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Auteur M. George Vosselman |
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Multiple-entity based classification of airborne laser scanning data in urban areas / S. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)
[article]
Titre : Multiple-entity based classification of airborne laser scanning data in urban areas Type de document : Article/Communication Auteurs : S. Xu, Auteur ; M. George Vosselman, Auteur ; Sander J. Oude Elberink, Auteur Année de publication : 2014 Article en page(s) : pp 1 - 15 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse multicritère
[Termes IGN] classificateur paramétrique
[Termes IGN] classification automatique d'objets
[Termes IGN] données laser
[Termes IGN] données localisées 3D
[Termes IGN] extraction de la végétation
[Termes IGN] image ALOS-PALSAR
[Termes IGN] milieu urbain
[Termes IGN] test de performanceRésumé : (Auteur) There are two main challenges when it comes to classifying airborne laser scanning (ALS) data. The first challenge is to find suitable attributes to distinguish classes of interest. The second is to define proper entities to calculate the attributes. In most cases, efforts are made to find suitable attributes and less attention is paid to defining an entity. It is our hypothesis that, with the same defined attributes and classifier, accuracy will improve if multiple entities are used for classification. To verify this hypothesis, we propose a multiple-entity based classification method to classify seven classes: ground, water, vegetation, roof, wall, roof element, and undefined object. We also compared the performance of the multiple-entity based method to the single-entity based method. Features have been extracted, in most previous work, from a single entity in ALS data; either from a point or from grouped points. In our method, we extract features from three different entities: points, planar segments, and segments derived by mean shift. Features extracted from these entities are inputted into a four-step classification strategy. After ALS data are filtered into ground and non-ground points. Features generalised from planar segments are used to classify points into the following: water, ground, roof, vegetation, and undefined objects. This is followed by point-wise identification of the walls and roof elements using the contextual information of a building. During the contextual reasoning, the portion of the vegetation extending above the roofs is classified as a roof element. This portion of points is eventually re-segmented by the mean shift method and then reclassified. Five supervised classifiers are applied to classify the features extracted from planar segments and mean shift segments. The experiments demonstrate that a multiple-entity strategy achieves slightly higher overall accuracy and achieves much higher accuracy for vegetation, in comparison to the single-entity strategy (using only point features and planar segment features). Although the multiple-entity method obtains nearly the same overall accuracy as the planar-segment method, the accuracy of vegetation improves by 3.3% with the rule-based classifier. The multiple-entity method obtains much higher overall accuracy and higher accuracy in vegetation in comparison to using only the point-wise classification method for all five classifiers. Meanwhile, we compared the performances of five classifiers. The rule-based method provides the highest overall accuracy at 97.0%. The rule-based method provides over 99.0% accuracy for the ground and roof classes, and a minimum accuracy of 90.0% for the water, vegetation, wall and undefined object classes. Notably, the accuracy of the roof element class is only 70% with the rule-based method, or even lower with other classifiers. Most roof elements have been assigned to the roof class, as shown in the confusion matrix. These erroneous assignments are not fatal errors because both a roof and a roof element are part of a building. In addition, a new feature which indicates the average point space within the planar segment is generalised to distinguish vegetation from other classes. Its performance is compared to the percentage of points with multiple pulse count in planar segments. Using the feature computed with only average point space, the detection rate of vegetation in a rule-based classifier is 85.5%, which is 6% lower than that with pulse count information. Numéro de notice : A2014-080 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32985
in ISPRS Journal of photogrammetry and remote sensing > vol 88 (February 2014) . - pp 1 - 15[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014021 RAB Revue Centre de documentation En réserve L003 Disponible EuroSDR project Commission 2, Mobile mapping - road environment mapping using mobile laser scanning / Harri Kaartinen (2013)
Titre : EuroSDR project Commission 2, Mobile mapping - road environment mapping using mobile laser scanning : final report Type de document : Chapitre/Contribution Auteurs : Harri Kaartinen, Auteur ; Juha Hyyppä, Auteur ; Antero Kukko, Auteur ; Matti Lehtomäki, Auteur ; Anttoni Jaakkola, Auteur ; M. George Vosselman, Auteur ; Sander J. Oude Elberink, Auteur ; Martin Rutzinger, Auteur ; Shi Pu, Auteur ; Matti Vaaja, Auteur Editeur : Dublin : European Spatial Data Research EuroSDR Année de publication : 2013 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] base de données routières
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] lasergrammétrie
[Termes IGN] système de numérisation mobile
[Termes IGN] télémétrie laserNote de contenu : 1. Introduction
2. State-of-the-art in mobile laser scanning
3. Benchmarking of mobile laser scanning systems on a test field
4. Benchmarking of pole detection algorithms
5. Discusion ans conclusionsNuméro de notice : H2013-009 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Chapître / contribution Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75593 Automated planimetric quality control in high accuracy airborne laser scanning surveys / M. George Vosselman in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)
[article]
Titre : Automated planimetric quality control in high accuracy airborne laser scanning surveys Type de document : Article/Communication Auteurs : M. George Vosselman, Auteur Année de publication : 2012 Article en page(s) : pp 90 - 100 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] contour
[Termes IGN] contrôle qualité
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] précision planimétrique
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] toitRésumé : (Auteur) With the increasing point densities of airborne laser scanning surveys, the applications of the generated point clouds have evolved from the production of digital terrain models to 3D modelling of a wide variety of objects. Likewise in quality control procedures criteria for height accuracy are extended with measures to describe the planimetric accuracy. This paper introduces a measure for the potential accuracy of outlining objects in a point cloud. It describes how this accuracy can be verified with the use of ridge lines of gable roofs in strip overlaps. Because of the high accuracy of modern laser scanning surveys, the influence of roof tiles onto the estimation of ridge lines is explicitly modelled. New selection criteria are introduced that allow an automated, reliable and accurate extraction of ridge lines from point clouds. The applicability of the procedure is demonstrated in a pilot project in an area covering 100,000 ha with around 20 billion points. Numéro de notice : A2012-605 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.09.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.09.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32051
