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A topology-preserving polygon rasterization algorithm / Chen Zhou in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)
[article]
Titre : A topology-preserving polygon rasterization algorithm Type de document : Article/Communication Auteurs : Chen Zhou, Auteur ; Dingmou Li, Auteur ; Ningchuan Xiao, Auteur ; Zhenjie Chen, Auteur ; Xiang Li, Auteur ; Manchun Li, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 509 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] données vectorielles
[Termes IGN] polygone
[Termes IGN] rastérisation
[Termes IGN] relation topologique
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Conventional algorithms for polygon rasterization are typically designed to maintain non-topological characteristics. Consequently, topological relationships, such as the adjacency between polygons, may also be lost or altered, creating topological errors. This paper proposes a topology-preserving polygon rasterization algorithm to avoid topological errors. Four types of topological error may occur during polygon rasterization. The algorithm starts from an initial polygon rasterization and uses a set of preserving strategies to increase topological accuracy. The count of the four types of error measures the topological errors of the conversion. Topological accuracy is summarized as 1 minus the ratio of actual topological errors to the total number of possible error cases. When applied to a land-use dataset with a data volume of 128 MB, 127,836 polygons, and extending 1352 km2, the algorithm achieves a topological accuracy of more than 99% when raster cell size is 30 m or smaller (100% for 5 and 10 m). The effects of cell size, polygon shape, and number of iterations on topological accuracy are also examined. Numéro de notice : A2018-473 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1401488 Date de publication en ligne : 21/11/2017 En ligne : https://doi.org/10.1080/15230406.2017.1401488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91256
in Cartography and Geographic Information Science > Vol 45 n° 6 (November 2018) . - pp 495 - 509[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Compactly representing massive terrain models as TINs in CityGML / Kavisha Kumar in Transactions in GIS, vol 22 n° 5 (October 2018)
[article]
Titre : Compactly representing massive terrain models as TINs in CityGML Type de document : Article/Communication Auteurs : Kavisha Kumar, Auteur ; Hugo Ledoux, Auteur ; Jantien E. Stoter, Auteur Année de publication : 2018 Article en page(s) : pp 1152 - 1178 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] CityGML
[Termes IGN] données massives
[Termes IGN] modèle numérique de terrain
[Termes IGN] module d'extension
[Termes IGN] relation topologique
[Termes IGN] Triangulated Irregular Network
[Termes IGN] UML
[Termes IGN] XML schemaRésumé : (Auteur) Terrains form an important part of 3D city models. GIS practitioners often model terrains with 2D grids. However, TINs (Triangulated Irregular networks) are also increasingly used in practice. One such example is the 3D city model of the Netherlands (3DTOP10NL), which covers the whole country as one massive triangulation with more than one billion triangles. Due to the massive size of terrain datasets, the main issue is how to efficiently store and maintain them. The international 3D GIS standard CityGML allows us to store TINs using the Simple Feature representation. However, we argue that it is not appropriate for storing massive TINs and has limitations. We focus in this article on an improved storage representation for massive terrain models as TINs. We review different data structures for compactly representing TINs and explore how they can be implemented in CityGML as an ADE (Application Domain Extension) to efficiently store massive terrains. We model our extension using UML, and XML schemas for the extension are automatically derived from these UML models. Experiments with massive real‐world terrains show that, with this approach, we can compress CityGML files up to a factor of ~20 with one billion+ triangles, and our method has the added benefit of explicitly storing the topological relationships of a TIN model. Numéro de notice : A2018-572 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12456 Date de publication en ligne : 11/10/2018 En ligne : https://doi.org/10.1111/tgis.12456 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92296
in Transactions in GIS > vol 22 n° 5 (October 2018) . - pp 1152 - 1178[article]A simple line clustering method for spatial analysis with origin-destination data and its application to bike-sharing movement data / Biao He in ISPRS International journal of geo-information, vol 7 n° 6 (June 2018)
