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Using simulated Terrestrial Laser Scanning to analyse errors in high-resolution scan data of irregular surfaces / R. Hodge in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 2 (March - April 2010)
[article]
Titre : Using simulated Terrestrial Laser Scanning to analyse errors in high-resolution scan data of irregular surfaces Type de document : Article/Communication Auteurs : R. Hodge, Auteur Année de publication : 2010 Article en page(s) : pp 227 - 240 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur en position
[Termes IGN] lasergrammétrie
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de points
[Termes IGN] simulation
[Termes IGN] surface hétérogène
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) Terrestrial Laser Scanning (TLS) is increasingly being used to collect mm-resolution surface data from a broad range of environments. When scanning complex surfaces, interactions between the surface topography, laser footprint and scanner precision can introduce errors into the point cloud. Quantification of these errors is, however, limited by the availability of independent measurement techniques. This research presents simulated TLS as a new approach to error quantification. Two sets of experiments are presented. The first set demonstrates that simulated TLS is able to reproduce real TLS data from a plane and a pebble. The second set uses simulated TLS to assess a methodology developed for the collection and processing of field TLS data. Simulated TLS data is collected from surfaces up to not, vert, similar1 m2 created from regular arrays of uniform spheres (sphere diameters of 10 to 100 mm) and irregular arrays of mixed spheres (median sphere diameters of 16 to 94 mm). These data were analysed to (i) assess the effectiveness of the processing methodology at removing erroneous points; (ii) quantify the magnitude of errors in a digital surface model (DSM) interpolated from the processed point cloud; and (iii) investigate the extent to which the interpolated DSMs retained the geometric properties of the original surfaces. The processing methodology was found to be effective, especially on data from coarser surfaces, with the retained points typically having an inter-quartile range (IQR) of point errors of not, vert, similar2 mm. DSM errors varied as a function of sphere size and packing, with DSM errors having an IQR of not, vert, similar2 mm for the regular surfaces and not, vert, similar4 mm for the irregular surfaces. Finally, whilst in the finer surfaces point and DSM errors were a substantial proportion of the sphere diameters, geometrical analysis indicated that the DSMs still reproduced properties of the original surface such as semivariance and some percentiles of the surface elevation distribution. Copyright ISPRS Numéro de notice : A2010-094 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2010.01.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2010.01.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30290
in ISPRS Journal of photogrammetry and remote sensing > vol 65 n° 2 (March - April 2010) . - pp 227 - 240[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2010021 SL Revue Centre de documentation Revues en salle Disponible
Titre : Acquisition of 3D topography : automated 3D road and building reconstruction using airborne laser scanner data and topographic maps Type de document : Thèse/HDR Auteurs : Sander J. Oude Elberink, Auteur Editeur : Delft : Netherlands Geodetic Commission NGC Année de publication : 2010 Collection : Netherlands Geodetic Commission Publications on Geodesy, ISSN 0165-1706 num. 74 Importance : 172 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-90-6132-318-1 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] bati
[Termes IGN] carte topographique
[Termes IGN] données laser
[Termes IGN] données localisées 3D
[Termes IGN] lasergrammétrie
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] réseau routier
[Termes IGN] télémétrie laser aéroportéIndex. décimale : 33.80 Lasergrammétrie Résumé : (Auteur) Introduction and research goal : Our research covers the automation in acquiring three dimensional (3D) topographic objects. The research tasks focus on two specific objects: roads and buildings. These objects are of high importance in 3D city models as they are two major topographic classes in the urban environment. Our activities are located between: -1. how topographic objects exist in reality; -2. how they are captured in the data, and -3. how they appear in a modelled/virtual world. To accomplish an automated approach, existing 2D topographic maps are upgraded to 3D using airborne laser scanner data. 3D topography also includes multiple heights or even multiple objects on top of each other at a certain location. The essence in the research activities on roads differs basically from those on buildings. For roads the focus is on reconstructing the edges' height of the objects, whereas for buildings the challenge is to reconstruct the 3D polyhedral roof shape inside the building edges.
