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Auteur Shih-Lung Shaw |
Documents disponibles écrits par cet auteur (7)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesRelative 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)
Titre : Relative space-based GIS data model to analyze the group dynamics of moving objects Type de document : Article/Communication Auteurs : Mingxiang Feng, Auteur ; Shih-Lung Shaw, Auteur ; Zhixiang Fang, Auteur ; Hao Cheng, Auteur Année de publication : 2019 Article en page(s) : pp 74 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] analyse spatio-temporelle
[Termes IGN] base de données d'objets mobiles
[Termes IGN] base de données orientée objet
[Termes IGN] modèle conceptuel de données
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] SIG dynamique
[Termes IGN] UMLRésumé : (Auteur) The relative motion of moving objects is an essential research topic in geographical information science (GIScience), which supports the innovation of geodatabases, spatial indexing, and geospatial services. This analysis is very popular in the domains of urban governance, transportation engineering, logistics and geospatial information services for individuals or industrials. Importantly, data models of moving objects are one of the most crucial approaches to support the analysis for dynamic relative motion between moving objects, even in the age of big data and cloud computing. Traditional geographic information systems (GIS) usually organize moving objects as point objects in absolute coordinated space. The derivation of relative motions among moving objects is not efficient because of the additional geo-computation of transformation between absolute space and relative space. Therefore, current GISs require an innovative approach to directly store, analyze and interpret the relative relationships of moving objects to support their efficient analysis. This paper proposes a relative space-based GIS data model of moving objects (RSMO) to construct, operate and analyze moving objects’ relationships and introduces two algorithms (relationship querying and relative relationship dynamic pattern matching) to derive and analyze the dynamic relationships of moving objects. Three scenarios (epidemic spreading, tracker finding, and motion-trend derivation of nearby crowds) are implemented to demonstrate the feasibility of the proposed model. The experimental results indicates the execution times of the proposed model are approximately 5–50% those of the absolute GIS method for the same function of these three scenarios. It’s better computational performance of the proposed model when analyzing the relative relationships of moving objects than the absolute methods in a famous commercial GIS software based on this experimental results. The proposed approach fills the gap of traditional GIS and shows promise for relative space-based geo-computation, analysis and service. Numéro de notice : A2019-261 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.002 Date de publication en ligne : 15/05/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.002 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93074
in ISPRS Journal of photogrammetry and remote sensing > vol 153 (July 2019) . - pp 74 - 95[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019071 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019073 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019072 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt
Titre : Fine-grained prediction of urban population using mobile phone location data Type de document : Article/Communication Auteurs : Jie Chen, Auteur ; Shih-Lung Shaw, Auteur ; Feng Lu, Auteur ; Mingxiao Li, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 1770 - 1786 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] classification par réseau neuronal
[Termes IGN] données spatiotemporelles
[Termes IGN] modèle de simulation
[Termes IGN] population urbaine
[Termes IGN] Shanghai (Chine)
[Termes IGN] trace numériqueRésumé : (Auteur) Fine-grained prediction of urban population is of great practical significance in many domains that require temporally and spatially detailed population information. However, fine-grained population modeling has been challenging because the urban population is highly dynamic and its mobility pattern is complex in space and time. In this study, we propose a method to predict the population at a large spatiotemporal scale in a city. This method models the temporal dependency of population by estimating the future inflow population with the current inflow pattern and models the spatial correlation of population using an artificial neural network. With a large dataset of mobile phone locations, the model’s prediction error is low and only increases gradually as the temporal prediction granularity increases, and this model is adaptive to sudden changes in population caused by special events. Numéro de notice : A2018-304 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1460753 Date de publication en ligne : 26/04/2018 En ligne : https://doi.org/10.1080/13658816.2018.1460753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90445
in International journal of geographical information science IJGIS > vol 32 n° 9-10 (September - October 2018) . - pp 1770 - 1786[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2018051 RAB Revue Centre de documentation En réserve L003 Disponible vol 30 n° 9-10 - September - October 2016 - Human dynamics in the mobile and big data era (Bulletin de International journal of geographical information science IJGIS) / Shih-Lung Shaw
Titre : vol 30 n° 9-10 - September - October 2016 - Human dynamics in the mobile and big data era Type de document : Périodique Auteurs : Shih-Lung Shaw, Éditeur scientifique ; Ming-Hsiang Tsou, Éditeur scientifique ; Xinyue Ye, Éditeur scientifique Année de publication : 2016 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatio-temporelle
[Termes IGN] données massives
[Termes IGN] géovisualisation
[Termes IGN] lever mobile
[Termes IGN] mobilité humaine
[Termes IGN] navigation
[Termes IGN] recherche appliquée
[Termes IGN] téléphonie mobileNuméro de notice : 079-201605 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Numéro de périodique En ligne : http://www.tandfonline.com/toc/tgis20/30/9 Format de la ressource électronique : URL Sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=27151 [n° ou bulletin]