[article]
Titre : A simple line clustering method for spatial analysis with origin-destination data and its application to bike-sharing movement data Type de document : Article/Communication Auteurs : Biao He, Auteur ; Zhang Yan, Auteur ; Yu Chen, Auteur ; Zhihui Gu, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatio-temporelle
[Termes IGN] bicyclette
[Termes IGN] entropie
[Termes IGN] extraction de modèle
[Termes IGN] origine - destination
[Termes IGN] raisonnement spatial
[Termes IGN] voisinage (relation topologique)Résumé : (Auteur) Clustering methods are popular tools for pattern recognition in spatial databases. Existing clustering methods have mainly focused on the matching and clustering of complex trajectories. Few studies have paid attention to clustering origin-destination (OD) trips and discovering strong spatial linkages via OD lines, which is useful in many areas such as transportation, urban planning, and migration studies. In this paper, we present a new Simple Line Clustering Method (SLCM) that was designed to discover the strongest spatial linkage by searching for neighboring lines for every OD trip within a certain radius. This method adopts entropy theory and the probability distribution function for parameter selection to ensure significant clustering results. We demonstrate this method using bike-sharing location data in a metropolitan city. Results show that (1) the SLCM was significantly effective in discovering clusters at different scales, (2) results with the SLCM analysis confirmed known structures and discovered unknown structures, and (3) this approach can also be applied to other OD data to facilitate pattern extraction and structure understanding. Numéro de notice : A2018-345 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7060203 Date de publication en ligne : 29/05/2018 En ligne : https://doi.org/10.10.3390/ijgi7060203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90568
in ISPRS International journal of geo-information > vol 7 n° 6 (June 2018)[article]Weighted simplicial complex reconstruction from mobile laser scanning using sensor topology / Stéphane Guinard in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)
[article]
Titre : Weighted simplicial complex reconstruction from mobile laser scanning using sensor topology Type de document : Article/Communication Auteurs : Stéphane Guinard , Auteur ; Bruno Vallet , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Article en page(s) : pp 63 - 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] complexe simplicial
[Termes IGN] coplanarité
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle géométrique
[Termes IGN] pondération
[Termes IGN] reconstruction 3D
[Termes IGN] relation topologique
[Termes IGN] relation topologique 3D
[Termes IGN] semis de pointsRésumé : (auteur) Nous présentons une nouvelle méthode pour la reconstruction de complexes simpliciaux (ensembles de points, segments et triangles) à partir de nuages de points 3D obtenus par LiDAR mobile, à balayage plan. Notre méthode utilise la topologie inhérente au capteur LiDAR pour définir une relation spatiale entre les points. Pour cela, nous examinons chaque connexion possible entre points, pondérée en fonction de sa distance au capteur, et les filtrons en privilégiant les structures collinéaires, ou perpendiculaires aux impulsions du laser. Ensuite, nous créons et filtrons des triangles pour chaque triplet de segments connectés entre eux, en fonction de leur coplanarité locale. Nous comparons nos résultats à une reconstruction non pondérée d'un complexe simplicial. Numéro de notice : A2018-497 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2018.412 En ligne : https://doi.org/10.52638/rfpt.2018.412 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91263
in Revue Française de Photogrammétrie et de Télédétection > n° 217-218 (juin - septembre 2018) . - pp 63 - 71[article]Sensor-topology based simplicial complex reconstruction from mobile laser scanning / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2 (June 2018)
[article]
Titre : Sensor-topology based simplicial complex reconstruction from mobile laser scanning Type de document : Article/Communication Auteurs : Stéphane Guinard , Auteur ; Bruno Vallet , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Conférence : ISPRS 2018, TC II Mid-term Symposium, Towards Photogrammetry 2020 04/06/2018 07/06/2018 Riva del Garda Italie ISPRS OA Annals Article en page(s) : pp 121 - 128 Note générale : bibliographie
The authors would like to acknowledge the DGA for their financial support of this work.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] reconstruction 3D
