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Evaluating geovisualization for spatial learning analytics / Anthony C. Robinson in International journal of cartography, vol 6 n° 3 (October 2020)  

Public [article]  inInternational journal of cartography > vol 6 n° 3 (October 2020) . - pp 331 - 349 Titre : Evaluating geovisualization for spatial learning analytics Type de document : Article/Communication Auteurs : Anthony C. Robinson, Auteur ; Cary L. Anderson, Auteur ; Sterling Quinn, Auteur Année de publication : 2020 Article en page(s) : pp 331 - 349 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse géovisuelle [Termes descripteurs IGN] analyse spatiale [Termes descripteurs IGN] apprentissage (cognition) [Termes descripteurs IGN] éducation [Termes descripteurs IGN] formation [Termes descripteurs IGN] formation à distance [Termes descripteurs IGN] géographie [Termes descripteurs IGN] pédagogie [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Contemporary systems for supporting digital learning are capable of collecting a wide range of data on learner behaviours. The emerging science and technology of learning analytics seeks to use this information to improve learning outcomes and support institutional assessment. In this work we explore the potential for the spatial dimension in learning analytics, and we evaluate a prototype geovisualization system designed to support what we call spatial learning analytics. A user evaluation with geographers and educators was conducted to characterize the usability and utility of our prototype spatial learning analytics system. By helping us understand what our prototype system does and does not do well, we are able to suggest a variety of new ways in which future spatial learning analytics systems can be developed. Numéro de notice : A2020-651 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2020.1735034 date de publication en ligne : 14/05/2020 En ligne : https://doi.org/10.1080/23729333.2020.1735034 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96107 [article]

Advancing the theory and practice of system evaluation: a case study in geovisual analytics of social media / Alexander Savelyev in International journal of cartography, Vol 6 n° 2 (July 2020)  

Public [article]  inInternational journal of cartography > Vol 6 n° 2 (July 2020) . - pp 202 - 221 Titre : Advancing the theory and practice of system evaluation: a case study in geovisual analytics of social media Type de document : Article/Communication Auteurs : Alexander Savelyev, Auteur ; Alan M. MacEachren, Auteur Année de publication : 2020 Article en page(s) : pp 202 - 221 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse géovisuelle [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] logiciel de visualisation [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] utilisateur [Vedettes matières IGN] Géovisualisation Résumé : (auteur) This paper advances the state-of-the-art in methodology design for empirical evaluation of (geo)visual analytics software. Specifically, we describe the process of design, development and application of a prototypical user study tailored to the evaluation of complex geovisual analytics tools that focus on social media analysis. We fist perform a synthesis of existing theory and best practices for software evaluation of comparable systems. We then demonstrate how the product of said synthesis – a methodological ‘check list’ – can be used to inform a proof-of-concept user study of an actual geovisual analytics software system. The resulting user study design accommodates for the use of real geographic social media datasets, the complexity of the intended analytical process, and for the learning challenges faced by the participants working with a fully-functional and mature geovisual analytics application, and is likely representative of a wide range of evaluation scenarios in (geo)visual analytics. A complete summary of all the study instruments is included to encourage their scrutiny, reuse and modification by others. Finally, we have discovered that participants’ curiosity and desire for autonomy played a noticeable role in the evaluation process – something not previously reported. Numéro de notice : A2020-373 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2019.1637488 date de publication en ligne : 01/08/2019 En ligne : https://doi.org/10.1080/23729333.2019.1637488 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95305 [article]

Computational improvements to multi-scale geographically weighted regressio / Ziqi Li in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 7 (July 2020) . - pp 1378 - 1397 Titre : Computational improvements to multi-scale geographically weighted regressio Type de document : Article/Communication Auteurs : Ziqi Li, Auteur ; A. Stewart Fotheringham, Auteur Année de publication : 2020 Article en page(s) : pp 1378 - 1397 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse géovisuelle [Termes descripteurs IGN] analyse multiéchelle [Termes descripteurs IGN] implémentation (informatique) [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] régression géographiquement pondérée [Termes descripteurs IGN] traitement parallèle Résumé : (auteur) Geographically Weighted Regression (GWR) has been broadly used in various fields to model spatially non-stationary relationships. Multi-scale Geographically Weighted Regression (MGWR) is a recent advancement to the classic GWR model. MGWR is superior in capturing multi-scale processes over the traditional single-scale GWR model by using different bandwidths for each covariate. However, the multiscale property of MGWR brings additional computation costs. The calibration process of MGWR involves iterative back-fitting under the additive model (AM) framework. Currently, MGWR can only be applied on small datasets within a tolerable time and is prohibitively time-consuming to run with moderately large datasets (greater than 5,000 observations). In this paper, we propose a parallel implementation that has crucial computational improvements to the MGWR calibration. This improved computational method reduces both memory footprint and runtime to allow MGWR modelling to be applied to moderate-to-large datasets (up to 100,000 observations). These improvements are integrated into the mgwr python package and the MGWR 2.0 software, both of which are freely available to download. Numéro de notice : A2020-305 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1720692 date de publication en ligne : 06/02/2020 En ligne : https://doi.org/10.1080/13658816.2020.1720692 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95147 [article]

