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Analyse et traitement d'ondes Lidar pour la cartographie et la reconnaissance de formes : application au milieu urbain / Clément Mallet (2008)
Titre : Analyse et traitement d'ondes Lidar pour la cartographie et la reconnaissance de formes : application au milieu urbain Titre original : Lidar waveform analysis and processing for cartography and pattern recognition: application to urban areas Type de document : Article/Communication Auteurs : Clément Mallet , Auteur ; Adrien Chauve , Auteur ; Frédéric Bretar, Auteur Editeur : Orsay, Chambéry : Association Française de l'Intelligence Artificielle AFIA Année de publication : 2008 Conférence : RFIA 2008, 16e conférence Reconnaissance des Formes et Intelligence Artificielle 22/01/2008 25/01/2008 Amiens France Importance : pp 693 - 702 Format : 21 x 30 cm Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification dirigée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forme d'onde
[Termes IGN] milieu urbain
[Termes IGN] onde électromagnétique
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] signal laserRésumé : (Auteur) Toute onde lidar rétrodiffusée par la surface terrestre contient des informations sur les cibles atteintes ayant contribué à la forme de l’onde. Les systèmes lidar capables de numériser l’intégralité des signaux retour sont apparus récemment et permettent le traitement a posteriori de ces profils altimétriques. Nous présentons dans cet article une méthode d’analyse puis de traitement des ondes lidar dans un contexte de cartographie automatique. Tout d’abord, nous montrons que l’analyse fine des ondes permet une densification des nuages de points 3D. Dans un second temps, le traitement a posteriori des signaux conduit à leur modélisation sous forme paramétrique. Nous proposons alors une méthode de reconnaissance de formes appliquée au milieu urbain. Une classification supervisée par Séparateurs à Vaste Marge est ainsi employée pour prendre en compte les caractéristiques des échos extraits lors de la phase de traitement. Les résultats montrent que la segmentation d’une zone urbaine en classes bâti, végétation, sol naturel et sol artificiel est possible à partir des ondes lidar seulement. Numéro de notice : 13576 Affiliation des auteurs : MATIS (1993-2011) Thématique : IMAGERIE Nature : Communication DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64263 Documents numériques
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13576_art_analyse_ondes_lidar_mallet.pdfAdobe Acrobat PDF
Titre : Analysis of full-waveform Lidar data for classification of urban areas Type de document : Article/Communication Auteurs : Uwe Soergel, Auteur ; Frédéric Bretar, Auteur ; Clément Mallet , Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2008 Collection : International Archives of Photogrammetry and Remote Sensing, ISSN 0252-8231 num. 37-B3 Conférence : ISPRS 2008, 21st ISPRS world congress 03/07/2008 11/07/2008 Pékin Chine OA ISPRS Archives Importance : pp 85 - 91 Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] impulsion laser
[Termes IGN] lidar à retour d'onde complète
[Termes IGN] milieu urbain
[Termes IGN] semis de points
[Termes IGN] signal lidar
[Termes IGN] traitement du signalRésumé : (auteur) In contrast to conventional airborne multi-echo laser scanner systems, full-waveform (FW) lidar systems are able to record the entire emitted and backscattered signal of each laser pulse. Instead of clouds of individual 3D points, FW devices provide connected 1D profiles of the 3D scene, which contain more detailed and additional information about the structure of the illuminated surfaces. This paper is focused on the analysis of FW data in urban areas. The problem of modelling FW lidar signals is first tackled. The standard method assumes the waveform to be the superposition of signal contributions of each scattering object in such a laser beam, which are approximated by Gaussian distributions. This model is suitable in many cases, especially in vegetated terrain. However, since it is not tailored to urban waveforms, the generalized Gaussian model is selected instead here. Then, a pattern recognition method for urban area classification is proposed. A supervised method using Support Vector Machines is performed on the FW point cloud based on the parameters extracted from the post-processing step. Results show that it is possible to partition urban areas in building, vegetation, natural ground and artificial ground regions with high accuracy using only lidar waveforms. Numéro de notice : C2008-022 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVII/congress/3_pdf/13.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64223 Documents numériques
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10700_isprs_2008_mallet.pdfAdobe Acrobat PDF Automatic pyramidal intensity-based laser scan matcher for 3D modeling of large scale unstructured environments / Daniela Craciun (2008)
