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Dépouillements

Feasibility of the space-time cube in temporal cultural landscape visualization / Edyta P. Bogucka in ISPRS International journal of geo-information, vol 7 n° 6 (June 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 6 (June 2018) Titre : Feasibility of the space-time cube in temporal cultural landscape visualization Type de document : Article/Communication Auteurs : Edyta P. Bogucka, Auteur ; Mathias Jahnke, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cube espace-temps [Termes IGN] données spatiotemporelles [Termes IGN] oculométrie [Termes IGN] patrimoine culturel [Termes IGN] site historique [Termes IGN] système d'information géographique [Termes IGN] Varsovie (Pologne) [Termes IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Change acts as an inherent characteristic of the landscape, and expresses dynamic interactions between its tangible and intangible elements. While the documentation and analysis of spatiotemporal patterns have been broadly discussed, major challenges concern the design of task-oriented, user-friendly landscape visualizations. Geographic information system (GIS) techniques and approaches from visual analytics may bring solutions to those questions. This paper considers the milestone documents for the representation of cultural heritage, and proposes a workflow for assessing the feasibility of the space–time cube concept in landscape representation. The usability of the visualization was examined during the interview with domain experts and potential interdisciplinary users. The evaluation session covered benchmark tasks, feedback, and eye-tracking. The performance of the space–time cube was compared with another spatiotemporal visualization technique and measured in terms of correctness, response time, and satisfaction. The Royal Castle in Warsaw, which was registered in 1980 as a part of Warsaw’s World Heritage Site of United Nations Educational, Scientific and Cultural Organization (UNESCO), served as the case study. The user tests show that the designed space–time cube excels for the completion rate; however, more time is required to provide answers to question tasks focusing on comparisons. Together, the case study and feedback from domain experts and participants demonstrate the benefit of the space–time cube concept in designing landscape visualizations. Numéro de notice : A2018-344 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7060209 Date de publication en ligne : 31/05/2018 En ligne : https://doi.org/10.10.3390/ijgi7060209 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90566 [article]

A simple line clustering method for spatial analysis with origin-destination data and its application to bike-sharing movement data / Biao He in ISPRS International journal of geo-information, vol 7 n° 6 (June 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 6 (June 2018) Titre : A simple line clustering method for spatial analysis with origin-destination data and its application to bike-sharing movement data Type de document : Article/Communication Auteurs : Biao He, Auteur ; Zhang Yan, Auteur ; Yu Chen, Auteur ; Zhihui Gu, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] analyse spatio-temporelle [Termes IGN] bicyclette [Termes IGN] entropie [Termes IGN] extraction de modèle [Termes IGN] origine - destination [Termes IGN] raisonnement spatial [Termes IGN] voisinage (relation topologique) Résumé : (Auteur) Clustering methods are popular tools for pattern recognition in spatial databases. Existing clustering methods have mainly focused on the matching and clustering of complex trajectories. Few studies have paid attention to clustering origin-destination (OD) trips and discovering strong spatial linkages via OD lines, which is useful in many areas such as transportation, urban planning, and migration studies. In this paper, we present a new Simple Line Clustering Method (SLCM) that was designed to discover the strongest spatial linkage by searching for neighboring lines for every OD trip within a certain radius. This method adopts entropy theory and the probability distribution function for parameter selection to ensure significant clustering results. We demonstrate this method using bike-sharing location data in a metropolitan city. Results show that (1) the SLCM was significantly effective in discovering clusters at different scales, (2) results with the SLCM analysis confirmed known structures and discovered unknown structures, and (3) this approach can also be applied to other OD data to facilitate pattern extraction and structure understanding. Numéro de notice : A2018-345 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7060203 Date de publication en ligne : 29/05/2018 En ligne : https://doi.org/10.10.3390/ijgi7060203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90568 [article]

Influence of sample size on automatic positional accuracy assessment methods for urban areas / Francisco Javier Ariza-López in ISPRS International journal of geo-information, vol 7 n° 6 (June 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 6 (June 2018) Titre : Influence of sample size on automatic positional accuracy assessment methods for urban areas Type de document : Article/Communication Auteurs : Francisco Javier Ariza-López, Auteur ; Juan J. Ruiz-Lendínez, Auteur ; Manuel A. Ureña-Cámara, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données urbaines [Termes IGN] distance de Kolmogorov-Smirnov [Termes IGN] échantillon [Termes IGN] polygone [Termes IGN] précision de localisation [Termes IGN] précision planimétrique [Termes IGN] qualité des données [Termes IGN] zone urbaine Résumé : (Auteur) In recent years, new approaches aimed to increase the automation level of positional accuracy assessment processes for spatial data have been developed. However, in such cases, an aspect as significant as sample size has not yet been addressed. In this paper, we study the influence of sample size when estimating the planimetric positional accuracy of urban databases by means of an automatic assessment using polygon-based methodology. Our study is based on a simulation process, which extracts pairs of homologous polygons from the assessed and reference data sources and applies two buffer-based methods. The parameter used for determining the different sizes (which range from 5 km up to 100 km) has been the length of the polygons’ perimeter, and for each sample size 1000 simulations were run. After completing the simulation process, the comparisons between the estimated distribution functions for each sample and population distribution function were carried out by means of the Kolmogorov–Smirnov test. Results show a significant reduction in the variability of estimations when sample size increased from 5 km to 100 km. Numéro de notice : A2018-346 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7060200 Date de publication en ligne : 28/05/2018 En ligne : https://doi.org/10.3390/ijgi7060200 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90570 [article]