3D Road reconstruction : When examining 3D road objects, we can expect that multiple road objects cross at a certain location. An automated method for 3D modelling of complex highway interchanges is presented. Laser data and 2D topographic map data are combined in an innovative 3D reconstruction procedure. Complex situations demand for knowledge to guide the automatic reconstruction. This knowledge is used in the fusion procedure to constrain the topological and geometrical properties of the reconstructed 3D model. Laser data has been segmented and filtered before it is fused with map data. In the surface-growing algorithm combining map and laser points, the laser data is assigned to the corresponding road element. Elevations of map points are determined by least squares plane fitting through a selection of neighbouring laser points. Although results are shown using two specific data sources, the algorithm is designed to be capable of dealing with any polygon-based topographic map and any aerial laser scanner data set. Quality analysis is essential for developing a reliable reconstruction process and for a proper use of 3D data. The quality of 3D reconstructed roads strongly depends on accuracy and type of input data and the reconstruction processing steps. We predict the precision of reconstructed map elevations by propagating errors in the input data through the processing steps. Besides this quality prediction, we test the reconstructed model against independent reference data. Differences between these two datasets are explained by the predicted uncertainty in the model. Map point heights can be reconstructed with an average precision of 10 to 15 cm, depending on the laser point configuration.
3D. Building reconstruction : The building reconstruction task contains three main goals: -1. to select laser points belonging to building roofs, -2. to detect the roof structure of that building, and -3. to reconstruct the outlines of the roof. We present a building reconstruction approach, which is based on a target graph matching algorithm as intermediate step to relate laser data with building models. Establishing this relation is important for adding building knowledge to the data. Our targets are topological representations of the most common roof structures which are stored in a database. Laser data is segmented into planar patches. The segments that are selected in the segment-in-polygon algorithm are considered initial roof segments. Topological relations between segments, in terms of intersection lines and height jumps, are represented in a building roof graph. These relations are labelled according to their geometry and that of the segments (e.g. same/opposite normal direction, convex/concave, tilted/horizontal). This graph is matched with the graphs from the target database. Matching results describe which target objects appear topologically in the data. Our target based graph matching algorithm supports the first two goals. The matching algorithm performs a filtering task: data features that topologically correspond with common roof structures are considered to be part of the roof structure of that building. These data features will be transferred to our automated building reconstruction, where the outlines of the roof faces have to be reconstructed. Segments and intersection lines that do not fit to an existing target roof topology will be removed from the further automated reconstruction approach. The reconstruction algorithm covers the third main goal of our building reconstruction task. For the geometric reconstruction, we present two approaches that vary in the amount of information they take from the data. The first, more data driven approach starts with laser data features that have been matched with target models. In general, the matched intersection lines represent the interior of the roof structure, so the task is to find an appropriate solution for the remaining roof edges, e.g. eaves and gutters. Map data is used for selection of roof segments and is taken as location for walls. Therefore we need to split up map polygons in order to build walls that distinguish various height levels, e.g. at step edge locations. The second, more model driven approach reconstructs parameterised building models. This approach relies more on geometric assumptions, such as roof symmetry, but the models can be refined if the data deviates significantly from the model. The target information includes the details on how these deviations are determined and on the thresholds to decide what is significant or not. We present results of 3D