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A space-time varying graph for modelling places and events in a network / Ikechukwu Maduako in International journal of geographical information science IJGIS, vol 33 n° 10 (October 2019)
[article]
Titre : A space-time varying graph for modelling places and events in a network Type de document : Article/Communication Auteurs : Ikechukwu Maduako, Auteur ; Monica Wachowicz, Auteur Année de publication : 2019 Article en page(s) : pp 1915 - 1935 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accident de la route
[Termes IGN] analyse des risques
[Termes IGN] analyse spatio-temporelle
[Termes IGN] connexité (graphes)
[Termes IGN] graphe
[Termes IGN] relation topologique
[Termes IGN] représentation spatiale
[Termes IGN] réseau routier
[Termes IGN] système d'information géographique
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) Modelling topological relationships between places and events is challenging especially because these relationships are dynamic, and their evolutionary analysis relies on the explanatory power of representing their interactions across different temporal resolutions. In this paper, we introduce the Space-Time Varying Graph (STVG) based on the whole graph approach that combines directed and bipartite subgraphs with a time-tree for representing the complex interaction between places and events across time. We demonstrate how the proposed STVG can be exploited to identify and extract evolutionary patterns of traffic accidents using graph metrics, ad-hoc graph queries and clustering algorithms. The results reveal evolutionary patterns that uncover the places with high incidence of accidents over different time resolutions, reveal the main reasons why the traffic accidents have occurred, and disclose evolving communities of densely connected traffic accidents over time. Numéro de notice : A2019-393 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1603386 Date de publication en ligne : 17/04/2019 En ligne : https://doi.org/10.1080/13658816.2019.1603386 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93497
in International journal of geographical information science IJGIS > vol 33 n° 10 (October 2019) . - pp 1915 - 1935[article]Analysis of positional uncertainty of road networks in volunteered geographic information with a statistically defined buffer-zone method / Wen-Bin Zhang in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)
[article]
Titre : Analysis of positional uncertainty of road networks in volunteered geographic information with a statistically defined buffer-zone method Type de document : Article/Communication Auteurs : Wen-Bin Zhang, Auteur ; Yee Leung, Auteur ; Jiang-Hong Ma, Auteur Année de publication : 2019 Article en page(s) : pp 1807 - 1828 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] incertitude de position
[Termes IGN] OpenStreetMap
[Termes IGN] précision de localisation
[Termes IGN] qualité des données
[Termes IGN] réseau routier
[Termes IGN] SIG participatif
[Termes IGN] zone tamponRésumé : (auteur) Volunteered geographic information (VGI) is crowdsourced information that can enrich and enhance research and applications based on geo-referenced data. However, the quality of VGI is of great concern, and positional accuracy is a fundamental basis for the VGI quality assurance. A buffer-zone method can be used for its assessment, but the buffer radius in this technique is subjectively specified; as result, different selections of the buffer radius lead to different positional accuracies. To solve this problem, a statistically defined buffer zone for the positional accuracy assessment in VGI is proposed in this study. To facilitate practical applications, we have also developed an iterative method to obtain a theoretically defined buffer zone. In addition to the positional accuracy assessment, we have derived a measure of positional quality, which comprises the assessment of positional accuracy and the level of confidence in such assessment determined with respect to a statistically defined buffer zone. To illustrate and substantiate the theoretical arguments, both numerical simulations and real-life experiments are performed using OpenStreetMap. The experimental results confirm the high significance of the proposed statistical approach to the buffer zone-based assessment of the positional uncertainty in VGI. Numéro de notice : A2019-390 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1606430 Date de publication en ligne : 29/04/2019 En ligne : https://doi.org/10.1080/13658816.2019.1606430 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93483
in International journal of geographical information science IJGIS > vol 33 n° 9 (September 2019) . - pp 1807 - 1828[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2019091 RAB Revue Centre de documentation En réserve L003 Disponible 079-2019092 RAB Revue Centre de documentation En réserve L003 Disponible Un demi-siècle de topographie à la SNCF / Pierre Lasseur in XYZ, n° 160 (septembre 2019)
[article]
Titre : Un demi-siècle de topographie à la SNCF Type de document : Article/Communication Auteurs : Pierre Lasseur, Auteur ; Flavien Viguier, Auteur ; André Rich, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 65 - 78 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Topographie
[Termes IGN] canevas planimétrique
[Termes IGN] évolution technologique
[Termes IGN] lever topographique
[Termes IGN] photogrammétrie
[Termes IGN] précision des données
[Termes IGN] réseau de nivellement
[Termes IGN] réseau ferroviaireRésumé : (Auteur) SNCF a créé en 1970 la division de Topographie. Cette division garante de la qualité des méthodes de topographie et cartographie déployées sur le Réseau Ferré National a dû adapter son outil de travail au gré des évolutioons technologiques et règlementaires avec pour objectif la fourniture de données d'entrée de précision indispensables pour assurer la disponibilité et la sécurité des circulations. Numéro de notice : A2019-479 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93654
in XYZ > n° 160 (septembre 2019) . - pp 65 - 78[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2019031 RAB Revue Centre de documentation En réserve L003 Disponible Detecting and mapping traffic signs from Google Street View images using deep learning and GIS / Andrew Campbell in Computers, Environment and Urban Systems, vol 77 (september 2019)
[article]
Titre : Detecting and mapping traffic signs from Google Street View images using deep learning and GIS Type de document : Article/Communication Auteurs : Andrew Campbell, Auteur ; Alan Both, Auteur ; Qian (Chayn) Sun, Auteur ; Qian (Chayn) Sun, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] apprentissage profond
