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A spatiotemporal data model and an index structure for computational time geography / Bi Yu Chen in International journal of geographical information science IJGIS, vol 37 n° 3 (March 2023)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 37 n° 3 (March 2023) . - pp 550 - 583 Titre : A spatiotemporal data model and an index structure for computational time geography Type de document : Article/Communication Auteurs : Bi Yu Chen, Auteur ; Yu-Bo Luo, Auteur ; Tao Jia, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 550 - 583 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] approche hiérarchique [Termes IGN] données massives [Termes IGN] données spatiotemporelles [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] requête spatiotemporelle [Termes IGN] stockage de données [Termes IGN] Time-geography Résumé : (auteur) The availability of Spatiotemporal Big Data has provided a golden opportunity for time geographical studies that have long been constrained by the lack of individual-level data. However, how to store, manage, and query a huge number of time geographic entities effectively and efficiently with complex spatiotemporal characteristics and relationships poses a significant challenge to contemporary GIS platforms. In this article, a hierarchical compressed linear reference (CLR) model is proposed to transform network-constrained time geographic entities from three-dimensional (3D) (x, y, t) space into two-dimensional (2D) space. Accordingly, time geographic entities can be represented as 2D spatial entities and stored in a classical spatial database. The proposed CLR model supports a hierarchical linear reference system (LRS) including not only underlying a link-based LRS but also multiple higher-level route-based LRSs. In addition, an LRS-based spatiotemporal index structure is developed to index both time geographic entities and the corresponding hierarchical network. The results of computational experiments on large datasets of space–time paths and prisms show that the proposed hierarchical CLR model is effective at storing and managing time geographic entities in road networks. The developed index structure achieves satisfactory query performance in milliseconds on large datasets of time geographic entities. Numéro de notice : A2023-153 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2128192 Date de publication en ligne : 03/10/2023 En ligne : https://doi.org/10.1080/13658816.2022.2128192 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102836 [article]

Spatiotemporal data model for network time geographic analysis in the era of big data / Bi Yu Chen in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 1041 - 1071 Titre : Spatiotemporal data model for network time geographic analysis in the era of big data Type de document : Article/Communication Auteurs : Bi Yu Chen, Auteur ; H. Yuan, Auteur ; Qingquan Li, Auteur Année de publication : 2016 Article en page(s) : pp 1041 - 1071 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données massives [Termes IGN] données spatiotemporelles [Termes IGN] entité géographique [Termes IGN] milieu urbain [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] temps Résumé : (Auteur) There has been a resurgence of interest in time geography studies due to emerging spatiotemporal big data in urban environments. However, the rapid increase in the volume, diversity, and intensity of spatiotemporal data poses a significant challenge with respect to the representation and computation of time geographic entities and relations in road networks. To address this challenge, a spatiotemporal data model is proposed in this article. The proposed spatiotemporal data model is based on a compressed linear reference (CLR) technique to transform network time geographic entities in three-dimensional (3D) (x, y, t) space to two-dimensional (2D) CLR space. Using the proposed spatiotemporal data model, network time geographic entities can be stored and managed in classical spatial databases. Efficient spatial operations and index structures can be directly utilized to implement spatiotemporal operations and queries for network time geographic entities in CLR space. To validate the proposed spatiotemporal data model, a prototype system is developed using existing 2D GIS techniques. A case study is performed using large-scale datasets of space-time paths and prisms. The case study indicates that the proposed spatiotemporal data model is effective and efficient for storing, managing, and querying large-scale datasets of network time geographic entities. Numéro de notice : A2016-294 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1104317 En ligne : https://doi.org/10.1080/13658816.2015.1104317 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80878 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2016032	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-2016031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A hybrid link-node approach for finding shortest paths in road networks with turn restrictions / Qingquan Li in Transactions in GIS, vol 19 n° 6 (December 2015)  

Public [article]  inTransactions in GIS > vol 19 n° 6 (December 2015) . - pp 915 - 929 Titre : A hybrid link-node approach for finding shortest paths in road networks with turn restrictions Type de document : Article/Communication Auteurs : Qingquan Li, Auteur ; Bi Yu Chen, Auteur ; Yafei Wang, Auteur ; William H. K. Lam, Auteur Année de publication : 2015 Article en page(s) : pp 915 - 929 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse comparative [Termes IGN] calcul d'itinéraire [Termes IGN] chemin le plus court, algorithme du [Termes IGN] navigation automobile [Termes IGN] noeud [Termes IGN] requête spatiale [Termes IGN] réseau routier [Termes IGN] traitement de données localisées Résumé : (auteur) Turn restrictions, such as ‘no left turn’ or ‘no U-turn’, are commonly encountered in real road networks. These turn restrictions must be explicitly considered in the shortest path problem and ignoring them may lead to infeasible paths. In the present study, a hybrid link-node Dijkstra's (HLND) algorithm is proposed to exactly solve the shortest path problem in road networks with turn restrictions. A new hybrid link–node labelling approach is devised by using a link–based labelling strategy at restricted nodes with turn restrictions, and a node-based labelling strategy at unrestricted nodes without turn restrictions. Computational results for several real road networks show that the proposed HLND algorithm obtains the same optimal results as the link-based Dijkstra's algorithm, while having a similar computational performance to the classical node-based Dijkstra's algorithm. Numéro de notice : A2016-438 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12133 En ligne : http://dx.doi.org/10.1111/tgis.12133 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81349 [article]