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Evaluating the impact of visualization of risk upon emergency route-planning / Lisa Cheong in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 5 (May 2020) . - pp 1022 - 1050 Titre : Evaluating the impact of visualization of risk upon emergency route-planning Type de document : Article/Communication Auteurs : Lisa Cheong, Auteur ; Christoph Kinkeldey, Auteur ; Ingrid Burfurd, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1022 - 1050 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes descripteurs IGN] analyse géovisuelle [Termes descripteurs IGN] cartographie d'urgence [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] inondation [Termes descripteurs IGN] itinéraire [Termes descripteurs IGN] planification [Termes descripteurs IGN] représentation cartographique [Termes descripteurs IGN] sémiologie graphique [Termes descripteurs IGN] symbole graphique Résumé : (auteur) This paper reports on a controlled experiment evaluating how different cartographic representations of risk affect participants’ performance on a complex spatial decision task: route planning. The specific experimental scenario used is oriented towards emergency route-planning during flood response. The experiment compared six common abstract and metaphorical graphical symbolizations of risk. The results indicate a pattern of less-preferred graphical symbolizations associated with slower responses and lower-risk route choices. One mechanism that might explain these observed relationships would be that more complex and effortful maps promote closer attention paid by participants and lower levels of risk taking. Such user considerations have important implications for the design of maps and mapping interfaces for emergency planning and response. The data also highlights the importance of the ‘right decision, wrong outcome problem’ inherent in decision-making under uncertainty: in individual instances, more risky decisions do not always lead to worse outcomes. Numéro de notice : A2020-206 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1701677 date de publication en ligne : 12/12/2019 En ligne : https://doi.org/10.1080/13658816.2019.1701677 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94885 [article]

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An IEEE value loop of human-technology collaboration in geospatial information science / Liqiu Meng in Geo-spatial Information Science, vol 23 n° 1 (March 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 1 (March 2020) . - pp 61- 67 Titre : An IEEE value loop of human-technology collaboration in geospatial information science Type de document : Article/Communication Auteurs : Liqiu Meng, Auteur Année de publication : 2020 Article en page(s) : pp 61- 67 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique [Termes descripteurs IGN] analyse géovisuelle [Termes descripteurs IGN] approche holistique [Termes descripteurs IGN] données localisées numériques [Termes descripteurs IGN] enrichissement sémantique [Termes descripteurs IGN] éthique [Termes descripteurs IGN] géographie sociale [Termes descripteurs IGN] information sémantique [Termes descripteurs IGN] intégration de données [Termes descripteurs IGN] intelligence artificielle [Termes descripteurs IGN] interface homme-machine [Termes descripteurs IGN] recherche interdisciplinaire [Termes descripteurs IGN] web sémantique Résumé : (auteur) Geosensing and social sensing as two digitalization mainstreams in big data era are increasingly converging toward an integrated system for the creation of semantically enriched digital Earth. Along with the rapid developments of AI technologies, this convergence has inevitably brought about a number of transformations. On the one hand, value-adding chains from raw data to products and services are becoming value-adding loops composed of four successive stages – Informing, Enabling, Engaging and Empowering (IEEE). Each stage is a dynamic loop for itself. On the other hand, the “human versus technology” relationship is upgraded toward a game-changing “human and technology” collaboration. The information loop is essentially shaped by the omnipresent reciprocity between humans and technologies as equal partners, co-learners and co-creators of new values. The paper gives an analytical review on the mutually changing roles and responsibilities of humans and technologies in the individual stages of the IEEE loop, with the aim to promote a holistic understanding of the state of the art of geospatial information science. Meanwhile, the author elicits a number of challenges facing the interwoven human-technology collaboration. The transformation to a growth mind-set may take time to realize and consolidate. Research works on large-scale semantic data integration are just in the beginning. User experiences of geovisual analytic approaches are far from being systematically studied. Finally, the ethical concerns for the handling of semantically enriched digital Earth cover not only the sensitive issues related to privacy violation, copyright infringement, abuse, etc. but also the questions of how to make technologies as controllable and understandable as possible for humans and how to keep the technological ethos within its constructive sphere of societal influence. Numéro de notice : A2020-163 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10095020.2020.1718004 date de publication en ligne : 23/01/2020 En ligne : https://doi.org/10.1080/10095020.2020.1718004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94823 [article]

Perspective switch and spatial knowledge acquisition: effects of age, mental rotation ability and visuospatial memory capacity on route learning in virtual environments with different levels of realism / Ismini E. Lokka in Cartography and Geographic Information Science, Vol 47 n° 1 (January 2020)  

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Visual analysis of inconsistencies in hydraulic simulation data / Octave Perrin (2020)  

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Visualizing 3D climate data in urban 3D models / Jacques Gautier (2020)  

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Multiple-view geospatial comparison using web-based virtual globes / Liangfeng Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

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Modeling and visualizing semantic and spatio-temporal evolution of topics in interpersonal communication on Twitter / Caglar Koylu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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The effect of topography and elevation on viewsheds in mountain landscapes using geovisualization / Loukas-Moysis Misthos in International journal of cartography, vol 5 n° 1 (March 2019)  

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CarSenToGram: geovisual text analytics for exploring spatiotemporal variation in public discourse on Twitter / Caglar Koylu in Cartography and Geographic Information Science, Vol 46 n° 1 (January 2019)  

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Manual of digital Earth, ch. 7. Geospatial information visualization and extended reality displays / Arzu Çöltekin (2019)  

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Modeling evacuation in institutional space: Linking three-dimensional data capture, simulation, analysis, and visualization workflows for risk assessment and communication / Ian M. Lochhead in Information visualization, vol 18 n° 1 (January 2019)  

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Visual exploration of migration patterns in gull data / Maximilian Konzack in Information visualization, vol 18 n° 1 (January 2019)  

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