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Sensing urban soundscapes from street view imagery / Tianhong Zhao in Computers, Environment and Urban Systems, vol 99 (January 2023)  

Public [article]  inComputers, Environment and Urban Systems > vol 99 (January 2023) . - n° 101915 Titre : Sensing urban soundscapes from street view imagery Type de document : Article/Communication Auteurs : Tianhong Zhao, Auteur ; Xiucheng Liang, Auteur ; Wei Tu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101915 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond [Termes IGN] bruit (audition) [Termes IGN] distribution spatiale [Termes IGN] image Streetview [Termes IGN] paysage sonore [Termes IGN] planification urbaine [Termes IGN] pollution acoustique [Termes IGN] Shenzhen [Termes IGN] Singapour [Termes IGN] ville durable [Vedettes matières IGN] Géovisualisation Résumé : (auteur) A healthy acoustic environment is an essential component of sustainable cities. Various noise monitoring and simulation techniques have been developed to measure and evaluate urban sounds. However, sensing large areas at a fine resolution remains a great challenge. Based on machine learning, we introduce a new application of street view imagery — estimating large-area high-resolution urban soundscapes, investigating the premise that we can predict and characterize soundscapes without laborious and expensive noise measurements. First, visual features are extracted from street-level imagery using computer vision. Second, fifteen soundscape indicators are identified and a survey is conducted to gauge them solely from images. Finally, a prediction model is constructed to infer the urban soundscape by modeling the non-linear relationship between them. The results are verified with extensive field surveys. Experiments conducted in Singapore and Shenzhen using half a million images affirm that street view imagery enables us to sense large-scale urban soundscapes with low cost but high accuracy and detail, and provides an alternative means to generate soundscape maps. reaches 0.48 by evaluating the predicted results with field data collection. Further novelties in this domain are revealing the contributing visual elements and spatial laws of soundscapes, underscoring the usability of crowdsourced data, and exposing international patterns in perception. Numéro de notice : A2023-014 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101915 Date de publication en ligne : 20/11/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101915 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102131 [article]

Adaptive transfer of color from images to maps and visualizations / Mingguang Wu in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)  

Public [article]  inCartography and Geographic Information Science > Vol 49 n° 4 (July 2022) . - pp 289 - 312 Titre : Adaptive transfer of color from images to maps and visualizations Type de document : Article/Communication Auteurs : Mingguang Wu, Auteur ; Yanjie Sun, Auteur ; Yaqian Li, Auteur Année de publication : 2022 Article en page(s) : pp 289 - 312 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] amélioration des couleurs [Termes IGN] couleur (rédaction cartographique) [Termes IGN] données vectorielles [Termes IGN] esthétique cartographique [Termes IGN] orthoimage couleur [Termes IGN] relation sémantique [Termes IGN] saillance [Termes IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Because crafting attractive and effective colors from scratch is a high-effort and time-consuming process in map and visualization design, transferring color from an inspiration source to maps and visualizations is a promising technique for both novices and experts. To date, existing image-to-image color transfer methods suffer from ambiguities and inconsistencies; no computational approach is available to transfer color from arbitrary images to vector maps. To fill this gap, we propose a computational method that transfers color from arbitrary images to a vector map. First, we classify reference images into regions with measures of saliency. Second, we quantify the communicative quality and esthetics of colors in maps; we then transform the problem of color transfer into a dual-objective, multiple-constraint optimization problem. We also present a solution method that can create a series of optimal color suggestions and generate a communicative quality-esthetic compromise solution. We compare our method with an image-to-image method based on two sample maps and six reference images. The results indicate that our method is adaptive to mapping scales, themes, and regions. The evaluation also provides preliminary evidence that our method can achieve better communicative quality and harmony. Numéro de notice : A2022-478 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2021.1982009 Date de publication en ligne : 10/11/2021 En ligne : https://doi.org/10.1080/15230406.2021.1982009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100826 [article]