Titre : Automatic pyramidal intensity-based laser scan matcher for 3D modeling of large scale unstructured environments Type de document : Article/Communication Auteurs : Daniela Craciun , Auteur ; Nicolas Paparoditis , Auteur ; Francis Schmitt, Auteur Editeur : New-York : IEEE Computer society Année de publication : 2008 Projets : 2-Pas d'info accessible - article non ouvert / Conférence : CRV 2008, 5th Canadian Conference on Computer and Robot Vision 28/05/2008 30/05/2008 Windsor Ontario - Canada Proceedings IEEE Importance : pp 18 - 25 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme ICP
[Termes IGN] alignement des données
[Termes IGN] appariement de données localisées
[Termes IGN] chaîne de traitement
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation de cohérence
[Termes IGN] grotte
[Termes IGN] image panoramique
[Termes IGN] image terrestre
[Termes IGN] lever souterrain
[Termes IGN] modèle 3D du site
[Termes IGN] site archéologiqueRésumé : (auteur) We are developing a vision-based system for photorealistic 3D modeling of previously unknown, complex and unstructured underground environments. Nowadays, laser range finders allow us to build 3D maps of the environment by taking multiple scans from different viewpoints. The scans are usually aligned via two post-processing steps: first, a coarse alignment is provided by an operator and second, a fine solution is computed via Iterative ClosestPoint algorithm. In this paper we describe an automatic on line scan matcher system which replaces the two post-processing steps of the existing methods. The scan matcher is powered by a pyramidal pairwise matching of 2D intensity panoramic views using a dense correlation procedure via quaternions. The proposed method does not rely on feature extraction providing thus an environment-independent solution for the scan matching task. The pyramidal structure provides a fast and accurate scan alignment in a coarse to fine approach. The scan matcher allows us to automatically build in situ 3D mosaics by integrating multiple partially overlapping scans based on a topological inference criterion which improves the global matching consistency. Tests on real data from two prehistoric caves are presented and a performance evaluation is given. Numéro de notice : C2008-026 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/CRV.2008.35 En ligne : https://doi.org/10.1109/CRV.2008.35 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97388
Titre : Calibration of a terrestrial laser scanner for engineering geodesy Type de document : Thèse/HDR Auteurs : Thorsten Schulz, Auteur Editeur : Zurich : Institut für Geodäsie und Photogrammetrie IGP - ETH Année de publication : 2008 Collection : IGP Mitteilungen, ISSN 0252-9335 num. 96 Importance : 158 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-906467-71-9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] angle d'incidence
[Termes IGN] balayage laser
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur instrumentale
[Termes IGN] étalonnage d'instrument
[Termes IGN] semis de points
[Termes IGN] télémètre laser terrestre
[Termes IGN] traitement automatique de donnéesIndex. décimale : 35.10 Acquisition d'images Résumé : (Auteur) For several years now, terrestrial laser scanning has become an additional surveying technique in geodesy. Recent developments have improved several aspects of terrestrial laser scanners, e.g. the data acquisition rate, accuracy, and range. Since such instruments are relatively new and constructed by manufacturers who do not have advanced experience in surveying instruments, investigations are needed to assess the quality of the instrumental characteristics and the acquired data. In this way, manufacturers will understand the needs of geodesists and in turn enable geodesists to provide the necessary support in the development of improvements. This thesis has three objectives, the calibration and investigation of a terrestrial laser scanner, the post-processing of point clouds acquired by laser scanners, and applications of terrestrial laser scanning.
The first objective is a comprehensive calibration and investigation of a specific laser scanner, the Imager 5003 of Zoller+Frohlich GmbH (Germany). The investigation and calibration procedures shall give a general impulse for all users of terrestrial laser scanning regarding instrumental and non-instrumental errors, the assessment of the quality of distance and angle measurements, and the influencing parameters. Laser scanners are a black box instrument that produces a huge number of 3D points in the form of a point cloud in a short time. However, it is the surveyor, who has to assess the reliability and quality of the resulting data. Therefore, the potential and the limitations of laser scanner systems must be identified. This is particularly important when a distance measurement is influenced by several parameters that can bias the data. Since laser scanning is an active surveying method, mostly independent of lighting conditions, distance measurements do not require prisms. Thus, surveying of almost every object is conceivable.
