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Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records / Zhang Liu in Transactions in GIS, vol 22 n° 2 (April 2018)
[article]
Titre : Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records Type de document : Article/Communication Auteurs : Zhang Liu, Auteur ; Ting Ma, Auteur ; Yunyan Du, Auteur ; Tao Pei, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 494 - 513 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] carte thématique
[Termes IGN] cartographie des flux
[Termes IGN] classification par réseau neuronal
[Termes IGN] mobilité urbaine
[Termes IGN] population urbaine
[Termes IGN] régression
[Termes IGN] téléphone intelligent
[Termes IGN] trace numérique
[Termes IGN] trajet (mobilité)Résumé : (Auteur) Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation. Numéro de notice : A2018-215 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12323 Date de publication en ligne : 26/02/2018 En ligne : https://doi.org/10.1111/tgis.12323 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90006
in Transactions in GIS > vol 22 n° 2 (April 2018) . - pp 494 - 513[article]Multilevel visualization of travelogue trajectory data / Yongsai Ma in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)
[article]
Titre : Multilevel visualization of travelogue trajectory data Type de document : Article/Communication Auteurs : Yongsai Ma, Auteur ; Yang Wang, Auteur ; Guangluan Xu, Auteur ; Xianqing Tai, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] récit
[Termes IGN] trajet (mobilité)
[Termes IGN] visualisation de données
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) User-generated travelogues can generate much geographic data, containing abundant semantic and geographic information that reflects people’s movement patterns. The tourist movement patterns in travelogues can help others when planning trips, or understanding how people travel within certain regions. The trajectory data in travelogues might include tourist attractions, restaurants and other locations. In addition, all travelogues generate a trajectory, which has a large volume. The variety and volume of trajectory data make it very hard to directly find patterns contained within them. Moreover, existing work about movement patterns has only explored the simple semantic information, without considering using visualization to find hidden information. We propose a multilevel visual analytical method to help find movement patterns in travelogues. The data characteristic of a single travelogue are different from multiple travelogues. When exploring a single travelogue, the individual movement patterns comprise our main concern, like semantic information. While looking at many travelogues, we focus more on the patterns of population movement. In addition, when choosing the levels for multilevel aggregation, we apply an adaptive method. By combining the multilevel visualization in a single travelogue and multiple travelogues, we can better explore the movement patterns in travelogues. Numéro de notice : A2018-042 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7010012 En ligne : https://doi.org/10.3390/ijgi7010012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89265
in ISPRS International journal of geo-information > vol 7 n° 1 (January 2018)[article]Unveiling movement uncertainty for robust trajectory similarity analysis / Andre Salvaro Furtado in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)
[article]
Titre : Unveiling movement uncertainty for robust trajectory similarity analysis Type de document : Article/Communication Auteurs : Andre Salvaro Furtado, Auteur ; Luis Otavio Alvares, Auteur ; Nikos Pelekis, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 140 - 168 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] distance
[Termes IGN] données localisées
[Termes IGN] incertitude des données
[Termes IGN] mesure de similitude multidimensionnelle
[Termes IGN] méthode robuste
[Termes IGN] trace GPS
[Termes IGN] trajet (mobilité)Résumé : (Auteur) Trajectory data analysis and mining require distance and similarity measures, and the quality of their results is directly related to those measures. Several similarity measures originally proposed for time-series were adapted to work with trajectory data, but these approaches were developed for well-behaved data that usually do not have the uncertainty and heterogeneity introduced by the sampling process to obtain trajectories. More recently, similarity measures were proposed specifically for trajectory data, but they rely on simplistic movement uncertainty representations, such as linear interpolation. In this article, we propose a new distance function, and a new similarity measure that uses an elliptical representation of trajectories, being more robust to the movement uncertainty caused by the sampling rate and the heterogeneity of this kind of data. Experiments using real data show that our proposal is more accurate and robust than related work. Numéro de notice : A2018-023 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1372763 En ligne : https://doi.org/10.1080/13658816.2017.1372763 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89175
in International journal of geographical information science IJGIS > vol 32 n° 1-2 (January - February 2018) . - pp 140 - 168[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018011 RAB Revue Centre de documentation En réserve L003 Disponible An analysis of movement patterns between zones using taxi GPS data / Zhanlong Chen in Transactions in GIS, vol 21 n° 6 (December 2017)
[article]
Titre : An analysis of movement patterns between zones using taxi GPS data Type de document : Article/Communication Auteurs : Zhanlong Chen, Auteur ; Xi Gong, Auteur ; Zhong Xie, Auteur Année de publication : 2017 Article en page(s) : pp 1341 - 1363 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] modèle numérique
[Termes IGN] Pékin (Chine)
[Termes IGN] trace GPS
[Termes IGN] trajectographie par GPS
[Termes IGN] trajet (mobilité)
[Termes IGN] urbanisme
[Termes IGN] véhicule automobile
