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SMSM: a similarity measure for trajectory stops and moves / Andre L. Lehmann in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 33 n° 9 (September 2019) . - pp 1847 - 1872 Titre : SMSM: a similarity measure for trajectory stops and moves Type de document : Article/Communication Auteurs : Andre L. Lehmann, Auteur ; Luis Otavio Alvares, Auteur ; Vania Bogorny, Auteur Année de publication : 2019 Article en page(s) : pp 1847 - 1872 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] calcul d'itinéraire [Termes descripteurs IGN] information sémantique [Termes descripteurs IGN] mesure de similitude [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] relation sémantique [Termes descripteurs IGN] taxi [Termes descripteurs IGN] temps de trajet [Termes descripteurs IGN] trajet Résumé : (auteur) For many years trajectory similarity research has focused on raw trajectories, considering only space and time information. With the trajectory semantic enrichment, emerged the need for similarity measures that support space, time, and semantics. Although some trajectory similarity measures deal with all these dimensions, they consider only stops, ignoring the moves. We claim that, for some applications, the movement between stops is as important as the stops, and they must be considered in the similarity analysis. In this article, we propose SMSM, a novel similarity measure for semantic trajectories that considers both stops and moves. We evaluate SMSM with three trajectory datasets: (i) a synthetic trajectory dataset generated with the Hermoupolis semantic trajectory generator, (ii) a real trajectory dataset from the CRAWDAD project, and (iii) the Geolife dataset. The results show that SMSM overcomes state-of-the-art measures developed either for raw or semantic trajectories. Numéro de notice : A2019-391 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1605074 date de publication en ligne : 24/06/2019 En ligne : https://doi.org/10.1080/13658816.2019.1605074 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93486 [article]

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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)  

Public [article]  inTransactions in GIS > vol 22 n° 2 (April 2018) . - pp 494 - 513 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 descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] carte thématique [Termes descripteurs IGN] cartographie des flux [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] population urbaine [Termes descripteurs IGN] régression [Termes descripteurs IGN] téléphone intelligent [Termes descripteurs IGN] trace numérique [Termes descripteurs IGN] trajet 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 Thématique : GEOMATIQUE 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 [article]

Multilevel visualization of travelogue trajectory data / Yongsai Ma in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 1 (January 2018) 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 descripteurs IGN] récit [Termes descripteurs IGN] trajet [Termes descripteurs IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Résumé : (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 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 [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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 1-2 (January - February 2018) . - pp 140 - 168 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 descripteurs IGN] distance [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] mesure de similitude multidimensionnelle [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] trace GPS [Termes descripteurs IGN] trajet 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 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 [article]

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An analysis of movement patterns between zones using taxi GPS data / Zhanlong Chen in Transactions in GIS, vol 21 n° 6 (December 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 6 (December 2017) . - pp 1341 - 1363 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 descripteurs IGN] modèle numérique [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] trace GPS [Termes descripteurs IGN] trajectographie par GPS [Termes descripteurs IGN] trajet [Termes descripteurs IGN] urbanisme [Termes descripteurs IGN] véhicule automobile [Vedettes matières IGN] Géovisualisation Résumé : (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 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 [article]

Extracting spatial patterns in bicycle routes from crowdsourced data / Jody Sultan in Transactions in GIS, vol 21 n° 6 (December 2017)  

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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)  

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Ship Traffic Simulation to assess noise exposure of whale populations in Canada / Axel Orger (2017) 

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Visual analytics of human mobility behavior / Robert Lutz Krüger (2017) 

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Simultaneous detection and tracking of pedestrian from panoramic laser scanning data / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, III-3 (July 2016)  

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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)  

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Trajectory 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)  

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Multidimensional Similarity Measuring for Semantic Trajectories / Andre Salvaro Furtado in Transactions in GIS, vol 20 n° 2 (April 2016)  

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T-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)  

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Points of interest recommendation from GPS trajectories / Yaqiong Liu in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)  

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