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A GIS representation framework for location-based social media activities / Xuebin Wei in Transactions in GIS, vol 26 n° 3 (May 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 3 (May 2022) . - pp 1444 - 1464 Titre : A GIS representation framework for location-based social media activities Type de document : Article/Communication Auteurs : Xuebin Wei, Auteur ; Xiaobai Yao, Auteur Année de publication : 2022 Article en page(s) : pp 1444 - 1464 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] cadre conceptuel [Termes IGN] données issues des réseaux sociaux [Termes IGN] environnement géographique virtuel [Termes IGN] Facebook [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] ontologie [Termes IGN] relations sociales [Termes IGN] représentation des données [Termes IGN] réseau social géodépendant [Termes IGN] système d'information géographique [Termes IGN] Time-geography Résumé : (auteur) The past couple of decades have witnessed tremendous growth of location-based social media activities (LBSMA) data in virtual spaces, including virtual geographic environments. Such data become innovative resources for the analysis of human activities. Meanwhile, a shift of human interactions from geographical spaces to virtual spaces has been observed. Although this is an exciting research opportunity, it also imposes significant challenges on GIScience, as current GIS representation models are no longer sufficient to handle the increased sophistication of human activities data. This research formalizes an ontology for LBSMA data and a conceptual framework for representing such data in GIS. The framework contributes to GIScience as it enables interconnections of human activities in both the physical and virtual worlds to be represented, organized, retrieved, analyzed, and visualized. The proposed GIS representation model integrates a social dimension into the existing spatial–temporal representation models and allows data analysis in the spatial–temporal–social (STS) dimensions. The research tested this conceptual framework with a prototype and a case study using Facebook data. The prototype and the case study prove that the proposed framework can significantly enhance GIS capabilities for data organization, retrieval, and analysis of LBSMA data in STS dimensions. Numéro de notice : A2022-477 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1111/tgis.12929 Date de publication en ligne : 02/05/2022 En ligne : https://doi.org/10.1111/tgis.12929 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100825 [article]

Reconsidering movement and exposure: Towards a more dynamic health geography / Malcolm Campbell in Geography compass, vol 15 n° 6 (June 2021)  

Public [article]  inGeography compass > vol 15 n° 6 (June 2021) . - n° Titre : Reconsidering movement and exposure: Towards a more dynamic health geography Type de document : Article/Communication Auteurs : Malcolm Campbell, Auteur ; Lukas Marek, Auteur ; Matthew Hobbs, Auteur Année de publication : 2021 Article en page(s) : n° Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] carte statique [Termes IGN] cartographie dynamique [Termes IGN] données [Termes IGN] équipement sanitaire [Termes IGN] géographie sociale [Termes IGN] mobilité humaine [Termes IGN] protection de la vie privée [Termes IGN] Time-geography [Termes IGN] traitement de données Résumé : (auteur) Acknowledging a paucity of emerging research, and some variation by sub-field, the geographical measures of exposure used in health and medical geography have largely stagnated often focusing on residence-based (‘static’) conceptualisations to define an individuals mobility or exposure. Detailed spatiotemporal data, such as smartphone data, allow richer understandings of the influence of the environment, or more broadly of place, on individual health outcomes and behaviours. However, while researchers are increasingly aware of such ‘dynamic’ definitions of place these are seldom employed in empirical evidence. Moreover, there may be differences in mobility by population groups which has not to our knowledge been examined fully. The main aim of this article is to provide a critical review of progress in the conceptualisation of location in health-related geospatial research to understand the evolution of key concepts and to provoke the reader into considering the utility of a (more) dynamic health geography. We explore the origins of time geography, activity spaces, before moving to recent developments in the area of the exposome and the linked dynamic conceptualisations of exposure in health geography. To illuminate and operationalise findings from our review for readers, we provide a small case study to demonstrate how ‘static’ and ‘dynamic’ approaches differ. Moreover, we consider why understanding heterogeneity in mobility could be particularly salient in the field of health geography, and to the discipline of geography more broadly. To conclude, we help readers understand the practical considerations of data privacy, the process of data collection, data processing, and interpretation, and dissemination of findings to offer practical assistance for those who are grappling with ‘dynamic’ definitions of mobility and conceptualisations of exposure. Numéro de notice : A2021-725 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/gec3.12566 Date de publication en ligne : 07/05/2021 En ligne : https://doi.org/10.1111/gec3.12566 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98646 [article]

