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Termes IGN > géomatique > géovisualisation > analyse géovisuelle
analyse géovisuelle
Commentaire :
- Geovisual analytics refers to the science of analytical reasoning with spatial information as facilitated by interactive visual interfaces. It is distinguished by its focus on novel approaches to analysis rather than novel approaches to visualization or computational methods alone. As a result, geovisual analytics is usually grounded in real-world problem solving contexts. Research in geovisual analytics may focus on the development of new computational approaches to identify or predict patterns, new visual interfaces to geographic data, or new insights into the cognitive and perceptual processes that users apply to solve complex analytical problems. Systems for geovisual analytics typically feature a high-degree of user-driven interactivity and multiple visual representation types for spatial data. Geovisual analytics tools have been developed for a variety of problem scenarios, such as crisis management and disease epidemiology. Looking ahead, the emergence of new spatial data sources and display formats is expected to spur an expanding set of research and application needs for the foreseeable future. (Robinson, A. (2017). Geovisual Analytics. The Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2017 Edition), John P. Wilson (ed.). DOI: 10.22224/gistbok/2017.3.6)
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Visual exploration of migration patterns in gull data / Maximilian Konzack in Information visualization, vol 18 n° 1 (January 2019)
[article]
Titre : Visual exploration of migration patterns in gull data Type de document : Article/Communication Auteurs : Maximilian Konzack, Auteur ; Pieter Gijsbers, Auteur ; Ferry Timmers, Auteur ; et al., Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] Aves
[Termes IGN] migration animale
[Termes IGN] origine - destination
[Termes IGN] visualisation multiéchelle
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) We present a visual analytics approach to explore and analyze movement data as collected by ecologists interested in understanding migration. Migration is an important and intriguing process in animal ecology, which may be better understood through the study of tracks for individuals in their environmental context. Our approach enables ecologists to explore the spatio-temporal characteristics of such tracks interactively. It identifies and aggregates stopovers depending on a scale at which the data is visualized. Statistics of stopover sites and links between them are shown on a zoomable geographic map which allows to interactively explore directed sequences of stopovers from an origin to a destination. In addition, the spatio-temporal properties of the trajectories are visualized by means of a density plot on a geographic map and a calendar view. To evaluate our visual analytics approach, we applied it on a data set of 75 migrating gulls that were tracked over a period of 3 years. The evaluation by an expert user confirms that our approach supports ecologists in their analysis workflow by helping to identifying interesting stopover locations, environmental conditions or (groups of) individuals with characteristic migratory behavior, and allows therefore to focus on visual data analysis. Numéro de notice : A2019-401 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1177/1473871617751245 Date de publication en ligne : 20/01/2018 En ligne : https://doi.org/10.1177/1473871617751245 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89120
in Information visualization > vol 18 n° 1 (January 2019)[article]Descriptive measures of point distributions summarized with respect to spatial scale in visualization / Yukio Sadahiro in Cartographica, vol 53 n° 3 (Fall 2018)
[article]
Titre : Descriptive measures of point distributions summarized with respect to spatial scale in visualization Type de document : Article/Communication Auteurs : Yukio Sadahiro, Auteur Année de publication : 2018 Article en page(s) : pp 185 - 202 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] carte de répartition par points
[Termes IGN] carte thématique
[Termes IGN] méthode fondée sur le noyau
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Visual exploration plays a critical role in point pattern analysis. It permits analysts to grasp a wide variety of spatial patterns in point distributions that are not necessarily detectable by mathematical and statistical methods. Since spatial patterns are scale-dependent, grid and kernel density maps are effective in analysis that can visualize point distributions at various scales from small to large. Visual exploration of these maps, however, takes a considerable amount of time even if the maps are generated automatically in GIS software. In addition, visual exploration inevitably becomes subjective and unstable when treating numerous maps simultaneously. It is not easy to evaluate and memorize spatial patterns in maps in a consistent and objective way. To resolve the problem, this article proposes new quantitative measures summarizing the characteristics of point distributions. The measures can be visualized as maps that help analysts to capture the overall spatial pattern of point distributions efficiently. Numerical experiments and applications to real data analysis are performed to test the validity of the proposed measures. The results reveal the effectiveness of the measures, as well as their shortcomings, to be resolved in future research. Numéro de notice : A2018-482 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart.53.3.2017-0023 Date de publication en ligne : 01/10/2018 En ligne : https://doi.org/10.3138/cart.53.3.2017-0023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91207
in Cartographica > vol 53 n° 3 (Fall 2018) . - pp 185 - 202[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 031-2018031 SL Revue Centre de documentation Revues en salle Disponible Method for the analysis and visualization of similar flow hotspot patterns between different regional groups / Haiping Zhang in ISPRS International journal of geo-information, vol 7 n° 8 (August 2018)
[article]
Titre : Method for the analysis and visualization of similar flow hotspot patterns between different regional groups Type de document : Article/Communication Auteurs : Haiping Zhang, Auteur ; Xingxing Zhou, Auteur ; Xin Gu, Auteur ; Lei Zhou, Auteur ; Genlin Ji, Auteur ; Guoan Tang, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] données de flux
[Termes IGN] interaction spatiale
[Termes IGN] système d'information géographique
