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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] analyse contextuelle [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] étiquetage sémantique [Termes IGN] partage de données localisées [Termes IGN] réseau social [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])  

Public [article]  inJournal of maps > vol 16 n° 1 [02/01/2020] . - pp 153 - 160 Titre : Spatio-temporal mobility and Twitter: 3D visualisation of mobility flows Type de document : Article/Communication Auteurs : Joaquín Osorio Arjona, Auteur ; Juan Carlos García Palomares, Auteur Année de publication : 2020 Article en page(s) : pp 153 - 160 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatio-temporelle [Termes IGN] base de données localisées [Termes IGN] données localisées des bénévoles [Termes IGN] espace-temps [Termes IGN] interface de programmation [Termes IGN] Madrid (Espagne) [Termes IGN] migration pendulaire [Termes IGN] mobilité urbaine [Termes IGN] réseau social [Termes IGN] système d'information géographique [Termes IGN] Time-geography [Termes IGN] Twitter [Termes IGN] visualisation 3D [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Recent progress in computation and the spatio-temporal richness of data obtained from new sources have invigorated Time Geography. It is now possible to visualise and represent movements of people in a dual spatial–temporal dimension. In this work, we use geo-located data from the social media platform Twitter to show the value of new data sources for Time Geography. The methodology consists of visualising space–time paths in 2D and 3D in four study zones, with different land-use profiles, based on tweets compiled over the course of two years. The results provide a view of behaviours occurring in the areas of study throughout the day, with complementary data to show the population's main activity at different times. Numéro de notice : A2020-645 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2020.1778549 date de publication en ligne : 18/06/2020 En ligne : https://doi.org/10.1080/17445647.2020.1778549 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96071 [article]

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

Public [article]  inMappemonde [en ligne] > n° 127 (juillet 2019) Titre : L’accessibilité ferroviaire à Paris des grandes aires urbaines françaises : approche par la time geography Type de document : Article/Communication Auteurs : Laurent Chapelon, Auteur ; Adrien Lammoglia, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accessibilité [Termes IGN] analyse des besoins [Termes IGN] métropole [Termes IGN] mobilité territoriale [Termes IGN] réseau ferroviaire [Termes IGN] Time-geography [Termes IGN] train à grande vitesse [Termes IGN] transport ferroviaire [Termes IGN] utilisateur Résumé : (auteur) Le déploiement de la grande vitesse ferroviaire en France depuis le début des années 80 a profondément modifié l’offre interurbaine de transport. Cet article vise à étudier l’accessibilité ferroviaire à Paris des grandes aires urbaines françaises. Pour cela, il mobilise les fondements théoriques et méthodologiques de la time-geography. Si d’importants gains de temps de parcours ont été observés pour certaines villes, la configuration du réseau et l’organisation des services ne répondent que partiellement aux besoins de déplacement des habitants des plus grands pôles urbains français. Numéro de notice : A2019-649 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.4000/mappemonde.1921 En ligne : https://doi.org/10.4000/mappemonde.1921 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97252 [article]

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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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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A GIS toolbox for measuring and mapping person-based space-time accessibility / Laure Charleux in Transactions in GIS, vol 19 n° 2 (April 2015)  

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Extended abstract proceedings of the GIScience 2014 / Kathleen Stewart (2014)  

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Improving knowledge about wildlife mobility in using geographic network analysis / Elodie Buard (2014) 

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