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Group diagrams for representing trajectories / Maike Buchin in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2401 - 2433 Titre : Group diagrams for representing trajectories Type de document : Article/Communication Auteurs : Maike Buchin, Auteur ; Bernhard Kilgus, Auteur ; Andrea Kölzsch, Auteur Année de publication : 2020 Article en page(s) : pp 2401 - 2433 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] approximation [Termes descripteurs IGN] diagramme [Termes descripteurs IGN] distance de Fréchet [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] géomètrie algorithmique [Termes descripteurs IGN] itinéraire [Termes descripteurs IGN] migration animale [Termes descripteurs IGN] mouvement [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] trajectoire Résumé : (auteur) Given the trajectories of one or several moving groups, we propose a new framework, the group diagram (GD) for representing these. Specifically, we seek a minimal GD as a concise representation of the groups maintaining the spatio-temporal structure of the groups’ movement. A GD is specified by three input values, namely a distance threshold, a similarity measure and a minimality criterion. For several variants of the GD, we give a comprehensive analysis of their computational complexity and present efficient approximation algorithms for their computation. Furthermore, we experimentally evaluate our algorithms on GPS data of migrating geese. Applying the proposed methods on these data sets reveals how the GD concisely represents the movement of the groups. This representation can be used for further analysis and for the formulation of new hypotheses for further ecological research, such as differences in movement patterns of groups on different surfaces or the shift of migration routes over several years. We use different similarity measures to summarize the migration routes of (i) a goose family for one migration period and to summarize (ii) the migration routes of one individual for several migration periods or (iii) the migration routes of several independent individuals for one migration period. Numéro de notice : A2020-690 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684498 date de publication en ligne : 25/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684498 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96227 [article]

Semantic trajectory segmentation based on change-point detection and ontology / Yuan Gao in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2361 - 2394 Titre : Semantic trajectory segmentation based on change-point detection and ontology Type de document : Article/Communication Auteurs : Yuan Gao, Auteur ; Longfei Huang, Auteur ; Jun Feng, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2361 - 2394 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] cible mobile [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] information sémantique [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] ontologie [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] probabilité [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] trajectoire Résumé : (auteur) Trajectory segmentation is a fundamental issue in GPS trajectory analytics. The task of dividing a raw trajectory into reasonable sub-trajectories and annotating them based on moving subject’s intentions and application domains remains a challenge. This is due to the highly dynamic nature of individuals’ patterns of movement and the complex relationships between such patterns and surrounding points of interest. In this paper, we present a framework called SEMANTIC-SEG for automatic semantic segmentation of trajectories from GPS readings. For the decomposition component of SEMANTIC-SEG, a moving pattern change detection (MPCD) algorithm is proposed to divide the raw trajectory into segments that are homogeneous in their movement conditions. A generic ontology and a spatiotemporal probability model for segmentation are then introduced to implement a bottom-up ontology-based reasoning for semantic enrichment. The experimental results on three real-world datasets show that MPCD can more effectively identify the semantically significant change-points in a pattern of movement than four existing baseline methods. Moreover, experiments are conducted to demonstrate how the proposed SEMANTIC-SEG framework can be applied. Numéro de notice : A2020-689 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1798966 date de publication en ligne : 04/08/2020 En ligne : https://doi.org/10.1080/13658816.2020.1798966 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96226 [article]

Atmospheric pathways and distance range analysis of castanea pollen transport in Southern Spain / Rocio López-Orozco in Forests, vol 11 n° 10 (October 2020)  

Public [article]  inForests > vol 11 n° 10 (October 2020) . - n° 1092 Titre : Atmospheric pathways and distance range analysis of castanea pollen transport in Southern Spain Type de document : Article/Communication Auteurs : Rocio López-Orozco, Auteur ; Miguel Angel Hernández-Ceballos, Auteur ; Carmen Galan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 1092 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Andalousie [Termes descripteurs IGN] Castanea (genre) [Termes descripteurs IGN] circulation atmosphérique [Termes descripteurs IGN] génétique forestière [Termes descripteurs IGN] pollen [Termes descripteurs IGN] trajectoire [Vedettes matières IGN] Sylviculture Résumé : (auteur) The sweet chestnut (Castanea sativa Mill.) is the only native species of this genus in Europe, where it faces various threats that are causing a severe decrease in populations, with the resulting loss of genetic diversity. In the Iberian Peninsula, it is of high economic and ecological importance, being well represented, especially in northern areas, whilst it is limited to isolated populations in medium-range mountains in southern Spain (Andalusia region). Taking advantage of this fragmented distribution, this study analyzes the dynamics of atmospheric transport of Castanea pollen through Andalusia region in order to obtain a better understanding of the pollination pathways as a key aspect of the floral biology of this partially anemophilous species. The aerobiological characteristics of this species are also of special interest since its pollen has been recognized as allergenic. Pollen transport pathways were studied by applying back-trajectories analysis together with aerobiological, phenological, land cover, and meteorological data. The results reveal that airborne Castanea pollen concentrations recorded in the city of Cordoba, in the center of Andalusia region, reach medium- and even long-range distances. The backward-trajectory analysis indicates that most of the pollen data detected outside the Castanea flowering season were related to westerly slow and easterly airflows. Furthermore, some of the case studies analyzed indicate the presence of southerly airflow patterns, which could influence medium- and long-range transport events from chestnut populations further south, even from those located in north African mountains. The integrated analysis of the results offers us better knowledge of the cross-pollination pathways of this endangered species, which help us to understand its genetic flows, as a basis for designing conservation strategies for this highly fragmented species in southern Spain. Numéro de notice : A2020-755 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f11101092 date de publication en ligne : 14/10/2020 En ligne : https://doi.org/10.3390/f11101092 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96461 [article]