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Interaction among different regions can be illustrated in the form of a stream. For example, the interaction between the flows of people and information among different regions can reflect city network structures, as well as city functions and interconnections. The popularization of big data has facilitated the acquisition of flow data for various types of individuals. The application of the regional interaction model, which is based on the summary level of individual flow data mining, is currently a hot research topic. Thus far, however, previous research on spatial interaction methods has mainly focused on point-to-point and area-to-area interaction patterns, and investigations on the patterns of interaction hotspots between two regional groups with predefined neighborhood relationships, that being with two regions, remain scarce. In this study, a method for the identification of similar interaction hotspot patterns between two regional groups is proposed, and geo-information Tupu methods are applied to visualize interaction patterns. China’s air traffic flow data are used as an example to illustrate the performance of the proposed method to identify and analyze interaction hotspot patterns between regional groups with adjoining relationships across China. Research results indicate that the proposed method efficiently identifies the patterns of interaction flow hotspots between regional groups. Moreover, it can be applied to analyze any flow space in the excavation of the patterns of regional group interaction hotspots. Numéro de notice : A2018-350 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7080328 Date de publication en ligne : 15/08/2018 En ligne : https://doi.org/10.10.3390/ijgi7080328 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90585
in ISPRS International journal of geo-information > vol 7 n° 8 (August 2018)[article]SensePlace3: a geovisual framework to analyze place–time–attribute information in social media / Scott Pezanowski in Cartography and Geographic Information Science, Vol 45 n° 5 (August 2018)
[article]
Titre : SensePlace3: a geovisual framework to analyze place–time–attribute information in social media Type de document : Article/Communication Auteurs : Scott Pezanowski, Auteur ; Alan M. MacEachren, Auteur ; Alexander Savelyev, Auteur ; Anthony C. Robinson, Auteur Année de publication : 2018 Article en page(s) : pp 420 - 437 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] analyse spatio-temporelle
[Termes IGN] données massives
[Termes IGN] environnement de développement
[Termes IGN] gestion de crise
[Termes IGN] réseau social
[Termes IGN] trace numérique
[Termes IGN] Twitter
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted about, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources. Numéro de notice : A2018-272 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1370391 Date de publication en ligne : 11/09/2017 En ligne : https://doi.org/10.1080/15230406.2017.1370391 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90336
in Cartography and Geographic Information Science > Vol 45 n° 5 (August 2018) . - pp 420 - 437[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2018051 RAB Revue Centre de documentation En réserve L003 Disponible Association rules-based multivariate analysis and visualization of spatiotemporal climate data / Feng Wang in ISPRS International journal of geo-information, vol 7 n° 7 (July 2018)
[article]
Titre : Association rules-based multivariate analysis and visualization of spatiotemporal climate data Type de document : Article/Communication Auteurs : Feng Wang, Auteur ; Wenwen Li, Auteur ; Sizhe Wang, Auteur ; Chris R. Johnson, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] analyse multivariée
[Termes IGN] Arctique
[Termes IGN] cyclone
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] phénomène atmosphérique
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Understanding atmospheric phenomena involves analysis of large-scale spatiotemporal multivariate data. The complexity and heterogeneity of such data pose a significant challenge in discovering and understanding the association between multiple climate variables. To tackle this challenge, we present an interactive heuristic visualization system that supports climate scientists and the public in their exploration and analysis of atmospheric phenomena of interest. Three techniques are introduced: (1) web-based spatiotemporal climate data visualization; (2) multiview and multivariate scientific data analysis; and (3) data mining-enabled visual analytics. The Arctic System Reanalysis (ASR) data are used to demonstrate and validate the effectiveness and usefulness of our method through a case study of “The Great Arctic Cyclone of 2012”. The results show that different variables have strong associations near the polar cyclone area. This work also provides techniques for identifying multivariate correlation and for better understanding the driving factors of climate phenomena. Numéro de notice : A2018-503 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7070266 Date de publication en ligne : 09/07/2018 En ligne : https://doi.org/10.3390/ijgi7070266 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90575
in ISPRS International journal of geo-information > vol 7 n° 7 (July 2018)[article]A geovisual analytics exploration of the OpenStreetMap crowd / Sterling Quinn in Cartography and Geographic Information Science, Vol 45 n° 2 (March 2018)PermalinkA simulation and visualization environment for spatiotemporal disaster risk assessments of network infrastructures / Magnus Heittzler in Cartographica, vol 52 n° 4 (Winter 2017)PermalinkInsight provenance for spatiotemporal visual analytics : Theory, review, and guidelines / Andreas Hall in Journal of Spatial Information Science (JoSIS), n° 15 (September 2017)PermalinkOptimization of simulation and visualization analysis of dam-failure flood disaster for diverse computing systems / Mingwei Liu in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)PermalinkVisual analytics of time-varying multivariate ionospheric scintillation data / Aurea Soriano-Vargas in Computers and graphics, vol 68 (November 2017)PermalinkAnimated chorem-based summaries of geographic data streams from sensors in real time / Zina Bouattou in Journal of Visual Languages and Computing, vol 41 (August 2017)PermalinkA viewpoint based approach to the visual exploration of trajectory / Jie Li in Journal of Visual Languages and Computing, vol 41 (August 2017)PermalinkAn evaluation of a visual analytics prototype for calendar-related spatiotemporal periodicity detection and analysis / Brian Swedberg in Cartographica, vol 52 n° 1 (Spring 2017)PermalinkVisual analytics of delays and interaction in movement data / Maximilian Konzack in International journal of geographical information science IJGIS, vol 31 n° 1-2 (January - February 2017)PermalinkDe la géographie militaire au Geospatial Intelligence en France (19e siècle - 21e siècle) / Philippe Boulanger in Bulletin de liaison des membres de la Société de Géographie, Hors-série (juin 2016)Permalink