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Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree / Giyu Chen in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 30 - 45 Titre : Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree Type de document : Article/Communication Auteurs : Giyu Chen, Auteur ; Gang Liu, Auteur ; Xiaogang Ma, Auteur ; Gregoire Mariethoz, Auteur ; Zhenwen He, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 30 - 45 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre quadratique [Termes IGN] entropie [Termes IGN] modèle numérique de terrain [Termes IGN] niveau de détail [Termes IGN] visualisation 3D Résumé : (Auteur) Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently. Numéro de notice : A2018-110 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89540 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Parallel indexing technique for spatio-temporal data / Zhenwen He in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 78 (April 2013) . - pp 116 - 128 Titre : Parallel indexing technique for spatio-temporal data Type de document : Article/Communication Auteurs : Zhenwen He, Auteur ; Menno-Jan Kraak, Auteur ; Otto Huisman, Auteur Année de publication : 2013 Article en page(s) : pp 116 - 128 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] arbre-R [Termes IGN] données hétérogènes [Termes IGN] données spatiotemporelles [Termes IGN] indexation spatiale [Termes IGN] requête spatiotemporelle [Termes IGN] système d'information géographique [Termes IGN] traitement parallèle Résumé : (Auteur) The requirements for efficient access and management of massive multi-dimensional spatio-temporal data in geographical information system and its applications are well recognized and researched. The most popular spatio-temporal access method is the R-Tree and its variants. However, it is difficult to use them for parallel access to multi-dimensional spatio-temporal data because R-Trees, and variants thereof, are in hierarchical structures which have severe overlapping problems in high dimensional space. We extended a two-dimensional interval space representation of intervals to a multi-dimensional parallel space, and present a set of formulae to transform spatio-temporal queries into parallel interval set operations. This transformation reduces problems of multi-dimensional object relationships to simpler two-dimensional spatial intersection problems. Experimental results show that the new parallel approach presented in this paper has superior range query performance than R*-trees for handling multi-dimensional spatio-temporal data and multi-dimensional interval data. When the number of CPU cores is larger than that of the space dimensions, the insertion performance of this new approach is also superior to R*-trees. The proposed approach provides a potential parallel indexing solution for fast data retrieval of massive four-dimensional or higher dimensional spatio-temporal data. Numéro de notice : A2013-182 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.01.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.01.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32320 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2013041	RAB	Revue	Centre de documentation	En réserve L003	Disponible