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How does the design of landmarks on a mobile map influence wayfinding experts’ spatial learning during a real-world navigation task? / Armand Kapaj in Cartography and Geographic Information Science, Vol 50 n° 2 (March 2023)  

Public [article]  inCartography and Geographic Information Science > Vol 50 n° 2 (March 2023) . - pp 197 - 213 Titre : How does the design of landmarks on a mobile map influence wayfinding experts’ spatial learning during a real-world navigation task? Type de document : Article/Communication Auteurs : Armand Kapaj, Auteur ; Sara Maggi, Auteur ; Christopher Hilton, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 197 - 213 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] itinéraire [Termes IGN] navigation pédestre [Termes IGN] oculométrie [Termes IGN] orientation [Termes IGN] point de repère [Termes IGN] raisonnement spatial [Termes IGN] représentation cartographique [Termes IGN] représentation mentale spatiale [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Humans increasingly rely on GPS-enabled mobile maps to navigate novel environments. However, this reliance can negatively affect spatial learning, which can be detrimental even for expert navigators such as search and rescue personnel. Landmark visualization has been shown to improve spatial learning in general populations by facilitating object identification between the map and the environment. How landmark visualization supports expert users’ spatial learning during map-assisted navigation is still an open research question. We thus conducted a real-world study with wayfinding experts in an unknown residential neighborhood. We aimed to assess how two different landmark visualization styles (abstract 2D vs. realistic 3D buildings) would affect experts’ spatial learning in a map-assisted navigation task during an emergency scenario. Using a between-subjects design, we asked Swiss military personnel to follow a given route using a mobile map, and to identify five task-relevant landmarks along the route. We recorded experts’ gaze behavior while navigating and examined their spatial learning after the navigation task. We found that experts’ spatial learning improved when they focused their visual attention on the environment, but the direction of attention between the map and the environment was not affected by the landmark visualization style. Further, there was no difference in spatial learning between the 2D and 3D groups. Contrary to previous research with general populations, this study suggests that the landmark visualization style does not enhance expert navigators’ navigation or spatial learning abilities, thus highlighting the need for population-specific mobile map design solutions. Numéro de notice : A2023-222 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2023.2183525 Date de publication en ligne : 07/03/2023 En ligne : https://doi.org/10.1080/15230406.2023.2183525 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103168 [article]

A spatiotemporal data model and an index structure for computational time geography / Bi Yu Chen in International journal of geographical information science IJGIS, vol 37 n° 3 (March 2023)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 37 n° 3 (March 2023) . - pp 550 - 583 Titre : A spatiotemporal data model and an index structure for computational time geography Type de document : Article/Communication Auteurs : Bi Yu Chen, Auteur ; Yu-Bo Luo, Auteur ; Tao Jia, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 550 - 583 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] approche hiérarchique [Termes IGN] données massives [Termes IGN] données spatiotemporelles [Termes IGN] modèle conceptuel de données spatio-temporelles [Termes IGN] requête spatiotemporelle [Termes IGN] stockage de données [Termes IGN] Time-geography Résumé : (auteur) The availability of Spatiotemporal Big Data has provided a golden opportunity for time geographical studies that have long been constrained by the lack of individual-level data. However, how to store, manage, and query a huge number of time geographic entities effectively and efficiently with complex spatiotemporal characteristics and relationships poses a significant challenge to contemporary GIS platforms. In this article, a hierarchical compressed linear reference (CLR) model is proposed to transform network-constrained time geographic entities from three-dimensional (3D) (x, y, t) space into two-dimensional (2D) space. Accordingly, time geographic entities can be represented as 2D spatial entities and stored in a classical spatial database. The proposed CLR model supports a hierarchical linear reference system (LRS) including not only underlying a link-based LRS but also multiple higher-level route-based LRSs. In addition, an LRS-based spatiotemporal index structure is developed to index both time geographic entities and the corresponding hierarchical network. The results of computational experiments on large datasets of space–time paths and prisms show that the proposed hierarchical CLR model is effective at storing and managing time geographic entities in road networks. The developed index structure achieves satisfactory query performance in milliseconds on large datasets of time geographic entities. Numéro de notice : A2023-153 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2128192 Date de publication en ligne : 03/10/2023 En ligne : https://doi.org/10.1080/13658816.2022.2128192 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102836 [article]