reconstructed models, including several quality checks. These quality measures describe the completeness of the match results plus the correctness of assumptions to the roof outline. About 20% of the buildings are affected by segments that did not completely match with the target graphs. In a few of these cases, this is correct because the segment is not representing a roof face. However, in about 40% of these cases, a neighbouring segment that would complete a target match is missing. Adapting processing parameters, such as minimum segment size, may improve the result but it may also disturb other topological relations. Setting the parameters is therefore an important task for the operator. Specially, parameters that define the segmentation algorithm are crucial as the segment is the key data feature in our building reconstruction algorithm. In order to improve our matching algorithm, the likelihood of relations between segments could be included in the attribute list of edges in the roof topology graph. At the moment only information on the geometric appearance of the intersection line is given as attribute value to the corresponding graph edge. Future work includes defining likelihood functions for graph edges and analysing the effect of likelihood attributes.Note de contenu : Part 1: Introduction to acquisition of 3D topography
1 Introduction
1.1 3D Topography
1.2 Scope and limitations
1.3 Input data
1.4 Research problems
1.5 Goal and objectives
1.6 Importance
1.7 Thesis outline
2 Use of 3D topography
2.1 Introduction
2.2 User requirements
2.2.1 Municipality of Den Bosch
2.2.2 Survey Department of Rijkswaterstaat
2.2.3 Water board "Hoogheemraadschap de Stichtsche Rijnlanden"
2.2.4 Topographic Service of the Dutch Cadastre
2.3 Re-using 3D models
2.3.1 Municipality of Den Bosch
2.3.2 Survey Department of Rijkswaterstaat
2.3.3 Water board "Hoogheemraadschap de Stichtsche Rijnlanden"
2.3.4 Topographic Service of the Dutch Cadastre
2.3.5 Availability and distribution
2.3.6 Data fusion
2.3.7 Generalization and filtering
2.3.8 3D Represents as-is situation
2.4 Role of use cases in research project
2.5 Recent developments in using 3D topography
2.6 Conclusions
Part 2: 3D Roads
3 3D Reconstruction of roads
3.1 Introduction
3.2 Related work
3.2.1 Road reconstruction from aerial images
3.2.2 2D Road mapping from laser data
3.2.3 3D Reconstruction from laser data
3.3 Proposed approach
3.4 Data sources
3.4.1 Airborne laser scanner data
3.4.2 Pre-processing laser data
3.4.3 2D Topographic map data
3.4.4 Pre-processing 2D map
3.5 Fusion of map and laser data
3.5.1 Research problems on fusing map and laser data
3.5.2 Proposed fusion algorithm
3.6 3D Reconstruction of polygons
3.6.1 Polygon boundaries
3.6.2 Additional polygons
3.6.3 Assumptions on boundaries
3.6.4 Surfaces
3.7 Results
3.7.1 Interchange "Prins Clausplein"
3.7.2 Interchange "Waterberg"
3.8 Discussion
3.8.1 Parameter settings
3.8.2 Topological correctness
4 Quality analysis on 3D roads
4.1 Error propagation
4.1.1 Quality of plane at map point location
4.1.2 Quality of laser block
4.1.3 Quality of plane model
4.2 Reference data
4.2.1 Height differences between reference data and 3D model
4.3 Testing of predicted quality
4.4 Discussion
Part 3: 3D Buildings
5 Building shape detection
5.1 Introduction
5.1.1 Real buildings vs 3D model representation
5.1.2 Real buildings vs appearance in input data
5.1.3 Appearance in input data vs 3D model representation
5.2 Related work
5.2.1 2D Mapping of building outlines
5.2.2 3D Reconstruction of buildings
5.3 Research problems
5.3.1 Problems on roof shape detection
5.3.2 Problems on scene complexity
5.4 Proposed approach
5.5 Information from map data
5.6 Features from laser data
5.6.1 Segmentation of laser scanner data
5.6.2 Intersection lines
5.6.3 Step edges
5.6.4 Roof topology graph
5.7 Target graphs
5.8 Target based graph matching
5.9 Complete matching results
5.10 Incomplete matching results
6 3D Building Reconstruction
6.1 Introduction
6.2 Components of a roof boundary
6.3 Approach 1: Combine features from complete match results
6.4 Extension of horizontal intersection lines
6.5 Outer boundaries of roof faces
6.5.1 Flat roof faces
6.5.2 Eave construction
6.5.3 Gutter construction
6.6 Dormers and step edges
6.6.1 Simple dormers
6.6.2 Step edges
6.6.3 Step edges for map subdivision
6.7 Reconstruction of walls
6.8 Approach 2: reconstructed targets
6.8.1 Parameterised target models
6.8.2 Use of map data
6.8.3 Limitations
6.8.4 Potential use
6.9 Summary
7 Results and evaluation
7.1 Introduction
7.2 Results
7.2.1 Approach 1: Combined features
