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Modeling 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)
[article]
Titre : Modeling spatiotemporal topological relationships between moving object trajectories along road networks based on region connection calculus Type de document : Article/Communication Auteurs : Linbing Ma, Auteur ; Min Deng, Auteur ; Jing Wu, Auteur ; Qiliang Liu, Auteur Année de publication : 2016 Article en page(s) : pp 346 - 360 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] Canton (Kouangtoung)
[Termes IGN] itinéraire
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] objet mobile
[Termes IGN] relation binaire
[Termes IGN] relation topologique
[Termes IGN] segment de droite
[Termes IGN] véhicule automobileMots-clés libres : region connection calculus Résumé : (Auteur) Considering the attempts to model spatiotemporal topological relationships between moving object trajectories, the conceptual and computational framework for moving objects along a road network has not received much attention. This paper aims to draw an improved model based on Region Connection Calculus (RCC) theory to represent the spatiotemporal topological relationships between moving object trajectories along road networks. This paper first uses a dimension reduction method based on a linear-reference transformation to model the moving object trajectories segments, and then defines new time–connection and space–connection relations between two trajectory segments. On this basis, the paper proposes an extension to the RCC-based spatiotemporal binary relationship set so that the combined semantics of the spatiotemporal predicates can be described completely. A case study was carried out using Floating Car Data in Guangzhou city. The computational results show that in a real application, the occurrence frequencies of the RCC-based binary relationships are distributed nonuniformly and the semantics of some binary relationships with the highest occurrence are coarse. Therefore, the partition of the spatiotemporal connection relations and the finer aspects of the spatiotemporal relationship model may require further research work. Numéro de notice : A2016-419 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2015.1088798 En ligne : https://doi.org/10.1080/15230406.2015.1088798 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81317
in Cartography and Geographic Information Science > Vol 43 n° 4 (September 2016) . - pp 346 - 360[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Space-time multiple regression model for grid-based population estimation in urban areas / Ko Ko Lwin in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)
[article]
Titre : Space-time multiple regression model for grid-based population estimation in urban areas Type de document : Article/Communication Auteurs : Ko Ko Lwin, Auteur ; Komei Sugiura, Auteur ; Koji Zettsu, Auteur Année de publication : 2016 Article en page(s) : pp 1579 - 1593 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] appareil portable
[Termes IGN] densité de population
[Termes IGN] estimation statistique
[Termes IGN] milieu urbain
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] population
[Termes IGN] régression multiple
[Termes IGN] TwitterRésumé : (Auteur) We can collect, store, and analyze a huge amount of information about human mobility and social interaction activities due to the emergence of information and communication technologies and location-enabled mobile devices under cyber physical system frameworks. The high spatial resolution of population data on a multi-temporal scale is required by transport planners, human geographers, social scientists, and emergency management teams. In this study, we build a space-time multiple regression model to estimate grid-based (500 m × 500 m) spatial resolution at multi-temporal scale (30-min intervals) population data based on the space-time relationship among geospatially enabled person trip (PT) survey data and incorporate both mobile call (MC) and geotagged Twitter (GT) data. Since using geospatially enabled PT survey data as dependent variables enables us to acquire actual population amounts, which strongly depend on MCs and social interaction activities. Although many grids have a strong correlation between PT and MC/GT, some show fewer correlation results, especially where the grids have factories, schools, and workshops in which fewer MCs are found but a large population is presented. Although GT data are sparser than MCs, people from amusement and tourist areas can be detected by GT data. The space-time multiple regression model can also estimate the different amounts of populations based on human travel behavior that changes over space and time. According to accuracy assessments, the night-time estimated results, especially between 00:00 and 06:30, strongly correlate with national census data except in places where the grids have railway and subway stations. Numéro de notice : A2016-319 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1143099 En ligne : http://dx.doi.org/10.1080/13658816.2016.1143099 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80939
in International journal of geographical information science IJGIS > vol 30 n° 7- 8 (July - August 2016) . - pp 1579 - 1593[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016042 RAB Revue Centre de documentation En réserve L003 Disponible 079-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Kinematic interpolation of movement data / Jed A. Long in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)
[article]
Titre : Kinematic interpolation of movement data Type de document : Article/Communication Auteurs : Jed A. Long, Auteur Année de publication : 2016 Article en page(s) : pp 854 - 868 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] interpolation
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] objet mobile
[Termes IGN] positionnement cinématique