A graph-based semi-supervised approach to classification learning in digital geographies / Pengyuan Liu in Computers, Environment and Urban Systems, vol 86 (March 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 86 (March 2021) . - n° 101583 Titre : A graph-based semi-supervised approach to classification learning in digital geographies Type de document : Article/Communication Auteurs : Pengyuan Liu, Auteur ; Stefano de Sabbata, Auteur Année de publication : 2021 Article en page(s) : n° 101583 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] apprentissage profond [Termes IGN] approche participative [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification semi-dirigée [Termes IGN] données spatiotemporelles [Termes IGN] partage de données localisées [Termes IGN] prise en compte du contexte [Termes IGN] réseau social [Termes IGN] segmentation sémantique [Termes IGN] Time-geography Résumé : (auteur) As the distinction between online and physical spaces rapidly degrades, social media have now become an integral component of how many people's everyday experiences are mediated. As such, increasing interest has emerged in exploring how the content shared through those online platforms comes to contribute to the collaborative creation of places in physical space at the urban scale. Exploring digital geographies of social media data using methods such as qualitative coding (i.e., content labelling) is a flexible but complex task, commonly limited to small samples due to its impracticality over large datasets. In this paper, we propose a new tool for studies in digital geographies, bridging qualitative and quantitative approaches, able to learn a set of arbitrary labels (qualitative codes) on a small, manually-created sample and apply the same labels on a larger set. We introduce a semi-supervised, deep neural network approach to classify geo-located social media posts based on their textual and image content, as well as geographical and temporal aspects. Our innovative approach is rooted in our understanding of social media posts as augmentations of the time-space configurations that places are, and it comprises a stacked multi-modal autoencoder neural network to create joint representations of text and images, and a spatio-temporal graph convolution neural network for semi-supervised classification. The results presented in this paper show that our approach performs the classification of social media content with higher accuracy than traditional machine learning models as well as two state-of-art deep learning frameworks. Numéro de notice : A2021-024 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101583 Date de publication en ligne : 16/12/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101583 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96608 [article]

Incorporating behavior into animal movement modeling: a constrained agent-based model for estimating visit probabilities in space-time prisms / Rebecca W. Loraamm in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 8 (August 2020) . - pp 1607 - 1627 Titre : Incorporating behavior into animal movement modeling: a constrained agent-based model for estimating visit probabilities in space-time prisms Type de document : Article/Communication Auteurs : Rebecca W. Loraamm, Auteur Année de publication : 2020 Article en page(s) : pp 1607 - 1627 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] comportement [Termes IGN] migration animale [Termes IGN] modèle orienté agent [Termes IGN] objet mobile [Termes IGN] prisme spatio-temporel [Termes IGN] système multi-agents [Termes IGN] Time-geography Résumé : (auteur) Animal movement is a dynamic spatio-temporal process. While trajectory data reflect the instantaneous animal position in space and time, other factors influence movement decisions between these observed positions. While some methods incorporate environmental (habitat) context into their understanding of the animal movement process, it is often captured in terms of simple parameters or weights influencing model results; primary behavioral data are not used directly to inform these models. Here, a new space-time constrained agent-based model is introduced, capable of producing ordered, behaviorally informed animal potential paths between observed space-time anchors. Potential paths generated by this approach incorporate both observed animal behavior and classical space-time constraints, and are used to construct associated visit probability distributions. Additionally, the notion of a behavioral space-time path is introduced, a variant of the space-time path based on the results of behaviorally aware animal movement simulation. The results of this approach demonstrate a means to better understand the varied movement opportunities within space-time prisms from an animal behavior perspective. From a spatial ecology perspective, not only is the environmental context considered, but the animal’s choice of transition and movement magnitude between contexts is modeled. This approach provides insight into the complex sequence of behaviorally informed actions driving animal movement decision-making. Numéro de notice : A2020-409 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1658875 Date de publication en ligne : 11/09/2019 En ligne : https://doi.org/10.1080/13658816.2019.1658875 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95466 [article]