7.2.2 Approach 2: Reconstructed targets
7.3 Evaluation
7.3.1 Laser data features
7.3.2 Evaluation on target based matching
7.3.3 Reconstructed models
7.3.4 Problematic situations
7.3.5 Performance in time
7.4 Potential for nation wide 3D building database
7.5 Summary
Part 4: Conclusions and recommendations
8 Conclusions and recommendations
8.1 Conclusions
8.1.1 3D Topographic object reconstruction
8.1.2 3D Road reconstruction
8.1.3 3D Building reconstruction
8.2 RecommendationsNuméro de notice : 10833 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère DOI : sans En ligne : https://www.ncgeo.nl/index.php/en/publicatiesgb/publications-on-geodesy/item/258 [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=62510 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 10833-01 33.80 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible Airborne and terrestrial laser scanning / M. George Vosselman (2010)
Titre : Airborne and terrestrial laser scanning Type de document : Guide/Manuel Auteurs : M. George Vosselman, Éditeur scientifique ; Hans-Gerd Maas, Auteur Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2010 Importance : 318 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-1-904445-87-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection du bâti
[Termes IGN] données laser
[Termes IGN] extraction de la végétation
[Termes IGN] modèle numérique de terrain
[Termes IGN] patrimoine culturel
[Termes IGN] semis de points
[Termes IGN] système de numérisation mobile
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] télémétrie laser terrestreIndex. décimale : 33.80 Lasergrammétrie Résumé : (Editeur) Written by a team of international experts, this book provides a comprehensive overview of the major applications of airborne and terrestrial laser scanning. It focuses on principles and methods and presents an integrated treatment of airborne and terrestrial laser scanning technology. After consideration of the technology and processing methods, the book turns to applications, such as engineering, forestry, cultural heritage, extraction of 3D building models, and mobile mapping. This book brings together the various facets of the subject in a coherent text that will be relevant for advanced students, academics and practitioners. Note de contenu : Chapitre 1 - Laser Scanning Technology
Chapitre 2 - Visualisation and Structuring of Point Clouds
Chapitre 3 - Registration and Calibration
Chapitre 4 - Extraction of Digital Terrain Models
Chapitre 5 - Building Extraction
Chapitre 6 - Forestry Applications
Chapitre 7 - Engineering Applications
Chapitre 8 - Cultural Heritage Applications
Chapitre 9 - Mobile MappingNuméro de notice : 20373 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=41782 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 20373-01 33.80 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible 20373-02 DEP-TRC Livre LASTIG Dépôt en unité Exclu du prêt Extraction of vertical posts in 3D laser point clouds acquired in dense urban areas by a mobile mapping system / Sterenn Liberge (2010)
contenu dans Photogrammetric computer vision and image analysis: ISPRS Commission 3 symposium, Saint-Mandé, 1-3 septembre 2010, volume 2. Papers accepted on the basis of abstracts / Nicolas Paparoditis (2010)
Titre : Extraction of vertical posts in 3D laser point clouds acquired in dense urban areas by a mobile mapping system Type de document : Article/Communication Auteurs : Sterenn Liberge, Auteur ; Bahman Soheilian , Auteur ; Nesrine Chehata , Auteur ; Nicolas Paparoditis , Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2010 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 38-3B Conférence : PCV 2010, ISPRS - Commission 3 symposium Photogrammetric computer vision and image analysis 01/09/2010 03/09/2010 Saint-Mandé France ISPRS OA Archives Importance : pp 126 - 130 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre de décision
[Termes IGN] extraction automatique