[Termes IGN] scène
[Termes IGN] semis de points
[Termes IGN] voisinage (relation topologique)Mots-clés libres : The authors would like to acknowledge the DGA for their financial support of this work Résumé : (auteur) We propose a new method for the reconstruction of simplicial complexes (combining points, edges and triangles) from 3D point clouds from Mobile Laser Scanning (MLS). Our main goal is to produce a reconstruction of a scene that is adapted to the local geometry of objects. Our method uses the inherent topology of the MLS sensor to define a spatial adjacency relationship between points. We then investigate each possible connexion between adjacent points and filter them by searching collinear structures in the scene, or structures perpendicular to the laser beams. Next, we create triangles for each triplet of self-connected edges. Last, we improve this method with a regularization based on the co-planarity of triangles and collinearity of remaining edges. We compare our results to a naive simplicial complexes reconstruction based on edge length. Numéro de notice : A2018-271 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-2-121-2018 Date de publication en ligne : 28/05/2018 En ligne : https://doi.org/10.5194/isprs-annals-IV-2-121-2018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90347
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-2 (June 2018) . - pp 121 - 128[article]Classification of topological relations between spatial objects in two‐dimensional space within the dimensionally extended 9‐intersection model / Jingwei Shen in Transactions in GIS, vol 22 n° 2 (April 2018)PermalinkA spatio-temporal scenario model for emergency decision / Cheng Liu in Geoinformatica, vol 22 n° 2 (April 2018)PermalinkGenerating vague neighbourhoods through data mining of passive web data / Paul Brindley in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)PermalinkInterpreting the fuzzy semantics of natural-language spatial relation terms with the fuzzy random forest algorithm / Xiaonan Wang in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)PermalinkDevelopment of a Protocol to Convert and Manage Underground Infrastructure Maps into Geographic Information Systems (GIS) Format / Guillemette Fonteix (2018)PermalinkPermalinkWeighted simplicial complex reconstruction from mobile laser scanning using sensor topology / Stéphane Guinard (2018)PermalinkObject-based classification of terrestrial laser scanning point clouds for landslide monitoring / Andreas Mayr in Photogrammetric record, vol 32 n° 160 (December 2017)PermalinkSocial Distance metric: from coordinates to neighborhoods / Vagan Terziyan in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)PermalinkGeometric features and their relevance for 3D point cloud classification / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-1/W1 (May 2017)PermalinkRule-guided human classification of Volunteered Geographic Information / Ahmed Loai Ali in ISPRS Journal of photogrammetry and remote sensing, vol 127 (May 2017)PermalinkA simplified linear feature matching method using decision tree analysis, weighted linear directional mean, and topological relationships / Ick-Hoi Kim in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)PermalinkThe analysis and measurement of building patterns using texton co-occurrence matrices / Wenhao Yu in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)PermalinkClassifying natural-language spatial relation terms with random forest algorithm / Shihong Du in International journal of geographical information science IJGIS, vol 31 n° 3-4 (March-April 2017)PermalinkModeling and manipulating spacetime objects in a true 4D model / Ken Arroyo Ohori in Journal of Spatial Information Science (JoSIS), n° 14 (March 2017)PermalinkReconstructing forest canopy from the 3D triangulations of airborne laser scanning point data for the visualization and planning of forested landscapes / Jari Vauhkonen in Annals of Forest Science, vol 74 n° 1 (March 2017)PermalinkAerial lidar point cloud voxelization with its 3D ground filtering application / Liying Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 2 (February 2017)PermalinkMise en place de l’utilisation d’instruments de mesure 3D dans le cadre d’auscultations de barrages / Cyril Cadiou (2017)PermalinkA Topology-inferred graph-based heuristic algorithm for map simplification / QiuLei Guo in Transactions in GIS, vol 20 n° 5 (October 2016)PermalinkModeling spatiotemporal topological relationships between moving object trajectories along road networks based on region connection calculus / Linbing Ma in Cartography and Geographic Information Science, Vol 43 n° 4 (September 2016)Permalink