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ISPRS 2008, 21st ISPRS world congress 03/07/2008 11/07/2008 Pékin Chine OA ISPRS Archives
nom du congrès :
ISPRS 2008, 21st ISPRS world congress
début du congrès :
03/07/2008
fin du congrès :
11/07/2008
ville du congrès :
Pékin
pays du congrès :
Chine
site des actes du congrès :
|
Documents disponibles (9)
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Titre : Advances in photogrammetry, remote sensing and spatial information sciences : 2008 ISPRS Congress book, Beijing, 3 - 11 July 2008 Type de document : Actes de congrès Auteurs : Z. Li, Éditeur scientifique ; J. Chen, Éditeur scientifique ; Emmanuel P. Baltsavias, Éditeur scientifique Editeur : Londres : Taylor & Francis Année de publication : 2008 Collection : ISPRS Book Series num. 7 Conférence : ISPRS 2008, 21st ISPRS world congress 03/07/2008 11/07/2008 Pékin Chine OA ISPRS Archives Importance : 527 p. Format : 18 x 25 cm ISBN/ISSN/EAN : 978-0-415-47805-2 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] acquisition de données
[Termes IGN] analyse de données
[Termes IGN] données lidar
[Termes IGN] mission spatiale
[Termes IGN] modélisation 3D
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] télédétection aérienne
[Termes IGN] visualisation 3DRésumé : (Editeur) Publié à l'occasion du 21e Congrès de la Société Internationale de Photogrammétrie et de Télédétection (SIPT) à Pékin, en Chine en 2008, cet ouvrage est une compilation de 34 contributions de 62 chercheurs actifs dans l'ISPRS. Il couvre l'état de l'art en photogrammétrie, en télédétection spatiale et en sciences de l'information géographique. Il est divisé en six parties : -introduction, -capteurs, plates-formes et systèmes d'acquisition de données, -traitement et analyse des données, -modélisation, gestion et visualisation des données, -applications, -formation et coopération. Il donne un aperçu complet des progrès accomplis dans ces domaines depuis le 20e Congrès de la SIPT, qui a eu lieu en 2004 à Istanbul, en Turquie. Le volume sera précieux, non seulement aux scientifiques et aux chercheurs, mais aussi aux étudiants universitaires et aux praticiens. Note de contenu : Part I - Introduction
Chapter 1 Historical development of ISPRS, John Trinder & Lawrence Fritz
Chapter 2 Scientific-Technological developments of photogrammetry and remote sensing between 2004 and 2008, Armin Gruen
Part II - Sensors, platforms and data acquisition systems
Chapter 3 Spaceborne digital imaging sensors and systems, Gordon Petrie
Chapter 4 Airborne digital imaging sensors and systems, Gordon Petrie & Kenneth Smillie
Chapter 5 Close-range photogrammetry sensors, Hans-Gerd Maas
Chapter 6 LIDAR: Airborne and terrestrial sensors, Aloysius Wehr
Chapter 7 Land mobile mapping systems, Naser El-Sheimy
Chapter 8 Small satellite missions, Rainer Sandau
Chapter 9 Unmanned aerial vehicles for photogrammetry and remote sensing, Jurgen Everaerts
Part III - Data processing and analysis
Chapter 10 Remote sensing signatures: Measurements, modelling and applications, Shunlin Liang, Michael Schaepman & Mathias Kneubühler
Chapter 11 Geometric modelling of linear CCDs and panoramic imagers, Karsten Jacobsen
Chapter 12 DSM generation and deformation measurement from SAR data, Michele Crosetto & Paolo Pasquali
Chapter 13 Early stages of LIDAR data processing, Norbert Pfeifer & Jan Böhm
Chapter 14 Pan-Sharpening for improved information extraction, Yun Zhang
Chapter 15 Object extraction and attribution from hyperspectral images, Freek van der Meer, Harald van der Werff, Mark van der Meijde, Frank van Ruitenbeek, Chris Hecker & Steven de Jong
Chapter 16 Automated extraction of roads, buildings, and vegetation from multi-source data, Helmut Mayer, Stefan Hinz & Uwe Stilla
Chapter 17 Processing of multitemporal data and change detection, Haigang Sui, Qiming Zhou, Jianya Gong & Guorui Ma
Part IV - Data modelling, management and visualization
Chapter 18 Spatio-Temporal modelling, Wolfgang Kainz & Xinming Tang
Chapter 19 Multi-scale modelling and representation of geospatial data, Zhilin Li
Chapter 20 Multiple representation databases, Monika Sester
Chapter 21 Dynamic GIS, Christopher M. Gold, Darka Mioc & François Anton
Chapter 22 Semantic integration of heterogeneous geospatial information, Marinos Kavouras & Margarita Kokla
Chapter 23 3D Data modelling and visualization, Sabry El-Hakim
Part V - Applications
Chapter 24 Spatial data infrastructures and clearinghouses, Costas Armenakis
Chapter 25 Web mapping/GIS services and applications, Songnian Li
Chapter 26 Updating geospatial databases from images, Christian Heipke, Peter A. Woodsford & Markus Gerke
Chapter 27 Applications in cultural heritage documentation, Petros Patias, Pierre Grussenmeyer & Klaus Hanke
Chapter 28 Natural disaster management: Activities in support of the UN system, Piero Boccardo & Fabio Giulio Tonolo
Chapter 29 Environmental sensing and human health, Stanley A. Morain & Amelia M. Budge
Chapter 30 Industrial applications of photogrammetry, Thomas Luhmann & Stuart Robson
Chapter 31 Medical applications, Nicola D’apuzzo & Harvey Mitchell
Chapter 32 Forestry applications, Barbara Koch & Matthias Dees
Part VI - Education and cooperation
Chapter 33 Educational developments and outreach, Kohei Cho, Gerhard König & Joachim Höhle
Chapter 34 International cooperation and capacity building, Ian Dowman & Shunji MuraiNuméro de notice : 20097 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Actes DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=34935 Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 20097-01 CG2008 Livre Centre de documentation Congrès Disponible An efficient approach to building superstructure reconstruction using digital elevation maps / Fadi Dornaika (2008)
Titre : An efficient approach to building superstructure reconstruction using digital elevation maps Type de document : Article/Communication Auteurs : Fadi Dornaika 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 179 - 184 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] ajustement de paramètres
