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Titre : Visual analytics of human mobility behavior Type de document : Thèse/HDR Auteurs : Robert Lutz Krüger, Auteur ; Thomas Ertl, Directeur de thèse ; Ross Maciejewski, Directeur de thèse Editeur : Stuttgart : University of Stuttgart Année de publication : 2017 Importance : 212 p. Format : 21 x 30 cm Note générale : Bibliographie
Von der Fakultät Informatik, Elektrotechnik und Informationstechnik der Universität Stuttgart zur Erlangung der Würde eines Doktors der Naturwissenschaften (Dr. rer. nat.), genehmigte AbhandlungLangues : Anglais (eng) Descripteur : [Termes IGN] acquisition de données
[Termes IGN] analyse visuelle
[Termes IGN] base de données localisées
[Termes IGN] comportement
[Termes IGN] données de terrain
[Termes IGN] données socio-économiques
[Termes IGN] enrichissement sémantique
[Termes IGN] exploration de données géographiques
[Termes IGN] mobilité humaine
[Termes IGN] modélisation
[Termes IGN] trajet (mobilité)
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Human mobility plays an important role in many domains of today’s society, such as security, logistics, transportation, urban planning, and geo-marketing. Both, government and industry thus have great interest in understanding mobility patterns and their driving social, economical, and environmental causes and effects. While
stakeholders had to rely on manual traffic surveys for a long time, improvements in tracking technology made analyses based on large digital datasets possible. Recently, the omnipresence of mobile devices significantly increased the amounts of collected movement and context data. People are willing to reveal their position, but also further personal details such as visited places, observations, events, news, and sentiments in exchange for personalized services and social networking. This opens up new possibilities for many domains where a semantic mobility understanding is required but also raises major challenges. To reveal a holistic picture, heterogeneous datasets of different services with different resolution and format have to be fused and analyzed. However, social sensing data is vast, has varying scale, is unevenly distributed, and constantly updated. Especially content from social media services is often inconsistent, unreliable, and incomplete, which requires special treatment. Fully automatic mapping approaches are not trustworthy as they do not take into account these uncertainties. At the same time, manual approaches become insufficient with large amounts of data. Even when data is perfectly aligned, analysts cannot purely rely on existing techniques. Answering questions about reasons for movement requires a broader perspective that takes into account environmental and social context, the driving forces for human mobility behavior. Visual analytics is an emerging research field to tackle such challenges. It creates added value by combining the processing power and accuracy of machines with human capabilities to perceive information visually. Automatic means are used to fuse and aggregate data and to detect hidden patterns therein. Interactive visualizations allow to explore and query the data and to steer the automatic processes with domain knowledge. This increases trust in data, models, and results, which is especially important when critical decisions need to be made. The strengths of visual analytics have been shown to be particularly advantageous when problems and goals are underspecified and exploratory means are needed to discover yet unknown patterns.
This thesis presents novel visual analytics approaches to derive meaning and reasons behind movement, by taking into account the aforementioned characteristics. The approaches are aligned in a holistic process model covering all steps from data retrieval, enrichment, exploration, and verification to externalization of gained knowledge for various fields of application such as electric mobility, event management, and law enforcement. It is shown how data from social media can not only be used to retrieve up-to-date movement information, but also to enrich movement trajectories from other sources with structured and unstructured information about places, events, transactions, and other observations. Through highly interactive visual interfaces analysts can bring in domain knowledge to deal with uncertainties during data fusion and to steer the subsequent semantic analysis. Exploratory and confirmatory analysis techniques are presented to create hypotheses, refine them, and find support in the data. Analysts can discover routines and abnormal behavior with assistance of automatic pattern detection methods to cope with the vast amounts of data. Spatial drill-down is supported by a set-based focus+context technique, while a more abstract visual query language allows to explicitly formulate, extract, and query for movement patterns. The approaches are applied in different scenarios and are integrated in a visual analytics system. Evaluation with experts and novice users, case studies, and comparisons to ground truth data reveal the need and effectiveness of the contributions. Overall, the thesis contributes a visual analytics process for human mobility behavior with novel semantic analysis approaches, ranging from global movements of many to local activities of a few people, for a wide range of application domains.Note de contenu : Introduction
1 - From Foundations to Applications
2 - Movement Data Retrieval and Visual Representation
3 - Semantic Enrichment with Context Data
4 - Interactive Filtering
5 - Pattern Detection and Verification
6 - MOBY - The Mobility Analysis System
Conclusion and OutlookNuméro de notice : 21573 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : PhD Dissertation : Informatik, Elektrotechnik und Informationstechnik : Universität Stuttgart : 2017 DOI : sans En ligne : http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-97337 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90574 A probabilistic approach to detect mixed periodic patterns from moving object data / Jun Li in Geoinformatica, vol 20 n° 4 (October - December 2016)