The second objective involves post-processing of the point clouds. Terrestrial laser scanning consists not only of data acquisition, but also processing of the acquired 3D data, which include an intensity value of the reflected laser beam. The point clouds define the objects and the data contains nearly all the information about the objects due to the high sampling interval of laser scanners. To produce the final result, data processing needs to be completed and this can be quiet involving, e.g. registration, data filtering, noise reduction, triangulation, and modeling. The ratio between post-processing and data acquisition can be 10:1 or greater, which means ten (or more) days of post-processing follow one day of data acquisition. This aspect of post-processing applies for both static laser scanning and kinematic laser scanning. The only difference is that kinematic laser scanning requires an unique method of registration and geo-referencing.
The third objective examines the applications of terrestrial laser scanning. Laser scanning can be used in different fields of applications, e.g. industrial metrology, cultural heritage, reverse engineering, and engineering geodesy. Due to the increased requirements regarding accuracy engineering geodesy appears to be a challenging field. Therefore, three different applications are presented which verify the successful use of terrestrial laser scanning in engineering geodesy. The first application involves the field of urban water management. A road surface was scanned to derive catchment areas and water flow directions. The second application covers the field of engineering geology. A tunnel during and after excavation was scanned to characterize rock mass structures and to derive displacement maps of surfaces and object points. Since the first two applications are based on static laser scanning, which means the laser scanner did not change in position and orientation during scanning, the third application is a kinematic one, which means the laser scanner was in motion during scanning. Such kinematic applications are of great interest since the performance of laser scanning can be increased significantly. Tunnels and roads are especially appropriate for kinematic laser scanning. The potential of kinematic laser scanning is tested by moving the laser scanner along a track line. The quality is assessed by scanning reference points.Note de contenu : 1 Introduction