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) This paper focuses on extracting vertical objects from 3D terrestrial point clouds, acquired in dense urban scenes. We are especially interested in urban vertical posts whose inventory is useful for many applications such as urban mapping, virtual tourism or localization. The proposed methodology is based on two steps. The first is a focalization step providing hypothetical candidates consisting of vertical features. The second step validates or rejects these candidates. In the case of validation, the features are classified according to the posts pattern library. The extraction of vertical objects is processed by projecting the point cloud in a horizontal plan. The accumulation density, the minimal and maximal heights are used to filter out ground points, tree leaves and to solve acquisition problems such as a region multiscans. After filtering step, the accumulation image is updated. Connex regions correspond to the vertical objects. These candidates are then validated regarding the posts pattern library. An analysis of the 3D vertical point distribution is processed. To do that, each region is characterized by its eigenvalues and eigenvectors based on a Principal Component Analysis in 3D space. The classification is processed by a decision tree algorithm. Results are presented on large and various datasets acquired under real conditions in a dense urban area. A global accuracy of 84 % is reached. Numéro de notice : C2010-006 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVIII/part3/b/pdf/126_XXXVIII-part3B.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65061 Factors influencing pulse width of small footprint, full wave form airborne laser scanning data / Y.C. Lin in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 1 (January 2010)
[article]
Titre : Factors influencing pulse width of small footprint, full wave form airborne laser scanning data Type de document : Article/Communication Auteurs : Y.C. Lin, Auteur ; Jon P. Mills, Auteur Année de publication : 2010 Article en page(s) : pp 49 - 59 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] balayage laser
[Termes IGN] classification automatique
[Termes IGN] impulsion laser
[Termes IGN] lidar à retour d'onde complète
[Termes IGN] longueur d'onde
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Small footprint, full waveform airborne laser scanning provides the opportunity to derive high-resolution geometric and physical information simultaneously from a single scanner system. This study evaluates the influence of various factors on the shape of the returned waveform and investigates the possibility of improving terrain classification by applying waveform-derived information. The factors discussed are surface roughness, slope angle, scan angle, amplitude, and footprint size. It is statistically demonstrated that roughness is the most significant factor affecting pulse width, and that, over relatively smooth surfaces, there is no significant variation in pulse width behavior resulting from different footprint sizes. Pulse width also exhibits a relatively stable behavior when amplitude, range distance, or scan angle vary substantially. The overall accuracy of classification achieved by applying pulse width information over all the different land-cover types examined in this study (including scrub, hillside, single trees, and forest areas) was greater than 85 percent, with > 94 percent achieved for open vegetation areas. Physical surface information provided by small footprint waveform data is considered to be at the microscale, therefore it is recommended to combine such information with geometry (e.g., filtering algorithms) for the optimal identification of terrain points. Copyright ASPRS Numéro de notice : A2010-013 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.76.1.49 En ligne : https://doi.org/10.14358/PERS.76.1.49 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30209
in Photogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 1 (January 2010) . - pp 49 - 59[article]In-flight quality assessment and data processing for airborne laser scanning / Philipp Schaer (2010)PermalinkPermalinkPermalinkSea surface topography and marine geoid by airborne laser altimetry and shipborne ultrasound altimetry / Philippe Limpach (2010)PermalinkDe la modélisation tridimensionnelle au SIG 3D / Mirko Peripimeno in Géomatique expert, n° 72 (01/12/2009)PermalinkRelevé, modélisation 3D et intégration SIG d'ouvrages d'art pour le projet Genève 3D / David Desbuisson in XYZ, n° 121 (décembre 2009 - février 2010)PermalinkThe building shadow problem of airborne lidar / T.Y. Shih in Photogrammetric record, vol 24 n° 128 (December 2009 - February 2010)PermalinkModelling the erectheion: extracting information from very large datasets / J. Beraldin in GIM international, vol 23 n° 11 (November 2009)PermalinkSmall-footprint laser scanning simulator for system validation, error assessment, and algorithm development / Antero Kukko in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 10 (October 2009)PermalinkASTM E57 international technical committee: developing standards for 3D imaging systems / A. Aindow in Geoinformatics, vol 12 n° 6 (01/09/2009)Permalink