[Termes IGN] base de données routières
[Termes IGN] détection d'objet
[Termes IGN] feu de circulation
[Termes IGN] gestion de trafic
[Termes IGN] image Streetview
[Termes IGN] réseau routier
[Termes IGN] signalisation routière
[Termes IGN] système d'information géographique
[Termes IGN] trafic routier
[Termes IGN] vision par ordinateurRésumé : (auteur) Street traffic sign infrastructure remains an extremely difficult asset for local government to manage due to its diverse physical structure and geographical distribution. A spatial registrar of traffic infrastructure is currently a required component of local government councils' mandatory road management plans. Recent advancements of object detection technology in machine learning have presented an automated approach for the detection and classification of street signage captured by Google's Street View (GSV) imagery. This paper explores the possibility of using deep learning to produce an autonomous system for detecting traffic signs on GSV images to assist in traffic assets monitoring and maintenance. By leveraging Google's Street View API, this research offers an economic approach of building purposeful street sign computer vision datasets. A custom object detection model was trained to detect and classify Stop and Give Way signs from images captured at intersection approaches. Considering the output detected bounding box coordinates, photogrammetry approach was applied to calculate the approximate location of each detected sign in two-dimensional geographical space. The newly located and classified street signs can be combined with relevant spatial data for implementation into an asset management system. By combining GIS and the GSV API, the process is completely scalable to any level of street sign classification scope. The experiments conducted on the road network of study area recorded a detection accuracy of 95.63% and classification accuracy of 97.82%. Our proposed automated approach to the detection and localisation of street sign infrastructure has displayed a promising potential for its use by local government authorities. Our workflow can be used to detect other traffic signs and applied to other road sections and other cities. Of primary importance, this approach takes an entirely free and open-source approach throughout. The continuation of Google's Street View program will account for the spatiotemporal representation of street sign infrastructure for the ongoing maintenance and renewal programs of this valuable asset. Numéro de notice : A2019-412 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2019.101350 Date de publication en ligne : 07/06/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101350 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93536
in Computers, Environment and Urban Systems > vol 77 (september 2019)[article]Performance analysis of GLONASS integration with GPS vectorised receiver in urban canyon positioning / Amir Tabatabaei in Survey review, vol 51 n° 368 (September 2019)
[article]
Titre : Performance analysis of GLONASS integration with GPS vectorised receiver in urban canyon positioning Type de document : Article/Communication Auteurs : Amir Tabatabaei, Auteur ; Mohammad-Reza Mosavi, Auteur Année de publication : 2019 Article en page(s) : pp 460 - 471 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] canyon urbain
[Termes IGN] positionnement par GNSS
[Termes IGN] positionnement statique
[Termes IGN] récepteur GLONASS
[Termes IGN] récepteur GPS
[Termes IGN] test de performanceRésumé : (Auteur) Urban-canyon positioning encounters many problems such as successive attenuation and even blocking of the signals. Vectorised receiver is a solution in which stronger signals aid weak and blocked ones to be tracked and reacquired. On the other hand, limited accessibility to the sky makes trouble in the performance of navigation filter. As the result, integration of satellite-based positioning systems is suggested to increase the number of visible satellites in the receiver view. In this paper, the architecture of an implemented GPS-combined-GLONASS Vectorised Receiver (GGVR) in a software platform is explored and its advantages rather than a GPS-only Vectorised Receiver (GVR) are demonstrated analytically. Experimental tests in different static and dynamic scenarios are also included. The results show that in the urban-canyon trajectory where the GVR has only 80% availability, the GGVR positioning solution is 100% available in the whole movement duration. Numéro de notice : A2019-387 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1481181 Date de publication en ligne : 13/06/2018 En ligne : https://doi.org/10.1080/00396265.2018.1481181 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93477
in Survey review > vol 51 n° 368 (September 2019) . - pp 460 - 471[article]L’accessibilité ferroviaire à Paris des grandes aires urbaines françaises : approche par la time geography / Laurent Chapelon in Mappemonde, n° 127 (juillet 2019)PermalinkAccuracy assessment of speed values calculated from GNSS tracks of roads obtained from VGI / Antonio Tomás Mozas-Calvache in Survey review, vol 51 n° 367 (July 2019)PermalinkExploitation of deep learning in the automatic detection of cracks on paved roads / Won Mo Jung in Geomatica, vol 73 n° 2 (June 2019)PermalinkA hidden Markov model for matching spatial networks / Benoit Costes in Journal of Spatial Information Science (JoSIS), n° 18 (2019)PermalinkDesserte des villes du territoire métropolitain Buenos Aires – Rosario par le réseau ferroviaire de voyageurs entre 1951 et 2008 / Thomas Massin in Mappemonde, n° 126 ([01/05/2019])PermalinkA model for phased evacuations for disasters with spatio-temporal randomness / Menghui Li in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)PermalinkAnalyse spatiotemporelle des tournées de livraison d’une entreprise de livraison à domicile / Khaled Belhassine in Revue internationale de géomatique, vol 29 n° 2 (avril - juin 2019)PermalinkMulti‐temporal transport network models for accessibility studies / Diego Bogado Tomasiello in Transactions in GIS, vol 23 n° 2 (April 2019)PermalinkMultilane roads extracted from the OpenStreetMap urban road network using random forests / Yongyang Xu in Transactions in GIS, vol 23 n° 2 (April 2019)PermalinkA topographically preserved road‐network tile model and optimal routing method for virtual globes / Quanhua Dong in Transactions in GIS, vol 23 n° 2 (April 2019)Permalink