A framework for group converging pattern mining using spatiotemporal trajectories / Bin Zhao in Geoinformatica [en ligne], vol 24 n° 4 (October 2020)  

Public [article]  inGeoinformatica [en ligne] > vol 24 n° 4 (October 2020) . - pp 745 - 776 Titre : A framework for group converging pattern mining using spatiotemporal trajectories Type de document : Article/Communication Auteurs : Bin Zhao, Auteur ; Xintao Liu, Auteur ; Jinping Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 745 - 776 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] base de données spatiotemporelles [Termes descripteurs IGN] comportement [Termes descripteurs IGN] convergence [Termes descripteurs IGN] exploration de données géographiques [Termes descripteurs IGN] jointure spatiale [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] reconnaissance de formes [Termes descripteurs IGN] trajectoire Résumé : (Auteur) A group event such as human and traffic congestion can be very roughly divided into three stages: converging stage before congestion, gathered stage when congestion happens, and dispersing stage that congestion disappears. It is of great interest in modeling and identifying converging behaviors before gathered events actually happen, which helps to proactively predict and handle potential public incidents such as serious stampedes. However, most of existing literature put too much emphasis on the second stage, only a few of them is dedicated to the first stage. In this paper, we propose a novel group pattern, namely converging, which refers to a group of moving objects converging from different directions during a certain period before gathered. To discover efficiently such converging patterns, we develop a framework for converging pattern mining (CPM) by examining how moving objects form clusters and the process of the “cluster containment”. The framework consists of three phases: snapshot cluster discovery phase, cluster containment join phase, and converging detection phase. As cluster containment mining is the key step, we develop three algorithms to discover cluster containment matches: a containment-join-algorithm, called SSCCJ, by using spatial proximity; a signature tree-based cluster-containment-join-algorithm, called STCCJ, which takes advantage of the cluster containment relations and signature techniques to filter enormous unqualified candidates in an efficient and effective way; and third, to keep the advantages of the above algorithms while avoiding their flaws, we further propose a signature quad-tree based cluster-containment-join algorithm, called SQTCCJ, which can identify efficiently matches by considering cluster spatial proximity as well as containment relations simultaneously. To assess the proposed methods, we redefine two evaluation metrics based on the concept of “Precision and Recall” in the field of information retrieval and the characteristics of converging patterns. We also propose a new indicator for measuring the duration of the converging stage in a group event. Finally, the effectiveness of the CPM and the efficiency of the mining algorithms are evaluated using three types of trajectory datasets, and the results show that the SQTCCJ algorithm demonstrates a superior performance. Numéro de notice : A2020-494 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00404-z date de publication en ligne : 25/04/2020 En ligne : https://doi.org/10.1007/s10707-020-00404-z Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96114 [article]

From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity / Elham Naghizade in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 10 (October 2020) . - pp 2004 - 2029 Titre : From small sets of GPS trajectories to detailed movement profiles: quantifying personalized trip-dependent movement diversity Type de document : Article/Communication Auteurs : Elham Naghizade, Auteur ; jeffrey Chan, Auteur ; Martin Tomko, Auteur Année de publication : 2020 Article en page(s) : pp 2004 - 2029 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] comportement [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] gestion de trafic [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] mouvement [Termes descripteurs IGN] origine - destination [Termes descripteurs IGN] trajectoire [Termes descripteurs IGN] trajet [Termes descripteurs IGN] voyage Résumé : (auteur) The ubiquity of personal sensing devices has enabled the collection of large, diverse, and fine-grained spatio-temporal datasets. These datasets facilitate numerous applications from traffic monitoring and management to location-based services. Recently, there has been an increasing interest in profiling individuals' movements for personalized services based on fine-grained trajectory data. Most approaches identify the most representative paths of a user by analyzing coarse location information, e.g., frequently visited places. However, even for trips that share the same origin and destination, individuals exhibit a variety of behaviors (e.g., a school drop detour, a brief stop at a supermarket). The ability to characterize and compare the variability of individuals' fine-grained movement behavior can greatly support location-based services and smart spatial sampling strategies. We propose a TRip DIversity Measure --TRIM – that quantifies the regularity of users' path choice between an origin and destination. TRIM effectively captures the extent of the diversity of the paths that are taken between a given origin and destination pair, and identifies users with distinct movement patterns, while facilitating the comparison of the movement behavior variations between users. Our experiments using synthetic and real datasets and across geographies show the effectiveness of our method. Numéro de notice : A2020-512 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1730849 date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1080/13658816.2020.1730849 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95666 [article]

Network-constrained bivariate clustering method for detecting urban black holes and volcanoes / Qiliang Liu in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

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Improving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations / Guanxu Chen in Journal of geodesy, vol 94 n° 6 (June 2020)  

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Improved kinematic precise point positioning performance with the use of map constraints / Emerson Pereira Cavalheri in Journal of applied geodesy, vol 14 n° 2 (April 2020)  

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Postprocessing synchronization of a laser scanning system aboard a UAV / Marcela do Valle Machado in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 10 (October 2019)  

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Relative space-based GIS data model to analyze the group dynamics of moving objects / Mingxiang Feng in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)  

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BIM-Tracker: A model-based visual tracking approach for indoor localisation using a 3D building model / Debaditya Acharya in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

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A methodology with a distributed algorithm for large-scale trajectory distribution prediction / QiuLei Guo in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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Global observations of ocean surface winds and waves using spaceborne synthetic aperture radar measurements / Huimin Li (2019)  

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Recalage conjoint de données de cartographie mobile et de modèles 3D de bâtiments / Miloud Mezian (2019)  

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A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks / Lin Wan in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)  

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