1.1 Terrestrial Laser Scanning
1.2 Motivation
1.3 Outline
2 Components of Terrestrial Laser Scanner
2.1 Distance and Reflectance Measurement System
2.1.1 Electromagnetic Waves
2.1.2 Laser
2.1.3 Direct Time-of-Flight
2.1.4 Amplitude-Modulated Continuous Wave (AMCW)
2.1.5 Frequency-Modulated Continuous Wave (FMCW)
2.1.6 Overview of Distance Measurement Techniques in Terrestrial Laser Scanners
2.1.7 Avalanche Photo Diode (APD)
2.1.8 Reflection Principles
2.1.9 Reflectance Models
2.2 Angle Measurement System
2.2.1 Incremental Encoding
2.2.2 Binary Encoding
2.3 Deflection System
2.3.1 Oscillating Mirror
2.3.2 Rotating Mirror
2.3.3 Overview of Deflection Techniques in Terrestrial Laser Scanners
3 Calibration of Terrestrial Laser Scanner
3.1 Laboratories and Tools for Calibration
3.1.1 Calibration Track Line
3.1.2 Test Field of Control Points
3.1.3 Test Field of Observation Pillars
3.1.4 Electronic Unit for Frequency Measurement
3.1.5 Calibration of Spheres
3.2 Distance Measurement System
3.2.1 Static Mode
3.2.2 Scanning Mode
3.2.3 Long-Term Stability
3.2.4 Frequency Stability
3.3 Angle Measurement System
3.3.1 Horizontal Encoder
3.3.2 Vertical Encoder
3.3.3 Angular Resolution
3.4 Instrumental Errors
3.4.1 Eccentricity of Scan Center
3.4.2 Wobble of Vertical axis
3.4.3 Error of Collimation Axis
3.4.4 Error of Horizontal Axis
3.5 Non-Instrumental Errors
3.5.1 Intensity of Laser Beam
3.5.2 Angle of Incidence
3.5.3 Surface Properties of Materials
3.6 Precision and Accuracy of Terrestrial Laser Scanner Data
3.6.1 Single Point Precision
3.6.2 Accuracy of Modeled Objects (Spheres)
4 Static Laser Scanning
4.1 Data Processing
4.1.1 Blunder Detection
4.1.2 Mixed Pixel
4.1.3 Range/Intensity Crosstalk .
4.1.4 Multipath
4.1.5 Noise Reduction
4.2 Registration
4.2.1 Target-Based Registration
4.2.2 Point Cloud Registration
4.3 Modeling and Visualization
4.3.1 Geometrical Primitives
4.3.2 Triangulation
4.3.3 NURBS
4.3.4 CAD
4.3.5 Rendering and Texture Mapping
5 Kinematic Laser Scanning
5.1 Test Trolley on Calibration Track Line
5.1.1 Relative Position and Orientation
5.1.2 Absolute Position and Orientation
5.2 Rotation Time of Rotating Mirror of Laser Scanner
5.2.1 Direct Method
5.2.2 Indirect Method
5.2.3 Discussion and Comparison
5.3 Position-Fixing Using Total Station
5.3.1 Blunder Detection and Smoothing
5.3.2 Polynomial Interpolation
5.3.3 Regression Line
5.3.4 Kalman Filtering
5.4 Synchronisation
6 Applications of Terrestrial Laser Scanning
6.1 Static Application: Road Surface Analysis
6.1.1 Introduction
6.1.2 Method.
6.1.3 Results
6.2 Static Application: Rock Engineering Applications
6.2.1 Introduction
6.2.2 Method.
6.2.3 Results
6.3 Kinematic Application: Test Tunnel
6.3.1 Introduction
6.3.2 Kinematic Model: Regression Line
6.3.3 Kinematic Model: Kalman Filter
6.3.4 Results
7 Summary
7.1 Conclusions
7.2 OutlookNuméro de notice : 13652 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère En ligne : http://dx.doi.org/10.3929/ethz-a-005368245 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=62557 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 13652-01 35.10 Livre Centre de documentation En réserve M-103 Disponible Entwicklung eines Qualitätsmodells für die Generierung von digitalen Gelandemodellen aus airborne Laser scanning / Hans Jürg Luthy (2008)
Titre : Entwicklung eines Qualitätsmodells für die Generierung von digitalen Gelandemodellen aus airborne Laser scanning Titre original : [Développement d'un modèle de qualité pour générer des modèles numériques de terrain à partir de télémétrie laser aéroportée] Type de document : Thèse/HDR Auteurs : Hans Jürg Luthy, Auteur Editeur : Zurich : Institut für Geodäsie und Photogrammetrie IGP - ETH Année de publication : 2008 Collection : IGP Mitteilungen, ISSN 0252-9335 num. 95 Importance : 140 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-906467-70-2 Note générale : Bibliographie Langues : Allemand (ger) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] géoréférencement direct
[Termes IGN] GPS en mode différentiel
[Termes IGN] GPS-INS
[Termes IGN] indicateur de qualité
[Termes IGN] mesure de la qualité
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] qualité des données
[Termes IGN] spécification
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] test de performanceIndex. décimale : 35.20 Traitement d'image Résumé : (Auteur) Airborne Laser Scanning (ALS) has become the most important technology in Europe to acquire high resolution Digital Elevation Models (DEM). Compared to the well established Photogrammetry ALS allows an increased efficiency due to direct georeferencing and direct determination of 3D coordinates. The dense point spacing and the possibility to acquire simultaneous Digital Terrain (DTM) and Digital Surface Models (DSM) are additional benefits. Some of the drawbacks of ALS are known from other methods to acquire spatial data: the abstraction of the real world in a data model is strongly influenced by the impossibility to validate the quality of data acquisition by the use of on set of reference data. As a matter of fact only partial verification of single characteristics is performed using adequate methods or reference information. A well known example for this is the determination of vertical accuracy using ground control points.
The two main disadvantages compared to Photogrammetry are the number of involved sensors and the unstructured data capturing during the scanning process. The former leads - in combination with the separation in different data processing activities - to a delayed discovery of faults in the data acquisition. Not captured features (completeness of data acquisition) are often detected later on in the feature extraction. Whilst for other survey methods quality measures had been developed over years, standards or guidelines for ALS with appropriate quality indicators and test methods are still missing. The separation between the determination of coordinates in the unstructured data acquisition and the feature extraction during point classification may have a negative impact on the data quality. The use of the spatial accuracy as the dominant indicator to measure the quality of a DEM is not suited to detect errors in the point classification. Delays and excessive costs in many projects are the consequence of this lack of complete specifications if a principal conducts thorough visual inspection of the deliverables.