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) The discovery of zones and people's movement patterns supports a better understanding of modern cities and enables a more comprehensive strategy for urban planning. This article proposes a modified method based on previous research to simultaneously discover people's zones and movement patterns, called movement patterns between functional zones (MPFZ). The method attempts to take full advantage of taxi GPS data to identify MPFZs by merging the movement traces satisfying the merging conditions. Considering movement directions, movement numbers and the adjacent constraints that consist of spatial relationship and attribute features, the merging conditions limit the movement traces to be merged. The new MPFZs are discovered by an iteration process and are measured by the following three evaluation indices: v‐value, a‐value and c‐value, which represent coverage, accuracy and their trade‐off. Using a real‐world taxi dataset of Beijing, 24 new MPFZs are discovered, which have higher v‐, a‐ and c‐values than the unmerged MPFZs. The results of the real‐world dataset experiment show that the proposed approach is effective and efficient. The proposed method can also be applied to other types of transportation data and regions by adjusting the dataset utilized and controlling the iteration process. Numéro de notice : A2017-839 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12281 Date de publication en ligne : 07/08/2017 En ligne : https://doi.org/10.1111/tgis.12281 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89375
in Transactions in GIS > vol 21 n° 6 (December 2017) . - pp 1341 - 1363[article]Extracting spatial patterns in bicycle routes from crowdsourced data / Jody Sultan in Transactions in GIS, vol 21 n° 6 (December 2017)
[article]
Titre : Extracting spatial patterns in bicycle routes from crowdsourced data Type de document : Article/Communication Auteurs : Jody Sultan, Auteur ; Gev Ben‐Haim, Auteur ; Jan‐Henrik Haunert, Auteur ; Sagi Dalyot, Auteur Année de publication : 2017 Article en page(s) : pp 1321 - 1340 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Amsterdam (Pays-Bas)
[Termes IGN] cycliste
[Termes IGN] données localisées des bénévoles
[Termes IGN] extraction de modèle
[Termes IGN] trace GPS
[Termes IGN] trajet (mobilité)Résumé : (auteur) Much is done nowadays to provide cyclists with safe and sustainable road infrastructure. Its development requires the investigation of road usage and interactions between traffic commuters. This article is focused on exploiting crowdsourced user‐generated data, namely GPS trajectories collected by cyclists and road network infrastructure generated by citizens, to extract and analyze spatial patterns and road‐type use of cyclists in urban environments. Since user‐generated data shows data‐deficiencies, we introduce tailored spatial data‐handling processes for which several algorithms are developed and implemented. These include data filtering and segmentation, map‐matching and spatial arrangement of GPS trajectories with the road network. A spatial analysis and a characterization of road‐type use are then carried out to investigate and identify specific spatial patterns of cycle routes. The proposed analysis was applied to the cities of Amsterdam (The Netherlands) and Osnabrück (Germany), proving its feasibility and reliability in mining road‐type use and extracting pattern information and preferences. This information can help users who wish to explore friendlier and more interesting cycle patterns, based on collective usage, as well as city planners and transportation experts wishing to pinpoint areas most in need of further development and planning. Numéro de notice : A2017-838 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12280 Date de publication en ligne : 06/06/2017 En ligne : https://doi.org/10.1111/tgis.12280 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89374
in Transactions in GIS > vol 21 n° 6 (December 2017) . - pp 1321 - 1340[article]Apports et limites des données passives de la téléphonie mobile pour la construction de matrices origine-destination / Patrick Bonnel in Revue d'économie régionale et urbaine, vol 2017 n° 4 (2017-4)PermalinkPermalinkSimultaneous detection and tracking of pedestrian from panoramic laser scanning data / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)PermalinkA 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)PermalinkTrajectory Box Plot: a new pattern to summarize movements / Laurent Etienne in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkMultidimensional Similarity Measuring for Semantic Trajectories / Andre Salvaro Furtado in Transactions in GIS, vol 20 n° 2 (April 2016)PermalinkEuropean handbook of crowdsourced geographic information, ch. 12. Gaining knowledge from georeferenced social media data with visual analytics / Gennady Andrienko (2016)PermalinkT-Warehousing for hazardous materials transportation / A. Boulmakoul in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 21 n° 1 (janvier - février 2016)PermalinkPoints of interest recommendation from GPS trajectories / Yaqiong Liu in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)PermalinkVisualization techniques for journey to crime flow data / Andrew Wheeler in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)PermalinkPassive mobile phone dataset to construct origin-destination matrix: Potentials and limitations / Patrick Bonnel in Transportation Research Procedia, vol 11 (2015)PermalinkLe Paris des visiteurs étrangers, qu'en disent les téléphones mobiles ? Inférence des pratiques spatiales et fréquentations des sites touristiques en Île-de-France / Ana-Maria Olteanu-Raimond in Revue internationale de géomatique, vol 22 n° 3 (septembre - novembre 2012)PermalinkVers une cartographie des trajectoires des communautés récifales en réponse aux perturbations : approche du blanchiment coralien sur l'île de la Réunion / G. Pennober in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)PermalinkBuilding agent-based walking models by machine-learning on diverse databases of space-time trajectory samples / Paul M. Torrens in Transactions in GIS, vol 15 supplement s1 (July 2011)PermalinkWeka-STPM: a software architecture and prototype for semantic trajectory data mining and visualization / Vania Bogorny in Transactions in GIS, vol 15 n° 2 (April 2011)PermalinkAutomatic detection and tracking of pedestrians from a moving stereo rig / Konrad Schindler in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 6 (November - December 2010)PermalinkAn integrated approach for visual analysis of a multisource moving objects knowledge base / N. Wllems in International journal of geographical information science IJGIS, vol 24 n° 10 (october 2010)PermalinkL'animation cartographique pour la représentation de trajectoires : Propositions et perspectives / L. Ravenel in Le monde des cartes, n° 205 (septembre 2010)PermalinkConstrained free space diagrams: a tool for trajectory analysis / Kevin Buchin in International journal of geographical information science IJGIS, vol 24 n°7-8 (july 2010)PermalinkIndoor routing for individuals with special needs and preferences / Hassan A. Karimi in Transactions in GIS, vol 14 n° 3 (June 2010)Permalink