A multi-source spatio-temporal data cube for large-scale geospatial analysis / Fan Gao in International journal of geographical information science IJGIS, vol 36 n° 9 (September 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 9 (September 2022) . - pp 1853 - 1884 Titre : A multi-source spatio-temporal data cube for large-scale geospatial analysis Type de document : Article/Communication Auteurs : Fan Gao, Auteur ; Peng Yue, Auteur ; Zhipeng Cao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1853 - 1884 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cube espace-temps [Termes IGN] cyberinfrastructure [Termes IGN] données spatiotemporelles [Termes IGN] Géocube [Termes IGN] hypercube [Termes IGN] informatique en nuage [Termes IGN] intelligence artificielle [Termes IGN] observation de la Terre Résumé : (auteur) Data management and analysis are challenging with big Earth observation (EO) data. Expanding upon the rising promises of data cubes for analysis-ready big EO data, we propose a new geospatial infrastructure layered over a data cube to facilitate big EO data management and analysis. Compared to previous work on data cubes, the proposed infrastructure, GeoCube, extends the capacity of data cubes to multi-source big vector and raster data. GeoCube is developed in terms of three major efforts: formalize cube dimensions for multi-source geospatial data, process geospatial data query along these dimensions, and organize cube data for high-performance geoprocessing. This strategy improves EO data cube management and keeps connections with the business intelligence cube, which provides supplementary information for EO data cube processing. The paper highlights the major efforts and key research contributions to online analytical processing for dimension formalization, distributed cube objects for tiles, and artificial intelligence enabled prediction of computational intensity for data cube processing. Case studies with data from Landsat, Gaofen, and OpenStreetMap demonstrate the capabilities and applicability of the proposed infrastructure. Numéro de notice : A2022-643 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2087222 Date de publication en ligne : 14/06/2022 En ligne : https://doi.org/10.1080/13658816.2022.2087222 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101458 [article]

Exemplaires(1)

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Narrative cartography with knowledge graphs / Gengchen Mai in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 6 n° 1 (June 2022) Titre : Narrative cartography with knowledge graphs Type de document : Article/Communication Auteurs : Gengchen Mai, Auteur ; Weiming Huang, Auteur ; Ling Cai, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] ArcGIS [Termes IGN] cartographie ancienne [Termes IGN] cartographie par internet [Termes IGN] données spatiotemporelles [Termes IGN] géovisualisation [Termes IGN] modèle d'ontologie [Termes IGN] ontologie [Termes IGN] réseau sémantique [Termes IGN] SPARQL [Termes IGN] système d'information géographique [Termes IGN] web sémantique Résumé : (auteur) Narrative cartography is a discipline which studies the interwoven nature of stories and maps. However, conventional geovisualization techniques of narratives often encounter several prominent challenges, including the data acquisition & integration challenge and the semantic challenge. To tackle these challenges, in this paper, we propose the idea of narrative cartography with knowledge graphs (KGs). Firstly, to tackle the data acquisition & integration challenge, we develop a set of KG-based GeoEnrichment toolboxes to allow users to search and retrieve relevant data from integrated cross-domain knowledge graphs for narrative mapping from within a GISystem. With the help of this tool, the retrieved data from KGs are directly materialized in a GIS format which is ready for spatial analysis and mapping. Two use cases — Magellan’s expedition and World War II — are presented to show the effectiveness of this approach. In the meantime, several limitations are identified from this approach, such as data incompleteness, semantic incompatibility, and the semantic challenge in geovisualization. For the later two limitations, we propose a modular ontology for narrative cartography, which formalizes both the map content (Map Content Module) and the geovisualization process (Cartography Module). We demonstrate that, by representing both the map content and the geovisualization process in KGs (an ontology), we can realize both data reusability and map reproducibility for narrative cartography. Numéro de notice : A2022-946 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41651-021-00097-4 Date de publication en ligne : 02/02/2022 En ligne : https://doi.org/10.1007/s41651-021-00097-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99869 [article]

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]

Swipe versus multiple view: a comprehensive analysis using eye-tracking to evaluate user interaction with web maps / Stanislav Popelka in Cartography and Geographic Information Science, vol 49 n° 3 (May 2022)  

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IGN, changer d'échelle ! / Jean-Pierre Maillard in XYZ, n° 170 (mars 2022)

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Increasing territorial planning activities through viewshed analysis / Gheorghe-Gavrilă Hognogi in Geocarto international, vol 37 n° 2 ([15/01/2022])  

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Detecting and visualizing observation hot-spots in massive volunteer-contributed geographic data across spatial scales using GPU-accelerated kernel density estimation / Guiming Zhang in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)  

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Visual analysis of geospatial multivariate data for investigating radioactive deposition processes / Shigeo Takahashi in The Visual Computer, vol 37 n° 12 (December 2021)  

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Identifying surface urban heat island drivers and their spatial heterogeneity in China’s 281 cities: An empirical study based on multiscale geographically weighted regression / Lu Niu in Remote sensing, vol 13 n° 21 (November-1 2021)  

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

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Flood risk mapping using uncertainty propagation analysis on a peak discharge: case study of the Mille Iles River in Quebec / Jean-Marie Zokagoa in Natural Hazards, vol 107 n° 1 (May 2021)  

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What is the difference between augmented reality and 2D navigation electronic maps in pedestrian wayfinding? / Weihua Dong in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)  

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Geovisualization of COVID-19: State of the art and opportunities / Yu Lan in Cartographica, vol 56 n° 1 (Spring 2021)  

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