[article]
Titre : A probabilistic approach to detect mixed periodic patterns from moving object data Type de document : Article/Communication Auteurs : Jun Li, Auteur ; Jingjing Wang, Auteur ; Junfei Zhang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 715 - 739 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] comportement
[Termes IGN] détection automatique
[Termes IGN] détection d'objet
[Termes IGN] estimation par noyau
[Termes IGN] objet mobile
[Termes IGN] séquence d'images
[Termes IGN] variable aléatoireRésumé : (Auteur) The prevalence of moving object data (MOD) brings new opportunities for behavior related research. Periodic behavior is one of the most important behaviors of moving objects. However, the existing methods of detecting periodicities assume a moving object either does not have any periodic behavior at all or just has a single periodic behavior in one place. Thus they are incapable of dealing with many real world situations whereby a moving object may have multiple periodic behaviors mixed together. Aiming at addressing this problem, this paper proposes a probabilistic periodicity detection method called MPDA. MPDA first identifies high dense regions by the kernel density method, then generates revisit time sequences based on the dense regions, and at last adopts a filter-refine paradigm to detect mixed periodicities. At the filter stage, candidate periods are identified by comparing the observed and reference distribution of revisit time intervals using the chi-square test, and at the refine stage, a periodic degree measure is defined to examine the significance of candidate periods to identify accurate periods existing in MOD. Synthetic datasets with various characteristics and two real world tracking datasets validate the effectiveness of MPDA under various scenarios. MPDA has the potential to play an important role in analyzing complicated behaviors of moving objects. Numéro de notice : A2016-814 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s10707-016-0261-2 En ligne : http://dx.doi.org/10.1007/s10707-016-0261-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82615
in Geoinformatica > vol 20 n° 4 (October - December 2016) . - pp 715 - 739[article]Integrating social network data into GISystems / Clio Andris in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
[article]
Titre : Integrating social network data into GISystems Type de document : Article/Communication Auteurs : Clio Andris, Auteur Année de publication : 2016 Article en page(s) : pp 2009 - 2031 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] classe d'objets
[Termes IGN] comportement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] service fondé sur la positionRésumé : (Auteur) Today, online social media outlets provide new and plentiful sources of data on social networks (SNs) and location-based social networks (LBSNs), i.e., geolocated evidence of connections between individuals. While SNs have been used to show how the magnitude of social connectivity decreases with distance, there are few examples of how to include SNs as layers in a GISystem. If SNs, and thus, interpersonal relationships, could be analyzed in a geographic information system (GIS) setting, we could better model how humans socialize, share information, and form social groups within the complex geographic landscape.
Our goal is to facilitate a guide for analyzing SNs (as derived from online social media, telecommunications, surveys, etc.) within geographic space by combining the mature fields of social network analysis (SNA) and GISystems. First, we describe why modeling socialization in geographic space is essential for understanding human behavior. We then outline best practices and techniques for embedding SN nodes and edges in GISystems by introducing terms like ‘social flow’ and ‘anthrospace’, and categorizations for data and spatial aggregation types. Finally, we explore case study vignettes of SNA within GISystems from diverse regions located in Bolivia, China, Côte d’Ivoire, Singapore, the United Kingdom, and the United States, using concepts such as geolocated dyads, ego–alter relationships, node feature roles, modularity, and network transitivity.Numéro de notice : A2016-574 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1153103 En ligne : http://dx.doi.org/10.1080/13658816.2016.1153103 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81730
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 2009 - 2031[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Managing real-time information within BIM-based processes for assessing building behaviours in operation / Daniela Pasini in International journal of 3-D information modeling, vol 5 n° 4 (October - December 2016)
[article]
Titre : Managing real-time information within BIM-based processes for assessing building behaviours in operation Type de document : Article/Communication Auteurs : Daniela Pasini, Auteur ; Angelo Luigi Camillo Ciribini, Auteur ; Bruno Daniotti, Auteur Année de publication : 2016 Article en page(s) : pp 25 - 38 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] comportement
[Termes IGN] format d'échange
[Termes IGN] format Industry foudation classes IFC
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] surveillance d'ouvrage
[Termes IGN] télémétrie laser terrestre