Mapping areas of asynchronous‐temporal interaction in animal‐telemetry data / Brendan A. Hoover in Transactions in GIS, Vol 24 n° 3 (June 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 3 (June 2020) . - pp 573 - 586 Titre : Mapping areas of asynchronous‐temporal interaction in animal‐telemetry data Type de document : Article/Communication Auteurs : Brendan A. Hoover, Auteur ; Jennifer A. Miller, Auteur ; Jed A. Long, Auteur Année de publication : 2020 Article en page(s) : pp 573 - 586 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] comportement [Termes IGN] écologie [Termes IGN] habitat animal [Termes IGN] interaction spatiale [Termes IGN] maladie animale [Termes IGN] migration animale [Termes IGN] population animale [Termes IGN] Time-geography Résumé : (Auteur) Animal interactions are a crucial aspect of behavioral ecology that affect mating, territorial behavior, resource use, and disease spread. Commonly, animals will interact because of shared resources. Recent methods have used time geography to map landscape areas where interactions were possible. However, such methods do not identify areas of less direct interaction, like through smell or sight. These indirect or asynchronous interactions are also a crucial aspect of animal behavioral ecology and affect group behaviors such as leading/following hierarchies and joint resource use. Asynchronous interactions are difficult to map because they can occur in a synchronous space at asynchronous times, as well as in asynchronous spaces at a synchronous time. Here, we present a method termed the temporally asynchronous‐joint potential path area (ta‐jPPA) that maps areas of potential temporally asynchronous–spatially synchronous interactions. We used simulated data to statistically test ta‐jPPA and empirical data to demonstrate how ta‐jPPA can find patterns in habitat use. Numéro de notice : A2020-246 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12622 Date de publication en ligne : 05/05/2020 En ligne : https://doi.org/10.1111/tgis.12622 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95308 [article]

Spatio-temporal mobility and Twitter: 3D visualisation of mobility flows / Joaquín Osorio Arjona in Journal of maps, vol 16 n° 1 ([02/01/2020])  

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L’accessibilité ferroviaire à Paris des grandes aires urbaines françaises : approche par la time geography / Laurent Chapelon in Mappemonde, n° 127 (juillet 2019)  

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A time‐geographic approach to quantifying wildlife–road interactions / Rebecca W. Loraamm in Transactions in GIS, vol 23 n° 1 (February 2019)  

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Rapport d'activité 2018 de l'Institut National de l'Information Géographique et Forestière IGN, 2. Panorama 2018 / Institut national de l'information géographique et forestière (2012 -) (2019)

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Thinking Time Geography / Kajsa Ellegård (2019)  

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Testing time-geographic density estimation for home range analysis using an agent-based model of animal movement / Joni A. Downs in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)  

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Extraction of spatio‐temporal data about historical events from text documents / Susanna Abraham in Transactions in GIS, vol 22 n° 3 (June 2018)  

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The geometry of space-time prisms with uncertain anchors / Bart Kuijpers in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)  

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A wildlife movement approach to optimally locate wildlife crossing structures / Rebecca W. Loraamm in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)  

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A modification of the time-geographic framework to support temporal flexibility in ‘fixed’ activities / Laure Charleux in International journal of geographical information science IJGIS, vol 29 n° 7 (July 2015)  

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