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Overcoming challenges in developing more usable pedestrian navigation systems / Ioannis Delikostidis in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)  

Public [article]  inCartography and Geographic Information Science > Vol 43 n° 3 (June 2016) . - pp 189 - 207 Titre : Overcoming challenges in developing more usable pedestrian navigation systems Type de document : Article/Communication Auteurs : Ioannis Delikostidis, Auteur ; Corné P.J.M. Van Elzakker, Auteur ; Menno-Jan Kraak, Auteur Année de publication : 2016 Article en page(s) : pp 189 - 207 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] conception orientée utilisateur [Termes IGN] évaluation [Termes IGN] implémentation (informatique) [Termes IGN] interface utilisateur [Termes IGN] milieu urbain [Termes IGN] navigation pédestre Résumé : (Auteur) This article presents an overview of a research project focusing on improving the usability of pedestrian navigation systems by following a User-Centered Design (UCD) approach. One of the main problems with those systems is how to adequately support and enhance the spatial interactions of a traveler to new urban areas, which is crucial for successful self-orienting and wayfinding. The methodology employed allows for conceptualizing, implementing and evaluating research prototypes that aim to satisfy the special user requirements. Outlined in this article are the techniques designed and integrated in the developed prototype, the methods used for their evaluation through field-based studies and the challenges encountered during this process. New techniques with a measurable impact on the effectiveness, efficiency and satisfaction of navigation were tested and found to dramatically enhance the sense of personal geo-identification in new places. Examples of those techniques are landmark visibility indication, multi-path routing based on time availability, multi-perspective landmark photos and reverse overview + detail maps. Overall, the outcomes of this research verify the capacity of UCD to help overcoming current usability issues with pedestrian navigation systems. By demonstrating an effective UCD methodology and discussing the lessons learned, we intend to aid the development of next generation navigation appliances. Numéro de notice : A2016-164 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/15230406.2015.1031180 En ligne : https://doi.org/10.1080/15230406.2015.1031180 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80470 [article]

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From taxonomies to ontologies: formalizing generalization knowledge for on-demand mapping / Nicholas Gould in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)  

Public [article]  inCartography and Geographic Information Science > Vol 43 n° 3 (June 2016) . - pp 208 - 222 Titre : From taxonomies to ontologies: formalizing generalization knowledge for on-demand mapping Type de document : Article/Communication Auteurs : Nicholas Gould, Auteur ; William A Mackaness, Auteur Année de publication : 2016 Article en page(s) : pp 208 - 222 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] accident de la route [Termes IGN] carte sur mesure [Termes IGN] conception cartographique [Termes IGN] contenu généré par les utilisateurs [Termes IGN] généralisation cartographique [Termes IGN] langage de requête [Termes IGN] ontologie [Termes IGN] OWL [Termes IGN] taxinomie [Termes IGN] web mapping [Vedettes matières IGN] Généralisation Résumé : (Auteur) Automation of the cartographic design process is central to the delivery of bespoke maps via the web. In this paper, ontological modeling is used to explicitly represent and articulate the knowledge used in this decision-making process. A use case focuses on the visualization of road traffic accident data as a way of illustrating how ontologies provide a framework by which salient and contextual information can be integrated in a meaningful manner. Such systems are in anticipation of web-based services in which the user knows what they need, but do not have the cartographic ability to get what they want. Numéro de notice : A2016-165 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2015.1072737 En ligne : https://doi.org/10.1080/15230406.2015.1072737 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80471 [article]

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An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States / Jochen Wendel in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)  

Public [article]  inCartography and Geographic Information Science > Vol 43 n° 3 (June 2016) . - pp 233 - 249 Titre : An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States Type de document : Article/Communication Auteurs : Jochen Wendel, Auteur ; Barbara P. Buttenfield, Auteur ; Lauwrence V. Stanislawski, Auteur Année de publication : 2016 Article en page(s) : pp 233 - 249 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] classification dirigée [Termes IGN] classification non dirigée [Termes IGN] données hydrographiques [Termes IGN] Etats-Unis [Termes IGN] généralisation cartographique automatisée [Termes IGN] intégration de données [Termes IGN] système d'information géographique Résumé : (Auteur) Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification. Numéro de notice : A2016-166 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15230406.2015.1067829 En ligne : https://doi.org/10.1080/15230406.2015.1067829 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80472 [article]

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Grid pattern recognition in road networks using the C4.5 algorithm / Jing Tian in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)  

Public [article]  inCartography and Geographic Information Science > Vol 43 n° 3 (June 2016) . - pp 266 - 282 Titre : Grid pattern recognition in road networks using the C4.5 algorithm Type de document : Article/Communication Auteurs : Jing Tian, Auteur ; Zihan Song, Auteur ; Fei Gao, Auteur ; Feng Zhao, Auteur Année de publication : 2016 Article en page(s) : pp 266 - 282 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] apprentissage dirigé [Termes IGN] classification dirigée [Termes IGN] exploration de données géographiques [Termes IGN] grille [Termes IGN] reconnaissance de formes [Termes IGN] réseau routier Résumé : (Auteur) Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks. Numéro de notice : A2016-167 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15230406.2015.1062425 En ligne : https://doi.org/10.1080/15230406.2015.1062425 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80473 [article]

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