[Termes IGN] temps réelRésumé : (auteur) Considering the remarkable shift that the digitalisation is nowadays bringing about in the building sector, the paper focuses on how the great amount of data collected around assets is changing the way buildings are operated, particularly for what concerns innovation on products, processes and technologies. By establishing a connection between as-designed virtual models and as-delivered physical assets, the paper presents methods and tools based on information management and developed for assessing building behaviours in operation and for defining control strategies for satisfying user needs. The research aims to investigate how the building process could benefit from the availability of multi-faceted information collected in real time (e.g. through sensors) during the operational stages of buildings. Digitally-enabled practices and technologies have been developed and tested for improving a data-driven asset management, by enriching Building Information Models through data gathered through Building Management Systems, according to the Industry Foundation Classes schema. Numéro de notice : A2016-148 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.4018/IJ3DIM.2016100103 En ligne : https://doi.org/10.4018/IJ3DIM.2016100103 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85916
in International journal of 3-D information modeling > vol 5 n° 4 (October - December 2016) . - pp 25 - 38[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 138-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Analysis of human mobility patterns from GPS trajectories and contextual information / Katarzyna Siła-Nowicka in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)
[article]
Titre : Analysis of human mobility patterns from GPS trajectories and contextual information Type de document : Article/Communication Auteurs : Katarzyna Siła-Nowicka, Auteur ; Jan Vandrol, Auteur ; Taylor Oshan, Auteur Année de publication : 2016 Article en page(s) : pp 881 - 906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] comportement
[Termes IGN] données localisées des bénévoles
[Termes IGN] exploration de données
[Termes IGN] itinéraire
[Termes IGN] milieu urbain
[Termes IGN] mobilité humaine
[Termes IGN] modèle numérique
[Termes IGN] plan de déplacement urbain
[Termes IGN] positionnement par GPS
[Termes IGN] prise en compte du contexte
[Termes IGN] segmentation dynamiqueRésumé : (Auteur) Human mobility is important for understanding the evolution of size and structure of urban areas, the spatial distribution of facilities, and the provision of transportation services. Until recently, exploring human mobility in detail was challenging because data collection methods consisted of cumbersome manual travel surveys, space-time diaries, or interviews. The development of location-aware sensors has significantly altered the possibilities for acquiring detailed data on human movements. Although this has spurred many methodological developments in identifying human movement patterns, many of these methods operate solely from the analytical perspective and ignore the environmental context within which the movement takes place. In this paper, we attempt to widen this view and present an integrated approach to the analysis of human mobility using a combination of volunteered GPS trajectories and contextual spatial information. We propose a new framework for the identification of dynamic (travel modes) and static (significant places) behaviour using trajectory segmentation, data mining, and spatio-temporal analysis. We are interested in examining if and how travel modes depend on the residential location, age, or gender of the tracked individuals. Further, we explore theorised ‘third places’, which are spaces beyond main locations (home/work) where individuals spend time to socialise. Can these places be identified from GPS traces? We evaluate our framework using a collection of trajectories from 205 volunteers linked to contextual spatial information on the types of places visited and the transport routes they use. The result of this study is a contextually enriched data set that supports new possibilities for modelling human movement behaviour. Numéro de notice : A2016-288 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1100731 En ligne : https://doi.org/10.1080/13658816.2015.1100731 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80867
in International journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 881 - 906[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 new method for discovering behavior patterns among animal movements / Yuwei Wang in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkExploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper) / Ran Wang in Geoinformatica, vol 20 n° 2 (April - June 2016)PermalinkTowards sustainable mobility behavior: research challenges for location-aware information and communication technology / Paul Weiser in Geoinformatica, vol 20 n° 2 (April - June 2016)PermalinkPersonal mobility pattern mining and anomaly detection in the GPS era / Dong-He Shih in Cartography and Geographic Information Science, Vol 43 n° 1 (January 2016)PermalinkTowards process validation for complex transport models: A sensitivity analysis of a social network-enhanced activity-travel model / Nicole Ronald in Computers, Environment and Urban Systems, vol 55 (January 2016)PermalinkMéthodes de recherche empirique en ingénierie des SI. Principes et applications / Saïd Assar in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 20 n° 6 (novembre - décembre 2015)PermalinkLinking ecosystem services and human-values theory / Christina C. Hicks in Conservation biology, vol 29 n° 5 (October 2015)PermalinkAnalyse du comportement d’annotation du réseau social d’un utilisateur pour la détection des intérêts. Application sur Delicious / Manel Mezghani in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 20 n° 4 (juillet - août 2015)PermalinkEnjeux et problématiques de conception d’un jeu sérieux pour la prise de décision / Thomas Constant in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 20 n° 1 (janvier - février 2015)PermalinkA Feasibility study on occupants' behaviour and energy usage patterns and its potential integration with building information modelling / Liangxiu Han in International journal of 3-D information modeling, vol 4 n° 1 (January - March 2015)Permalink