This thesis introduces a quality model which eliminates the above listed shortcomings. In a holistic approach sensors, algorithms and processes are examined on their impact on spatial data described. The quality model is built up on the requirements set forth in the ISO standards for quality management and for spatial data but is also taking into account the (unique) properties of the ALS technology and the sensitive customer relationship. The core element of the model is the product specification where the representation of the real world in the spatial data set is defined. The non-quantitative quality element is completed by the Meta data further information to allow traceability. To the second layer of the quality model belong various components to describe the quantitative quality indicators. By extending the elements from currently used spatial accuracy and point spacing all user requirements can be captured in technical specifications. The benefit can only be achieved if appropriate test methods and the acceptable conformance quality level are defined. The thesis does not attempt to define a minimum acceptable level of quality for DEMs since they strongly depend on individual user requirements but proposes ideas how the quality elements may be used. The third layer then defines requirements for process quality. Here it is distinguished between the processes for product realisation and management processes. The activities on the technical side directly impact the quality of the products and include inter alia sensor system, data processing, verification and documentation. The mid and long term quality of the products and realisation processes is achieved through the management processes. Special attendance is needed for data management due to the huge volume of data. As the outcome of the three inner layers the outermost contains finally the spatial data sets according to product definitions and technical specifications.
The complexity of the processes and the data volume requires suitable software tools, particularly for larger projects. A high level system architecture and the base functionality of such a production suite for ALS are outlined and the positive effects in the production due to increased efficiency and effectivity are demonstrated.
The benefits and the advantages of the quality model in the practical application are discussed on a large project for the Federal Office of Topographic (swisstopo).Note de contenu : l Einführung
1.1 Ausgangslage und Motivation
1.2 Ziel der Arbeit
1.3 Gliederung der Arbeit
1.4 Qualitäts- und Prozessmanagement
1.4.1 Erläuterung zum Begriff Qualität
l .4.2 Grundzüge des Qualitätsmanagements
1.4.3 Prozesse
1.4.4 Qualitätsplanung
1.4.5 Qualitätsmanagement bei ALS-Projekten
1.5 Qualität im Vermessungswesen
1.6 Qualität von Geodäten
1.6.1 Produktmerkmale
1.6.2 Allgemeine Qualitätsmerkmale von Geodäten
1.6.3 Die Qualitätsmerkmale der ISO Geonormen
1.6.4 Der Prozess der Qualitätsprüfung
1.6.5 Dokumentation der Qualitätsinformation
1.7 Qualität von Digitalen Geländemodellen
1.7.1 Begriffe
1.7.2 Modellierungsprozesse
1.7.3 Klassische Qualitätsmerkmale von DGM
2 Datenerfassung mittels Airborne Laser Scanning
2.1 Laser Scanner/
2.1.1 Laser Impuls
2.1.2 Ablenktechnologie
2.2 Positionierungs- und Orientierungssystem
2.2.1 Kinematisches DGPS
2.2.2 Inertiales Messsystem
2.2.3 Kombination der POS-Messgrössen
2.3 Vergleich der gebräuchlichsten ALS-Systeme
2.4 Unsicherheiten in der Datenerfassung
2.4. l Unsicherheit der Objekterfassung
2.4.2 Messunsicherheit in der Rangebestimmung
2.4.3 Messunsicherheit der Winkelbestimmung
2.4.4 Messunsicherheit der Positions- und Orientierungsbestimmung
2.4.5 Kombinierte Messunsicherheit
2.4.6 Anmerkung zur kombinierten Messunsicherheit
2.5 Bestimmung und Reduktion von systematischen Einflüssen
2.5. l Labor-Kalibrierung Laser Scanner
2.5.2 In situ Systemkalibrierung
2.5.3 Streifenausgleichung