[Termes IGN] détection automatique
[Termes IGN] image numérique
[Termes IGN] modèle géométrique du bâti
[Termes IGN] modèle numérique de sursol
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] toitRésumé : (Auteur) This paper describes an efficient method for detecting and modeling roof superstructures (detailed volumes present on roofs such as chimneys, dormer windows...) using only a Digital Elevation Map (DEM) and an initial building model without superstructures. This problem is made challenging since both detection and reconstruction should be performed simultaneously. Our proposed method is modular. The first stage (initialization stage) provides a fast and coarse detection of possible superstructures. The second stage (refinement stage) refines the parametric models of the coarse superstructures using either an iterative improvement scheme or a stochastic diffusion where both heuristics attempt to maximize the benefit of adding a superstructure model to the whole building model. The final stage selects the most consistent set of superstructures. Experiments as well as method comparisons show the efficiency of the proposed method. Numéro de notice : 10665 Affiliation des auteurs : MATIS (1993-2011) Thématique : IMAGERIE Nature : Communication DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVII/congress/3_pdf/27.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64216
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 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
en open access
10700_isprs_2008_mallet.pdfAdobe Acrobat PDF
Titre : Detection, segmentation and characterisation of vegetation in high-resolution aerial images for 3D city modelling Type de document : Article/Communication Auteurs : Corina Iovan Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2008 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 37-B3 Conférence : ISPRS 2008, 21st ISPRS world congress 03/07/2008 11/07/2008 Pékin Chine OA ISPRS Archives Importance : pp 247 - 252 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse texturale
[Termes IGN] arbre (flore)
[Termes IGN] caractérisation
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection automatique
[Termes IGN] espèce végétale
[Termes IGN] houppier
[Termes IGN] image aérienne
[Termes IGN] image infrarouge couleur
[Termes IGN] matrice de co-occurrence
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation d'imageRésumé : (Auteur) An approach for tree species classification in urban areas from high resolution colour infrared (CIR) aerial images and the corresponding Digital Surface Model (DSM) is described in this paper. The proposed method is a supervised classification one based on a Support Vector Machines (SVM) classifier. Texture features from the Gray Level Co-occurrence Matrix (GLCM) are computed to form feature vectors for both per-pixel and per-region classification approaches. The two approaches are presented and results obtained are evaluated and compared both against each other and also against a manual defined ground truth. To perform tree species classification on highdensity urban area images, trees must previously be segmented into individual objects. All intermediary methods developed to segment individual trees will also be shortly described. Tree parameters (height, crown diameter) are estimated from the DSM. These parameters together with the tree species information are used for a 3D realistic modelling of the trees in urban environments. Results of the described system are presented for a typical scene. Numéro de notice : C2008-023 Affiliation des auteurs : MATIS (1993-2011) Thématique : FORET/IMAGERIE Nature : Communication DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVII/congress/3_pdf/38.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64218 Documents numériques
en open access
10667_isprs_2008_iovan.pdfAdobe Acrobat PDF
Titre : Lidar data classification using hierarchical K-means clustering Type de document : Article/Communication Auteurs : Frédéric Bretar, Auteur ; Nicolas David 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 325 - 330 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de groupement
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] modèle numérique de terrain
[Termes IGN] pente
[Termes IGN] semis de pointsRésumé : (Auteur) This paper deals with lidar point cloud filtering and classification for modelling the Terrain and more generally for scene segmentation. In this study, we propose to use the well-known K-means clustering algorithm that filters and segments (point cloud) data. The K-means clustering is well adapted to lidar data processing, since different feature attributes can be used depending on the desired classes. Attributes may be geometric or textural when processing only 3D-point cloud but also spectral in case of joint use of optical images and lidar data. The algorithm is based on a fixed neighbourhood size that can deal with steep relief covered by dense vegetation, mountainous area and terrains which present micro-relieves. The novelty of our algorithm consists in providing a hierarchical splitting clustering to extract ground points. The number of cluster splits is used to qualify automatically the classification reliability. This point is rarely treated in previous works. Moreover landscape predictors such as slope map are used to locally refine the classification. Finally, the methodology is extended to a multi-scale framework. The hierarchical clustering is processed from coarse DTM resolution to finer one. This implementation improves the algorithm robustness and ensures reliable ground estimation. Quantitative and qualitative results are presented on the ISPRS data set. Numéro de notice : 10664 Affiliation des auteurs : MATIS (1993-2011) Thématique : IMAGERIE Nature : Communication DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVII/congress/3b_pdf/65.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64215 Documents numériques
en open access
10664_isprs_2008_chehata.pdfAdobe Acrobat PDF
