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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 descripteurs IGN] analyse contextuelle [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] classification semi-dirigée [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] étiquetage sémantique [Termes descripteurs IGN] partage de données localisées [Termes descripteurs IGN] réseau social [Termes descripteurs 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 descripteurs IGN] comportement [Termes descripteurs IGN] migration animale [Termes descripteurs IGN] modèle orienté agent [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] prisme spatio-temporel [Termes descripteurs IGN] système multi-agents [Termes descripteurs 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 descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] comportement [Termes descripteurs IGN] écologie [Termes descripteurs IGN] habitat animal [Termes descripteurs IGN] interaction spatiale [Termes descripteurs IGN] maladie animale [Termes descripteurs IGN] migration animale [Termes descripteurs IGN] population animale [Termes descripteurs 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 descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] base de données localisées [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] espace-temps [Termes descripteurs IGN] interface de programmation [Termes descripteurs IGN] Madrid (Espagne) [Termes descripteurs IGN] migration pendulaire [Termes descripteurs IGN] mobilité urbaine [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] Time-geography [Termes descripteurs IGN] Twitter [Termes descripteurs 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]

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

Public [article]  inTransactions in GIS > vol 23 n° 1 (February 2019) . - pp 70 - 86 Titre : A time‐geographic approach to quantifying wildlife–road interactions Type de document : Article/Communication Auteurs : Rebecca W. Loraamm, Auteur ; Joni A. Downs, Auteur ; David Lamb, Auteur Année de publication : 2019 Article en page(s) : pp 70 - 86 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] comportement [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] faune locale [Termes descripteurs IGN] gestion de la vie sauvage [Termes descripteurs IGN] interaction spatiale [Termes descripteurs IGN] migration animale [Termes descripteurs IGN] Mustelidae [Termes descripteurs IGN] prisme spatio-temporel [Termes descripteurs IGN] route [Termes descripteurs IGN] Time-geography [Termes descripteurs IGN] voxel Résumé : (auteur) Recent advances in time geography offer new perspectives for studying animal movements and interactions in an environmental context. In particular, the ability to estimate an animal's spatial location probabilistically at temporal sampling intervals between known fix locations allows researchers to quantify how individuals interact with one another and their environment on finer temporal and spatial scales than previously explored. This article extends methods from time geography, specifically probabilistic space–time prisms, to quantify and summarize animal–road interactions toward understanding related diurnal movement behaviors, including road avoidance. The approach is demonstrated using tracking data for fishers (Martes pennanti) in New York State, where the total probability of interaction with roadways is calculated for individuals over the duration tracked. Additionally, a summarization method visualizing daily interaction probabilities at 60 s intervals is developed to assist in the examination of temporal patterns associated with fishers’ movement behavior with respect to roadways. The results identify spatial and temporal patterns of fisher–roadway interaction by time of day. Overall, the methodologies discussed offer an intuitive means to assess moving object location probabilities in the context of environmental factors. Implications for movement ecology and related conservation planning efforts are also discussed. Numéro de notice : A2019-090 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12497 date de publication en ligne : 17/12/2018 En ligne : https://doi.org/10.1111/tgis.12497 Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92237 [article]

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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Linking time geography and activity theory to support the activities of mobile information seekers / Paul Crease in Transactions in GIS, vol 17 n° 4 (August 2013)  

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