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Comparative usability of an augmented reality sandtable and 3D GIS for education / Antoni B. Moore in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 229 - 250 Titre : Comparative usability of an augmented reality sandtable and 3D GIS for education Type de document : Article/Communication Auteurs : Antoni B. Moore, Auteur ; Benjamin Daniel, Auteur ; greg Leonard, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 229 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] enseignement supérieur [Termes IGN] hydrologie [Termes IGN] modèle numérique de terrain [Termes IGN] modélisation 3D [Termes IGN] Nouvelle-Zélande [Termes IGN] réalité augmentée [Termes IGN] réalité de terrain [Termes IGN] réalité virtuelle [Termes IGN] sable [Termes IGN] test de performance Résumé : (auteur) Augmented Reality (AR) sandtables facilitate the shaping of sand to form a surface that is transformed into a digital terrain map which is projected back onto the sand. Although a mature technology, there are still few instances of sandtables being used in surface analysis. Fundamentally there has not been any reported formal assessment of how well sandtables perform in an educational context compared to other conventional learning environments. We compared learning outcomes from using an AR sandtable versus a conventional 3D GIS to convey key concepts in terrain and hydrological analyses via usability and knowledge testing. Overall results from students at a research-intensive New Zealand university reveal a faster task performance and more learning satisfaction when using the sandtable to undertake experimental tasks. Effectiveness and knowledge quiz results revealed no significant difference between the technologies though there was a trend for more accurate answers with 3D GIS tasks. Student learning wise, the sandtable integrated core concepts (especially morphometry) more effectively though both technologies were otherwise similar. We conclude that sandtables have high potential in geospatial teaching, fostering accessible and engaging means of introducing terrain and hydrological concepts, prior to undertaking a more accurate and precise surface analysis with 3D GIS. Numéro de notice : A2020-028 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1656810 Date de publication en ligne : 27/08/2019 En ligne : https://doi.org/10.1080/13658816.2019.1656810 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94481 [article]

Geospatial big data and cartography : research challenges and opportunities for making maps that matter / Anthony C. Robinson in International journal of cartography, vol 3 suppl 1 (May 2017)  

Public [article]  inInternational journal of cartography > vol 3 suppl 1 (May 2017) . - pp 32 - 60 Titre : Geospatial big data and cartography : research challenges and opportunities for making maps that matter Type de document : Article/Communication Auteurs : Anthony C. Robinson, Auteur ; Urška Demšar, Auteur ; Antoni B. Moore, Auteur ; Aileen Buckley, Auteur ; Jiang Bin, Auteur ; Kenneth Field, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 32 - 60 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] données localisées [Termes IGN] données massives [Termes IGN] recherche scientifique Résumé : (Auteur) Geospatial big data present a new set of challenges and opportunities for cartographic researchers in technical, methodological and artistic realms. New computational and technical paradigms for cartography are accompanying the rise of geospatial big data. Additionally, the art and science of cartography needs to focus its contemporary efforts on work that connects to outside disciplines and is grounded in problems that are important to humankind and its sustainability. Following the development of position papers and a collaborative workshop to craft consensus around key topics, this article presents a new cartographic research agenda focused on making maps that matter using geospatial big data. This agenda provides both long-term challenges that require significant attention and short-term opportunities that we believe could be addressed in more concentrated studies. Numéro de notice : A2018-436 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2016.1278151 Date de publication en ligne : 13/03/2017 En ligne : https://doi.org/10.1080/23729333.2016.1278151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90922 [article]

An intelligent geospatial processing unit for image classification based on geographic vector agents (GVAs) / Kambiz Borna in Transactions in GIS, vol 20 n° 3 (June 2016)  

