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Les recherches sur les réseaux au laboratoire COGIT : bilan et perspectives [diaporama] / Jean-François Gleyze (2009)
Titre : Les recherches sur les réseaux au laboratoire COGIT : bilan et perspectives [diaporama] Type de document : Article/Communication Auteurs : Jean-François Gleyze , Auteur Editeur : Paris : Institut Géographique National - IGN (1940-2007) Année de publication : 2009 Conférence : Journées Recherche de l'IGN 2009, 18es journées 11/03/2009 12/03/2009 Saint-Mandé France OA program Importance : 36 p. Format : 30 x 21 cm Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatiale
[Termes IGN] Conception Objet et Généralisation de l'Information Topographique = Cartographie et Géomatique
[Termes IGN] données vectorielles
[Termes IGN] figure géométrique
[Termes IGN] généralisation automatique de données
[Termes IGN] indicateur spatial
[Termes IGN] relation topologique
[Termes IGN] réseau de transport
[Termes IGN] réseau hydrographiqueNuméro de notice : C2009-056 Affiliation des auteurs : COGIT (1988-2011) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64204 Documents numériques
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Les recherches sur les réseaux ... - pdf auteurAdobe Acrobat PDF Verification of topographic road centerline data using ALOS/PRISM images: implementation / H. Fujimura in Bulletin of the Geographical survey institute, vol 56 (December 2008)
[article]
Titre : Verification of topographic road centerline data using ALOS/PRISM images: implementation Type de document : Article/Communication Auteurs : H. Fujimura, Auteur ; H. Ninami, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 27 - 36 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] axe médian
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image ALOS-PRISM
[Termes IGN] image panchromatique
[Termes IGN] Japon
[Termes IGN] niveau de gris (image)
[Termes IGN] précision du positionnement
[Termes IGN] route
[Termes IGN] système d'information cartographique
[Termes IGN] valeur radiométriqueRésumé : (Auteur) Elimination of displacement due to map editing inherent in road centerline data of the New Topographic map Information System (NTIS) is implemented. Panchromatic satellite images from ALOS/PRISM are used in the process. Histogram analysis of gray value profiles parallel to the roads is employed. The true-position candidate is selected by supervised classification of histograms using support vector machine (SVM) method. According to the experiments with the Japanese NTIS road centerline database, the proposed method reverses the displacement of approximately 50 % of the road features, while a further 20% of the road features are validated as already located at the true position. The proposed method is proved to be useful for German Amtliches Topographisch-Kartographisches InformationsSystem (ATKIS) road database. This indicates wider applicability of this method to various geographic regions. Copyright Geographical Survey Institute Numéro de notice : A2008-518 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : sans En ligne : https://www.gsi.go.jp/common/000048821.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29587
in Bulletin of the Geographical survey institute > vol 56 (December 2008) . - pp 27 - 36[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 250-08021 RAB Revue Centre de documentation En réserve L003 Disponible A Polygonal approach for automation in extraction of serial modular roofs / Y. Avrahami in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 11 (November 2008)
[article]
Titre : A Polygonal approach for automation in extraction of serial modular roofs Type de document : Article/Communication Auteurs : Y. Avrahami, Auteur ; Y. Raizman, Auteur ; Y. Doytsher, Auteur Année de publication : 2008 Article en page(s) : pp 1365 - 1378 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] base de connaissances
[Termes IGN] classificateur paramétrique
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] polygone
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] toit
[Termes IGN] visualisation 3DRésumé : (Auteur) This paper presents a novel approach for automation in roof extraction from two solved aerial images. The approach assumes that roofs are composed of several spatial polygons, and that they can be obtained by extracting all or even only some of them if the model is known. In view of this assumption, innovative algorithms for semi-automatic spatial polygon extraction were developed. These algorithms are based on a 2D approach to solving the 3D reality. Based on these algorithms, an interactive and semi-automatic modelbased approach for automation in roof extraction was developed. The approach is composed of two phases: manual (interactive) and automatic. In the manual (interactive) phase, the operator needs to choose an Expanded Parameterized Model (EPM) from a knowledge base and select one pre-prepared Interactive Option for Extraction (IOE) of the roof. Then, the operator needs to point according to the guidelines of the chosen option in the left image space. In the automatic phase, the selected spatial polygons are extracted, the parameters of the selected model are calculated and the roof is reconstructed. The approach was examined and the results we obtained had standard accuracy. It appears that the approach can be implemented on many types of roofs and under diverse photographic conditions. In this paper, the algorithms, the experiments and the results are detailed. Copyright ASPRS Numéro de notice : A2008-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.11.1365 En ligne : https://doi.org/10.14358/PERS.74.11.1365 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29401
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 11 (November 2008) . - pp 1365 - 1378[article]Using a binary space partitioning tree for reconstructing polyhedral building models from airborne Lidar data / Gunho Sohn in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 11 (November 2008)
