filtering points into ground and non-ground classes have been widely studied mostly on datasets derived from airborne laser scanners, less so for terrestrial laser scanners. Recent developments in terrestrial laser sensors (longer ranges, faster acquisition and multiple return echoes) has aroused greater interest for surface modelling applications. The downside of TLS is that a typical dataset has high variability in point density, with evident side-effects on processing methods and CPU-time. In this work we use a scan dataset from a sensor which returns multiple target echoes, in this case providing more than 70 million points on our study site. The area presents low, medium and high vegetation, undergrowth with varying density, as well as bare ground with varying morphology (i.e. very steep slopes as well as flat areas). We test an integrated work-flow for defining a terrain and surface model (DTM and DSM) and successively for extracting information on vegetation density and height distribution on such a complex environment. Attention was given to efficiency and speed of processing. The method consists on a first step which subsets the original points to define ground candidates by taking into account the ordinal return number and the amplitude. A custom progressive morphological filter (opening operation) is applied next, on ground candidate points using a multidimensional grid to account for the fallout in point density as a function of distance from scanner. Vegetation density mapping over the area is then estimated using a weighted ratio of point counts in the tri-dimensional space over each cell. The overall result is a pipeline for processing TLS points clouds with minimal user interaction, producing a Digital Terrain Model (DTM), a Digital Surface Model (DSM), a vegetation density map and a derived Canopy Height Model (CHM). These products are of high importance for many applications ranging from forestry to hydrology and geomorphology. Numéro de notice : A2013-092 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.08.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32230
in ISPRS Journal of photogrammetry and remote sensing > vol 76 (February 2013) . - pp 56 - 63[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013021 RAB Revue Centre de documentation En réserve L003 Disponible Digital Elevation Model from the best results of different filtering of a LiDAR point cloud / T. Podobnikar in Transactions in GIS, vol 16 n° 5 (October 2012)
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Titre : Digital Elevation Model from the best results of different filtering of a LiDAR point cloud Type de document : Article/Communication Auteurs : T. Podobnikar, Auteur ; Anja Vrecko, Auteur Année de publication : 2012 Article en page(s) : pp 603 - 617 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de pointsRésumé : (Auteur) The LiDAR point clouds captured with airborne laser scanning provide considerably more information about the terrain surface than most data sources in the past. This rich information is not simply accessed and convertible to a high quality digital elevation model (DEM) surface. The aim of the study is to generate a homogeneous and high quality DEM with the relevant resolution, as a 2.5D surface. The study is focused on extraction of terrain (bare earth) points from a point cloud, using a number of different filtering techniques accessible by selected freeware. The proposed methodology consists of: (1) assessing advantages/disadvantages of different filters across the study area, (2) regionalization of the area according to the most suitable filtering results, (3) data fusion considering differently filtered point clouds and regions, and (4) interpolation with a standard algorithm. The resulting DEM is interpolated from a point cloud fused from partial point clouds which were filtered with multiscale curvature classification (MCC), hierarchical robust interpolation (HRI), and the LAStools filtering. An important advantage of the proposed methodology is that the selected landscape and datasets properties have been more holistically studied, with applied expert knowledge and automated techniques. The resulting highly applicable DEM fulfils geometrical (numerical), geomorphological (shape), and semantic quality properties. Numéro de notice : A2012-513 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01332.x Date de publication en ligne : 10/10/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01332.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31959
in Transactions in GIS > vol 16 n° 5 (October 2012) . - pp 603 - 617[article]A model-based approach for reconstructing a terrain surface from airborne Lidar data / Gunho Sohn in Photogrammetric record, vol 23 n° 122 (June - August 2008)PermalinkPermalinkA filtering strategy for interest point detecting to improve repeatability and information content / Q. Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 5 (May 2007)Permalink