[Termes IGN] requête spatiotemporelleRésumé : (Auteur) Mobile tracking technologies are facilitating the collection of increasingly large and detailed data sets on object movement. Movement data are collected by recording an object’s location at discrete time intervals. Often, of interest is to estimate the unknown position of the object at unrecorded time points to increase the temporal resolution of the data, to correct erroneous or missing data points, or to match the recorded times between multiple data sets. Estimating an object’s unknown location between known locations is termed path interpolation. This paper introduces a new method for path interpolation termed kinematic interpolation. Kinematic interpolation incorporates object kinematics (i.e. velocity and acceleration) into the interpolation process. Six empirical data sets (two types of correlated random walks, caribou, cyclist, hurricane and athlete tracking data) are used to compare kinematic interpolation to other interpolation algorithms. Results showed kinematic interpolation to be a suitable interpolation method with fast-moving objects (e.g. the cyclist, hurricane and athlete tracking data), while other algorithms performed best with the correlated random walk and caribou data. Several issues associated with path interpolation tasks are discussed along with potential applications where kinematic interpolation can be useful. Finally, code for performing path interpolation is provided (for each method compared within) using the statistical software R. Numéro de notice : A2016-286 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1081909 En ligne : https://doi.org/10.1080/13658816.2015.1081909 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80865
in International journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 854 - 868[article]Réservation
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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 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)
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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] tempsRésumé : (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
in International journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 1041 - 1071[article]Réservation
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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 Spatio-temporal traffic video data archiving and retrieval system / Hang Yue in Geoinformatica, vol 20 n° 1 (January - March 2016)
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Titre : Spatio-temporal traffic video data archiving and retrieval system Type de document : Article/Communication Auteurs : Hang Yue, Auteur ; Laurence R. Rilett, Auteur ; Peter Z. Revesz, Auteur Année de publication : 2016 Article en page(s) : pp 59 - 94 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données spatiotemporelles
[Termes IGN] données spatiotemporelles
[Termes IGN] dynamique spatiale
[Termes IGN] positionnement automatique
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] requête (informatique)
[Termes IGN] vidéo numérique
[Termes IGN] vitesseRésumé : (auteur) This paper presents a transportation spatio-temporal system that efficiently converts traffic video data into vehicular motion information in spatio-temporal databases for a variety of transportation applications. The proposed transportation spatio-temporal system interpolates the vehicle trajectory data (i.e., time, location, and speed), which are extracted from video, and integrates them with spatial road information for storage of dynamic transportation environments. The proposed transportation spatio-temporal system can mitigate data storage and retrieval issues related to storing large amounts of traffic video. Moreover, users can manage and operate multiform and multidimensional traffic data in a spatio-temporal transportation environment. The proposed approach is demonstrated for typical transportation applications. The experimental results show that the proposed transportation spatio-temporal system has excellent potential for addressing issues related to storage of large amounts of traffic video data. Numéro de notice : A2016-366 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-015-0231-0 En ligne : http://dx.doi.org/10.1007/s10707-015-0231-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81129
in Geoinformatica > vol 20 n° 1 (January - March 2016) . - pp 59 - 94[article]An exploration of future patterns of the contributions to OpenStreetMap and development of a contribution index / Jamal Jokar Arsanjani in Transactions in GIS, vol 19 n° 6 (December 2015)PermalinkGérer les informations temporelles dans et par les modèles informatiques / Frédéric Bertrand in Revue internationale de géomatique, vol 25 n° 3 (septembre - novembre 2015)PermalinkRegards croisés sur la modélisation des dynamiques spatiales / Anne Ruas in Revue internationale de géomatique, vol 25 n° 3 (septembre - novembre 2015)PermalinkAn evaluation and classification of nD topological data structures for the representation of objects in a higher-dimensional GIS / Ken Arroyo Ohori in International journal of geographical information science IJGIS, vol 29 n° 5 (May 2015)PermalinkForming a global monitoring mechanism and a spatiotemporal performance model for geospatial services / Jizhe Xia in International journal of geographical information science IJGIS, vol 29 n° 3 (March 2015)PermalinkBayesian belief networks as a versatile method for assessing uncertainty in land-change modeling / Carsten Krüger in International journal of geographical information science IJGIS, vol 29 n° 1 (January 2015)PermalinkUn système d'information géographique pour le suivi d'objets historiques urbaines à travers l'espace et le temps / Bertrand Duménieu (2015)PermalinkCloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model / Qing Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 92 (June 2014)PermalinkSimuler les évolutions urbaines à l'aide de données géographiques urbaines 3D / Mickaël Brasebin in Revue internationale de géomatique, vol 24 n° 2 (juin - août 2014)PermalinkA comparative study of two approaches for supporting optimal network location queries / Parisa Ghaemi in Geoinformatica, vol 18 n° 2 (April 2014)PermalinkA general framework for trajectory data warehousing and visual OLAP / Luca Leonardi in Geoinformatica, vol 18 n° 2 (April 2014)PermalinkA morphological approach to predicting urban expansion / Jamal Jokar Arsanjani in Transactions in GIS, vol 18 n° 2 (April 2014)PermalinkDissemination and geovisualization of territorial entities’ history / Christine Plumejeaud in Journal of Spatial Information Science (JoSIS), n° 8 (2014)PermalinkObjets géographiques et processus de changement / Hélène Mathian (2014)PermalinkThinking about space-time connections : spatiotemporal scheduling of individual activities / Kathleen Stewart in Transactions in GIS, vol 17 n° 6 (December 2013)PermalinkModeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques / M. Sarabuddin Mondal in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkA spatio-temporal graph model for marine dune dynamics analysis and representation / Rémy Thibaud in Transactions in GIS, vol 17 n° 5 (October 2013)PermalinkModèles et méthodes pour l'information spatio-temporelle évolutive / Christine Plumejeaud in Cartes & Géomatique, n° 215 (mars 2013)PermalinkProcessing aggregated data: the location of clusters in health data / Kevin Buchin in Geoinformatica, vol 16 n° 3 (July 2012)PermalinkDiscovering spatial patterns in origin-destination mobility data / D. Guo in Transactions in GIS, vol 16 n° 3 (June 2012)Permalink