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Street-level traffic flow and context sensing analysis through semantic integration of multisource geospatial data / Yatao Zhang in Transactions in GIS, vol 26 n° 8 (December 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 8 (December 2022) . - pp 3330 - 3348 Titre : Street-level traffic flow and context sensing analysis through semantic integration of multisource geospatial data Type de document : Article/Communication Auteurs : Yatao Zhang, Auteur ; Martin Raubal, Auteur Année de publication : 2022 Article en page(s) : pp 3330 - 3348 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] allocation de Dirichlet latente [Termes IGN] appariement sémantique [Termes IGN] approche hiérarchique [Termes IGN] données multisources [Termes IGN] espace urbain [Termes IGN] flux [Termes IGN] milieu urbain [Termes IGN] point d'intérêt [Termes IGN] segmentation en régions [Termes IGN] Singapour [Termes IGN] trafic routier [Termes IGN] utilisation du sol Résumé : (auteur) Sensing urban spaces from multisource geospatial data is vital to understanding the transportation system in the urban context. However, the complexity of urban context and its indirect interaction with traffic flow deepen the difficulty of exploring their relationship. This study proposes a geo-semantic framework first to generate semantic representations of multi-hierarchical urban context and street-level traffic flow, and then investigate their mutual correlation and predictability using a novel semantic matching method. The results demonstrate that each street is associated with its multi-hierarchical spatial signatures of urban context and street-level temporal signatures of traffic flow. The correlation between urban context and traffic flow displays higher values after semantic matching than those in multi-hierarchies. Moreover, we found that utilizing traffic flow to predict urban context results in better accuracy than the reversed prediction. The results of signature analysis and relationship exploration can contribute to a deeper understanding of context-aware transportation research. Numéro de notice : A2022-916 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.13005 Date de publication en ligne : 27/11/2022 En ligne : https://doi.org/10.1111/tgis.13005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102348 [article]

Spatial big data and machine learning in GIScience, Workshop at GIScience 2018, Melbourne, Australia, 28 August 2018 / Martin Raubal (2018)    

Public Titre : Spatial big data and machine learning in GIScience, Workshop at GIScience 2018, Melbourne, Australia, 28 August 2018 : Proceedings Type de document : Actes de congrès Auteurs : Martin Raubal, Éditeur scientifique ; Shaowen Wang, Éditeur scientifique ; Mengyu Guo, Éditeur scientifique ; David Jonietz, Éditeur scientifique ; Peter Kiefer, Éditeur scientifique Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2018 Conférence : Workshop 2018 on Spatial big data and machine learning 28/08/2018 28/08/2018 Melbourne Australie OA Proceedings Importance : 53 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] apprentissage automatique [Termes IGN] données localisées [Termes IGN] données massives [Termes IGN] interface homme-machine [Termes IGN] trajectoire (véhicule non spatial) Note de contenu : PART 1: TRAJECTORIES - Stay-Move Tree for Summarizing Spatiotemporal Trajectories / Eun-Kyeong Kim - Detection of Unsigned Ephemeral Road Incidents by Visual Cues / Alex Levering, Kourosh Khoshelham, Devis Tuia, and Martin Tomko - Convolutional Neural Network for Traffic Signal Inference based on GPS Traces / Y. Méneroux, V. Dizier, M. Margollé, M.D. Van Damme, H.Kanasugi, A. Le Guilcher, G. Saint Pierre, and Y. Kato - Using Stream Processing to Find Suitable Rides: An Exploration based on New York City Taxi Data / Roswita Tschümperlin, Dominik Bucher, and Joram Schito - Classification of regional dominant movement patterns in trajectories with a convolutional neural network / Can Yang and Gyozo Gidófalvi PART 2: COGNITION & HCI - Spatial Big Data for Human-Computer Interaction / Ioannis Giannopoulos - Unsupervised Clustering of Eye Tracking Data / Fabian Göbel and Henry Martin - Collections of Points of Interest: How to Name Them and Why it Matters / Gengchen Mai, Krzysztof Janowicz, Yingjie Hu, Song Gao, Rui Zhu, Bo Yan, Grant McKenzie, Anagha Uppal, and Blake Regalia PART 3: SPATIAL PATTERNS - A Multi-scale Spatio-temporal Approach to Analysing the changing inequality in the Housing Market during 2001-2014 / Yingyu Feng and Kelvyn Jones - Automated social media content analysis from urban green areas – Case Helsinki / Vuokko Heikinheimo, Henrikki Tenkanen, Tuomo Hiippala, Olle Järv, and Tuuli Toivonen - Long short-term memory networks for county-level corn yield estimation / Haifeng Li, Yudi Wang, Renhai Zhong, Hao Jiang, and Tao Lin - Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering / Torben Peters and Claus Brenner Numéro de notice : 17546 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Actes En ligne : http://spatialbigdata.ethz.ch/index.php/proceedings/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91338

Contient

• Convolutional neural network for traffic signal inference based on GPS traces / Yann Méneroux (2018) 

Documents numériques

en open access Spatial big data and machine learning in GIScience 2018 - pdf éditeur Adobe Acrobat PDF

Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn / R. Ahas in International journal of geographical information science IJGIS, vol 29 n° 11 (November 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 11 (November 2015) . - pp 2017 - 2039 Titre : Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn Type de document : Article/Communication Auteurs : R. Ahas, Auteur ; Y. Yuan, Auteur ; Martin Raubal, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 2017 - 2039 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] capteur non-imageur [Termes IGN] données localisées des bénévoles [Termes IGN] surveillance de l'urbanisation [Termes IGN] téléphonie mobile Résumé : (Auteur) This paper proposes a methodology for using mobile telephone-based sensor data for detecting spatial and temporal differences in everyday activities in cities. Mobile telephone-based sensor data has great applicability in developing urban monitoring tools and smart city solutions. The paper outlines methods for delineating indicator points of temporal events referenced as ‘midnight’, ‘morning start’, ‘midday’, and ‘duration of day’, which represent the mobile telephone usage of residents (what we call social time) rather than solar or standard time. Density maps by time quartiles were also utilized to test the versatility of this methodology and to analyze the spatial differences in cities. The methodology was tested with data from cities of Harbin (China), Paris (France), and Tallinn (Estonia). Results show that the developed methods have potential for measuring the distribution of temporal activities in cities and monitoring urban changes with georeferenced mobile phone data. Numéro de notice : A2015-618 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1063151 En ligne : https://doi.org/10.1080/13658816.2015.1063151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78087 [article]

Where am I? Investigating map matching during self-localization with mobile eye tracking in an urban environment / Peter Kiefer in Transactions in GIS, vol 18 n° 5 (October 2014)  

Public [article]  inTransactions in GIS > vol 18 n° 5 (October 2014) . - pp 660 – 686 Titre : Where am I? Investigating map matching during self-localization with mobile eye tracking in an urban environment Type de document : Article/Communication Auteurs : Peter Kiefer, Auteur ; Ioannis Giannopoulos, Auteur ; Martin Raubal, Auteur Année de publication : 2014 Article en page(s) : pp 660 – 686 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] géolocalisation [Termes IGN] géopositionnement [Termes IGN] sémiologie graphique [Termes IGN] signe conventionnel Résumé : (Auteur) Self-localization is the process of identifying one's current position on a map, and it is a crucial part of any wayfinding process. During self-localization the wayfinder matches visually perceptible features of the environment, such as landmarks, with map symbols to constrain potential locations on the map. The success of this visual matching process constitutes an important factor for the success of self-localization. In this research we aim at observing the visual matching process between environment and map during self-localization with real-world mobile eye tracking. We report on one orientation and one self-localization experiment, both in an outdoor urban environment. The gaze data collected during the experiments show that successful participants put significantly more visual attention to those symbols on the map that were helpful in the given situation than unsuccessful participants. A sequence analysis revealed that they also had significantly more switches of visual attention between map symbols and their corresponding landmarks in the environment, which suggests they were following a more effective self-localization strategy. Numéro de notice : A2014-509 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12067 Date de publication en ligne : 27/10/2013 En ligne : https://doi.org/10.1111/tgis.12067 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74108 [article]

An indoor routing algorithm for the blind: development and comparison to a routing algorithm for the sighted / M. Swobodzinski in International journal of geographical information science IJGIS, vol 23 n°9-10 (september 2009)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 23 n°9-10 (september 2009) . - pp 1315 - 1343 Titre : An indoor routing algorithm for the blind: development and comparison to a routing algorithm for the sighted Type de document : Article/Communication Auteurs : M. Swobodzinski, Auteur ; Martin Raubal, Auteur Année de publication : 2009 Article en page(s) : pp 1315 - 1343 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] analyse comparative [Termes IGN] navigation [Termes IGN] personne malvoyante [Termes IGN] positionnement en intérieur [Termes IGN] prototype Résumé : (Auteur) This paper presents a prototypical implementation of a non-network-based indoor routing algorithm for the sighted and the blind. The spatial abilities of the visually impaired are discussed. Former approaches of outdoor navigation systems for the blind are analysed and deemed inappropriate for the purpose of modelling indoor navigation. The proposed routing algorithm for the blind calculates routes based on physical characteristics of travelling with a long cane. The algorithm distinguishes between clues, landmarks, obstacles, and hazards along the feasible paths and selects the optimal route by trading off distance and the number of landmarks and clues along a route. Subsequently, the routes for the blind are compared to routes calculated by the routing algorithm for the sighted. The paper asserts that the proposed indoor routing algorithm leads to more suitable routes for the blind. Copyright Taylor & Francis Numéro de notice : A2009-391 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/13658810802421115 En ligne : https://doi.org/10.1080/13658810802421115 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30021 [article]

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Time geography for ad-hoc shared-ride trip planning in mobile geosensor networks / Martin Raubal in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 5 (October 2007)  

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Geographic information science, 4th international conference, GIScience 2006, Münster, Germany, September 2006 / Martin Raubal (2006)  

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Geographic Information Science, Fourth International Conference, GIScience 2006, Münster, Germany, September 2006 / Martin Raubal (2006)

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