[article]
Titre : Using a binary space partitioning tree for reconstructing polyhedral building models from airborne Lidar data Type de document : Article/Communication Auteurs : Gunho Sohn, Auteur ; X. Huang, Auteur ; V. Tao, Auteur Année de publication : 2008 Article en page(s) : pp 1425 - 1438 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre-B
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] modélisation 3D
[Termes IGN] polyèdre
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] toitRésumé : (Auteur) During the past several years, point density covering topographic objects with airborne lidar (Light Detection And Ranging) technology has been greatly improved. This achievement provides an improved ability for reconstructing more complicated building roof structures; more specifically, those comprising various model primitives horizontally and/or vertically. However, the technology for automatically reconstructing such a complicated structure is thus far poorly understood and is currently based on employing a limited number of pre-specified building primitives. This paper addresses this limitation by introducing a new technique of modeling 3D building objects using a data-driven approach whereby densely collecting low-level modeling cues from lidar data are used in the modeling process. The core of the proposed method is to globally reconstruct geometric topology between adjacent linear features by adopting a BSP (Binary Space Partitioning) tree. The proposed algorithm consists of four steps: (a) detecting individual buildings from lidar data, (b) clustering laser points by height and planar similarity, (c) extracting rectilinear lines, and (d) planar partitioning and merging for the generation of polyhedral models. This paper demonstrates the efficacy of the algorithm for creating complex models of building rooftops in 3D space from airborne lidar data. Copyright ASPRS Numéro de notice : A2008-410 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.11.1425 En ligne : https://doi.org/10.14358/PERS.74.11.1425 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29402
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 11 (November 2008) . - pp 1425 - 1438[article]Generalization-oriented road line classification by means of an artificial neural network / J.L. Garcia Balboa in Geoinformatica, vol 12 n° 3 (September - November 2008)
[article]
Titre : Generalization-oriented road line classification by means of an artificial neural network Type de document : Article/Communication Auteurs : J.L. Garcia Balboa, Auteur ; Francisco Javier Ariza-López, Auteur Année de publication : 2008 Article en page(s) : pp 289 - 312 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] acquisition de connaissances
[Termes IGN] analyse en composantes principales
[Termes IGN] apprentissage dirigé
[Termes IGN] axe médian
[Termes IGN] classification par réseau neuronal
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] matrice d'erreur
[Termes IGN] objet géographique linéaire
[Termes IGN] route
[Termes IGN] segmentation
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) In line generalization, a first goal to achieve is the classification of features previous to the selection of processes and parameters. A feed forward backpropagation artificial neural network (ANN) is designed for classifying a set of road lines through a supervised learning process, attempting to emulate a classification performed by a human expert for cartographic generalization purposes. The main steps of the process are presented in this paper: (a) experimental data selection; (b) segmentation of lines into homogeneous sections, (c) sections enrichment through a set of quantitative measures derived from a principal component analysis, and qualitative information derived from road network and road type; (d) expert classification of the sections; and finally (e) the ANN design, training and validation. The quality of results is analyzed by means of error matrices after a cross-validation process giving a goodness, or percentage of agreement, over 83%. Copyright Springer Numéro de notice : A2008-282 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-007-0026-z En ligne : https://doi.org/10.1007/s10707-007-0026-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29275
in Geoinformatica > vol 12 n° 3 (September - November 2008) . - pp 289 - 312[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-08031 RAB Revue Centre de documentation En réserve L003 Disponible High resolution elevation data derived from stereoscopic CORONA imagery ground control: an approach using IKONOS and SRTM data / Nikolaos Galiatsatos in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 9 (September 2008)PermalinkShaping polyhedral buildings by the fusion of vector maps and lidar point clouds / L.C. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 9 (September 2008)PermalinkGeneralized network Voronoi diagrams: concepts, computational methods, and applications / Atsuyuki Okabe in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)PermalinkSpatial objects / R. Thompson in GIM international, vol 22 n° 7 (July 2008)PermalinkA simplicial complex-based DBMS approach to 3D topographic data modelling / F. Penninga in International journal of geographical information science IJGIS, vol 22 n° 6-7 (june 2008)PermalinkReducing edge effects in the classification of high resolution imagery / Guiyun Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 4 (April 2008)PermalinkSensitivity analysis of spatially aggregated responses: a gradient-based method / F. Pantus in International journal of geographical information science IJGIS, vol 22 n° 4-5 (april 2008)PermalinkPhotogrammetric and LIDAR data integration using the centroid of a rectangular roof as a control point / Edson Aparecido Mitishita in Photogrammetric record, vol 23 n° 121 (March - May 2008)PermalinkUnfolding the Earth: myriahedral projections / J. Van Wijk in Cartographic journal (the), vol 45 n° 1 (February 2008)PermalinkPermalink