- Exploration of spatiotemporal and semantic clusters of Twitter data using unsupervised neural networks / Enrico Steiger in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Understanding the bias of call detail records in human mobility research / Ziliang Zhao in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Measures of transport mode segmentation of trajectories / Adrain C. Prelipcean in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Finding spatial outliers in collective mobility patterns coupled with social ties / Monica Wachowicz in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us? / Qunying Huang in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Discovery of local topics by using latent spatio-temporal relationships in geo-social media / Kyoung-Sook Kim in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- A novel methodology for identifying environmental exposures using GPS data / Andreea Cetateanu in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Modeling spatiotemporal information generation / Simon Scheider in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Integrating social network data into GISystems / Clio Andris in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
- Incorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections? / Paul Holloway in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Understanding the bias of call detail records in human mobility research Type de document : Article/Communication Auteurs : Ziliang Zhao, Auteur ; Shih-Lung Shaw, Auteur ; Yang Xu, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1738 - 1762 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Chine
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données massives
[Termes IGN] erreur systématique
[Termes IGN] mobilité humaine
[Termes IGN] navigation pédestre
[Termes IGN] statistiques d'appels détaillés
[Termes IGN] téléphonie mobileRésumé : (Auteur) In recent years, call detail records (CDRs) have been widely used in human mobility research. Although CDRs are originally collected for billing purposes, the vast amount of digital footprints generated by calling and texting activities provide useful insights into population movement. However, can we fully trust CDRs given the uneven distribution of people’s phone communication activities in space and time? In this article, we investigate this issue using a mobile phone location dataset collected from over one million subscribers in Shanghai, China. It includes CDRs (~27%) plus other cellphone-related logs (e.g., tower pings, cellular handovers) generated in a workday. We extract all CDRs into a separate dataset in order to compare human mobility patterns derived from CDRs vs. from the complete dataset. From an individual perspective, the effectiveness of CDRs in estimating three frequently used mobility indicators is evaluated. We find that CDRs tend to underestimate the total travel distance and the movement entropy, while they can provide a good estimate to the radius of gyration. In addition, we observe that the level of deviation is related to the ratio of CDRs in an individual’s trajectory. From a collective perspective, we compare the outcomes of these two datasets in terms of the distance decay effect and urban community detection. The major differences are closely related to the habit of mobile phone usage in space and time. We believe that the event-triggered nature of CDRs does introduce a certain degree of bias in human mobility research and we suggest that researchers use caution to interpret results derived from CDR data. Numéro de notice : A2016-567 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1137298 En ligne : http://dx.doi.org/10.1080/13658816.2015.1137298 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81710
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1738 - 1762[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Exploring potential human activities in physical and virtual spaces: a spatio-temporal GIS approach Type de document : Article/Communication Auteurs : H. Yu, Auteur ; Shih-Lung Shaw, Auteur Année de publication : 2008 Article en page(s) : pp 409 - 430 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] données spatiotemporelles
[Termes IGN] espace-temps
[Termes IGN] monde virtuel
[Termes IGN] SIG 3D
[Termes IGN] Time-geographyRésumé : (Auteur) Today, the opportunity for potential human activity has gone beyond physical space to virtual space. Based on a proposed conceptual framework that models the relationships between physical and virtual spaces, this paper presents an attempt to adjust the space-time prism concept of Haumlgerstrand's time geography to identify potential activity opportunities in virtual space, focusing on the virtual space access channels available in physical space. A three-dimensional (3D) spatio-temporal Geographic Information System (GIS) design has been developed in this research to accommodate the adjusted space-time prism concept to support the representation, visualization, and analysis of potential human activities and interactions in physical and virtual spaces using the prism representation. Following the design, a prototype system has been successfully implemented in a 3D GIS environment. Such a system can provide powerful analytical tools for studies related to potential human activities and applications such as location-based services (LBS) and accessibility analysis in the information age. Copyright Taylor & Francis Numéro de notice : A2008-147 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810701427569 En ligne : https://doi.org/10.1080/13658810701427569 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29142
in International journal of geographical information science IJGIS > vol 22 n° 4-5 (april 2008) . - pp 409 - 430[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-08031 RAB Revue Centre de documentation En réserve L003 Disponible 079-08032 RAB Revue Centre de documentation En réserve L003 Disponible GIS and remote sensing: research, development and applications, West Palm Beach, Florida, USA, April 26 - 28, 1996, Volume 1. Geoinformatics '96 proceedings / Weihe Guan (1996)
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