Public [article]  inTransactions in GIS > vol 20 n° 3 (June 2016) . - pp 368–381 Titre : An intelligent geospatial processing unit for image classification based on geographic vector agents (GVAs) Type de document : Article/Communication Auteurs : Kambiz Borna, Auteur ; Antoni B. Moore, Auteur ; Pascal Sirguey, Auteur Année de publication : 2016 Article en page(s) : pp 368–381 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] agent (intelligence artificielle) [Termes IGN] analyse d'image orientée objet [Termes IGN] classification automatique [Termes IGN] données lidar [Termes IGN] données vectorielles [Termes IGN] image Ikonos [Termes IGN] modèle orienté agent Résumé : (auteur) Spatial modeling methods usually use pixels and image objects as fundamental processing units to address real-world objects, geo-objects, in image space. To do this, both pixel-based and object-based approaches typically employ a linear two-staged workflow of segmentation and classification. Pixel-based methods segment a classified image to address geo-objects in image space. In contrast, object-based approaches classify a segmented image to identify geo-objects from raster datasets. These methods lack the ability to simultaneously integrate the geometry and theme of geo-objects in image space. This article explores Geographical Vector Agents (GVAs) as an automated and intelligent processing unit to directly address real-world objects in the process of remote sensing image classification. The GVA is a distinct type of geographic automata characterized by elastic geometry, dynamic internal structure, neighborhoods and their respective rules. We test this concept by modeling a set of objects on a subset IKONOS image and LiDAR DSM datasets without the setting parameters (e.g. scale, shape information), usually applied in conventional Geographic Object-Based Image Analysis (GEOBIA) approaches. The results show that the GVA approach achieves more than 3.5% improvement for correctness, 2% improvement for quality, although no significant improvement for completeness to GEOBIA, thus demonstrating the competitive performance of GVAs classification. Numéro de notice : A2016-460 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12226 En ligne : http://dx.doi.org/10.1111/tgis.12226 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81390 [article]

Adaptive relative motion representation of space–time trajectories / Antoni B. Moore in Cartographic journal (the), Vol 52 n° 2 (May 2015)  

Public [article]  inCartographic journal (the) > Vol 52 n° 2 (May 2015) . - pp 204 - 209 Titre : Adaptive relative motion representation of space–time trajectories Type de document : Article/Communication Auteurs : Antoni B. Moore, Auteur ; Juddy Rodda, Auteur Année de publication : 2015 Article en page(s) : pp 204 - 209 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] algorithme du recuit simulé [Termes IGN] généralisation cartographique automatisée [Termes IGN] matrice [Termes IGN] représentation spatiale Résumé : (Auteur) Many devices are now geared towards collecting spatiotemporal data on a massive scale. Trajectory data of objects form a large component of this resource and even the smaller trajectory datasets are a representational challenge for cartography. We present a method that regularizes mapped trajectory data into an object × time interval matrix to better compare the direction characteristics of objects. We use a simulated annealing method to optimize the order of object rows at a specific time interval so that objects that are close together in space tend to be close together in the matrix. We also graphically represent the distance between objects and the general direction the object is travelling in the matrix, which is called Adaptive Relative Motion (ARM). Finally, we demonstrate the implementation of ARM through a case study of dolphin trajectories. Numéro de notice : A2015-766 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00087041.2015.1119463 En ligne : http://dx.doi.org/10.1080/00087041.2015.1119463 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78804 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
030-2015021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Exploring the hidden potential of common spatial data models to visualize uncertainty / J. Kardos in Cartography and Geographic Information Science, vol 32 n° 4 (October 2005)  

Public [article]  inCartography and Geographic Information Science > vol 32 n° 4 (October 2005) . - pp 359 - 367 Titre : Exploring the hidden potential of common spatial data models to visualize uncertainty Type de document : Article/Communication Auteurs : J. Kardos, Auteur ; Antoni B. Moore, Auteur ; G.L. Benwell, Auteur Année de publication : 2005 Article en page(s) : pp 359 - 367 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] arbre quadratique [Termes IGN] incertitude des données [Termes IGN] modèle conceptuel de données localisées [Termes IGN] structure de données localisées [Termes IGN] visualisation Résumé : (Auteur) Common Spatial Data Models (SDMs) such the vector, raster, and quadtree have well understood and widely practiced conventions of storage and visualization. This paper explores what happens when the conventions of visualization are not strictly adhered to, and the SDMs are used in an atypical fashion. A framework based on a quasi similarity measure is presented, which quantifies (in terras of "distance") the relationship between the storage format and the visualization output, following an accepted protocol. This research used a transformation process (Tp) to define this distance. Then, the atypical use of the quadtree SDM to represent choropleth spatial boundary uncertainty and attribute uncertainty was quantified using the same framework. This research shows that if a SDM is used outside of its original context, then the distance between the storage format and its visual output can alter; in our case, the distance decreased. This result was interpreted as evidence for the creation of a new spatial data structure. The formalization of the relationship between an SDM and its visual output will be valuable for future exploration of the non-conventional visualization of common SDMs. Numéro de notice : A2005-538 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1559/152304005775194827 En ligne : https://doi.org/10.1559/152304005775194827 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27674 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-05041	RAB	Revue	Centre de documentation	En réserve L003	Disponible