2.6 Diskussion
3 Die ALS-Prozesskette
3.1 Produktspezifikation
3.2 Flugplanung
3.3 Flugvorbereitung und Systemkalibrierung
3.4 Befliegung 3.5 Berechnen der externen Orientierung
3.6 Prozessieren der Rohdaten
3.7 Filterung der Punkte
3.8 Modellbildung
3.9 Metadaten und Datenabgabe
3.10 Datensätze
3.10.1 Daten für die Planung und Vorbereitung der Arbeiten
3.10.2 Befliegung
3.10.3 Prozessieren der Rohdaten
3.10.4 Filterung der Punktwolke
3.10.5 Unterstützende Daten
3.10.6 Prozess-Aufzeichnungen
3.10.7 Qualitätskontrollen
3.11 Unsicherheiten in und aus den Prozessen
3.11.1 Umgang mit Ausreissern in der Rangebestimmung
3.11.2 Abweichungen und Fehler bei Terrain-Filterung
3.11.3 Unsicherheit aus der Modellierung
3.12 Diskussion
4 Qualitätsmodell für Airborne Laser Scanning
4.1 Aufbau des ALS-Qualitätsmodells
4.2 Nicht-quantitative Qualitätselemente
4.2.1 Allgemeine Produktdefinitionen für DGM
4.2.2 Definition des Produkts „DTM"
4.2.3 Definition des Produkts „DOM",
4.2.4 Nachvollziehbarkeit und Metadaten '
4.3 Quantitative Qualitätselemente (technischen Spezifikationen),
4.3.1 Auflösung
4.3.2 Räumliche Genauigkeit
4.3.3 Thematische Genauigkeit
4.3.4 Vollständigkeit
4.3.5 Zeitliche Genauigkeit
4.3.6 Logische Konsistenz
4.3.7 Vorschlag für technische Spezifikationen
4.4 Prozessqualität
4.5 Realisierungsprozesse
4.6 Managementprozesse
4.6.1 Projektmanagement
4.6.2 Kontinuierliche Verbesserung
4.6.3 Ausbildung und Training
4.6.4 Know-how Management
4.7 Qualitätsprüfung
4.7.1 Methoden der Qualitätsprüfungen
4.7.2 Kontrollen im Prozessablauf
4.7.3 Werkzeuge zur Qualitätskontrolle
4.7.4 Aufzeichnung der Qualitätsprüfung
4.8 Datenmanagement
4.9 Produktionssystem für ALS
4.9.1 Modul Qualitätssicherung und Visuelle Kontrolle
4.9.2 Modul Produktionsmonitoring
4.9.3 Modul Prozess-Manager
5 Analyse und Verbesserungsmöglichkeiten aus dem Projekt Landwirtschaftliche Nutzfläche
5.1 Einführung zum Projekt
5.2 Erarbeiten der Spezifikationen
5.3 Datenerfassung
5.3.1 Flugplanung
5.3.2 Schwierigkeiten in der Befliegung
5.3.3 Erkenntnisse aus der Datenerfassung im alpinen Raum
5.4 Prozessieren der Messwerte
5.4.1 Ableiten der Punktwolke aus den Messungen
5.4.2 Klassifizierung der Punkte
5.4.3 Ausbildung
5.4.4 ALS-Produktionssystem
5.5 Qualitätsmanagement
5.5.1 Kontrolle während der Befliegung
5.5.2 Kontrolle der Datenerfassung
5.5.3 Visuelle Kontrolle der Endprodukte
5.5.4 Resultate der quantitativen Qualitätsprüfungen
5.6 Diskussion der Erkenntnisse aus dem Projekt LWN
6 Schlussfolgerungen und Ausblick
6.1 Schlussfolgerungen
6.2 Ausblick
6.2.1 Monitoring des Scannens
6.2.2 Automatische Selektion der optimalen Punkte im Übeflappungsbereich
6.2.3 Filterung der Terrainpunkte
6.2.4 Echtzeit-DatenauswertungNuméro de notice : 13651 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère DOI : 10.3929/ethz-a-005396321 En ligne : http://dx.doi.org/10.3929/ethz-a-005396321 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=62556 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 13651-01 35.20 Livre Centre de documentation Télédétection Disponible PermalinkPermalinkPermalinkManaging full waveform Lidar data : a challenging task for the forthcoming years / Frédéric Bretar (2008)PermalinkPermalinkLa télédétection au service de la forêt / Françoise de Blomac in SIG la lettre, n° 93 (janvier 2008)PermalinkTerrain modeling from lidar data: Hierarchical K-means filtering and Markovian regularization / Nesrine Chehata (2008)PermalinkDevelopment of a simulation model to predict Lidar interception in forested environments / N.R. Goodwin in Remote sensing of environment, vol 111 n° 4 (28/12/2007)PermalinkImproving river flood extent delineation from synthetic aperture radar using airborne laser altimetry / D.C. Mason in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkLe lidar topographique à retour d'onde complète: Etat de l'art / Clément Mallet in Traitement du signal, vol 24 n° 6 (01/12/2007)Permalink