in ISPRS Journal of photogrammetry and remote sensing > vol 74 (Novembrer 2012) . - pp 90 - 100[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012081 SL Revue Centre de documentation Revues en salle Disponible Verification of 2D building outlines using oblique airborne images / A. Nyaruhuma in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
[article]
Titre : Verification of 2D building outlines using oblique airborne images Type de document : Article/Communication Auteurs : A. Nyaruhuma, Auteur ; Markus Gerke, Auteur ; M. George Vosselman, Auteur ; E.G. Mtalo, Auteur Année de publication : 2012 Article en page(s) : pp 62 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre aléatoire
[Termes IGN] base de données foncières
[Termes IGN] bâtiment
[Termes IGN] boosting adapté
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] contour
[Termes IGN] image aérienne oblique
[Termes IGN] logique floueRésumé : (Auteur) Oblique airborne images are interesting not only for visualization but also for the acquisition and updating of geo-spatial vector data. This is because side views of vertical structures, such as buildings, are present in those images. In recent years, techniques for automatic verification of building outlines have been proposed. These techniques utilized color, texture and height from vertical images or range data while oblique images contain façade information that can also be used to identify buildings. This paper presents a methodology to verify 2D building outlines in a cadastral dataset by using oblique airborne images. The method searches for clues such as building edges, wall façade edges and texture. The 2D clues in images taken from different perspectives but expected to contain the same wall are transformed to 3D, combined and used for a verification of the particular wall. Unlike methods that use vertical images or LIDAR, walls are verified individually and then the results are combined for the building. We compare three methods for combining wall-based evidence. Experiments using almost 700 buildings show that best results are obtained using Adaptive Boosting where – with a bias for better identification of demolished buildings – 100% of demolished buildings are identified and 91% of existing buildings are confirmed. The other two methods are Random Trees and a variant of the Dempster–Shafer approach combined with fuzzy reasoning and they only show some minor differences to the Adaptive Boosting result. The research as presented in this paper demonstrates the potential of oblique images, but some further work has to be done, including the identification of modified buildings and the extension towards verification of 3D building models. Numéro de notice : A2012-348 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.04.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31794
in ISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 62 - 75[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible Change detection of trees in urban areas using multi-temporal airborne lidar point clouds / Wen Xiao (2012)
Titre : Change detection of trees in urban areas using multi-temporal airborne lidar point clouds Type de document : Article/Communication Auteurs : Wen Xiao, Auteur ; Sudan Xu, Auteur ; Sander J. Oude Elberink, Auteur ; M. George Vosselman, Auteur Editeur : Washington : Society of Photo-Optical Instrumentation Engineers SPIE Année de publication : 2012 Conférence : SPIE 2012, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions Conference 24/09/2012 27/09/2012 Edimbourg Royaume-Uni Proceedings SPIE Importance : n° 853207 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection d'arbres
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) Light detection and ranging (lidar) provides a promising way of detecting changes of vegetation in three dimensions (3D) because the beam of laser may penetrate through the foliage of vegetation. This study aims at the detection of changes in trees in urban areas with a high level of automation using mutil-temporal airborne lidar point clouds. Three datasets covering a part of Rotterdam, the Netherlands, have been classified into several classes including trees. A connected components algorithm was applied first to group the points of trees together. The attributes of components were utilized to differentiate tree components from misclassified non-tree components. A point based local maxima algorithm was implemented to distinguish single tree from multiple tree components. After that, the parameters of trees were derived through two independent ways: a point based method using 3D alpha shapes and convex hulls; and a model based method which fits a Pollock tree model to the points. Then the changes were detected by comparing the parameters of corresponding tree components which were matched by a tree to tree matching algorithm using the overlapping of bounding boxes and point to point distances. The results were visualized and statistically analyzed. The difference of parameters and the difference of changes derived from point based and model based methods were both lower than 10%. The comparison of these two methods illustrates the consistency and stability of the parameters. The detected changes show the potential to monitor the growth and pruning of trees. Numéro de notice : C2012-028 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1117/12.974266 Date de publication en ligne : 19/10/2012 En ligne : https://doi.org/10.1117/12.974266 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101192 Recognizing basic structures from mobile laser scanning data for road inventory studies / Shi Pu in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 6 supplement (December 2011)PermalinkQuality analysis on 3D building models reconstructed from airborne laser scanning data / Sander J. Elberink in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 2 (March - April 2011)PermalinkKnowledge-based building reconstruction from terrestrial video sequences / Yuan Tian in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 4 (July - August 2010)PermalinkPermalink3D information extraction from laser point clouds covering complex road junctions / Sander J. Oude Elberink in Photogrammetric record, vol 24 n° 125 (March - May 2009)PermalinkPermalinkAnalysis of planimetric accuracy of airborne laser scanning surveys / M. George Vosselman in Bulletin des sciences géographiques, n° 22 (octobre 2008)PermalinkBridge detection in airborne laser scanner data / George Sithole in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 1 (October 2006)PermalinkPermalinkPermalink