Interactive visual analytics of moving passenger flocks using massive smart card data / Tong Zhang in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)  

Public [article]  inCartography and Geographic Information Science > Vol 49 n° 4 (July 2022) . - pp 354 - 369 Titre : Interactive visual analytics of moving passenger flocks using massive smart card data Type de document : Article/Communication Auteurs : Tong Zhang, Auteur ; Wei He, Auteur ; Jing Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 354 - 369 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatiale [Termes IGN] analyse visuelle [Termes IGN] carte à puce [Termes IGN] données massives [Termes IGN] mobilité urbaine [Termes IGN] objet mobile [Termes IGN] Shenzhen [Termes IGN] trajet (mobilité) [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Understanding urban mobility patterns is constrained by our limited capabilities to extract and visualize spatio-temporal regularities from large amounts of mobility data. Moving flocks, defined as groups of people traveling along over a pre-defined time duration, can reveal collective moving patterns at aggregated spatio-temporal scales, thereby facilitating the discovery of urban mobility structure and travel demand patterns. In this study, we extend classical trajectory-oriented flock mining algorithms to discover moving flocks of transit passengers, accounting for the constraints of multi-modal transit networks. We develop a map-centered visual analytics approach by integrating the flock mining algorithm with interactive visualization designs of discovered flocks. Novel interactive visualizations are designed and implemented to support the exploration and analyses of discovered moving flocks at different spatial and temporal scales. The visual analytics approach is evaluated using a real-world smart card dataset collected in Shenzhen City, China, validating its applicability in capturing and mapping dynamic mobility patterns over a large metropolitan area. Numéro de notice : A2022-480 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2022.2039775 Date de publication en ligne : 09/03/2022 En ligne : https://doi.org/10.1080/15230406.2022.2039775 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100886 [article]

Visualising post-disaster damage on maps: a user study / Thomas Candela in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 7 (juillet 2022) . - pp 1364 - 1393 Titre : Visualising post-disaster damage on maps: a user study Type de document : Article/Communication Auteurs : Thomas Candela, Auteur ; Matthieu Péroche, Auteur ; Arnaud Sallaberry, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1364 - 1393 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de répartition par points [Termes IGN] catastrophe naturelle [Termes IGN] comportement [Termes IGN] dommage matériel [Termes IGN] enquête [Termes IGN] lecture de carte [Termes IGN] oculométrie [Termes IGN] psychologie cognitive [Termes IGN] représentation cartographique [Termes IGN] sémiologie graphique [Termes IGN] tessellation [Vedettes matières IGN] Géovisualisation Résumé : (auteur) The mapping of the damage caused by natural disasters is a crucial step in deciding on the actions to take at the international, national, and local levels. The large variety of representations that we have observed leads to problems of transfer and variations in analysis. In this article, we propose a representation, Regular Dot map (RD), and we compare it to 4 others routinely used to visualise post-disaster damage. Our comparison is based on a user study in which a set of participants carried out various tasks on multiple datasets using the various visualisations. We then analysed the behaviour during the experiment using three approaches: (1) quantitative analysis of user answers according to the reality on the ground, (2) quantitative analysis of user preferences in terms of perceived effectiveness and appearance, and (3) qualitative analysis of the data collected using an eye tracker. The results of this study lead us to believe that RD is the best compromise in terms of effectiveness among the various representations studied. Numéro de notice : A2022-492 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2063872 Date de publication en ligne : 19/04/2022 En ligne : https://doi.org/10.1080/13658816.2022.2063872 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100971 [article]

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Self-organizing maps as a dimension reduction approach for spatial global sensitivity analysis visualization / Seda Şalap-Ayça in Transactions in GIS, vol 26 n° 4 (June 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 4 (June 2022) . - pp 1718 - 1734 Titre : Self-organizing maps as a dimension reduction approach for spatial global sensitivity analysis visualization Type de document : Article/Communication Auteurs : Seda Şalap-Ayça, Auteur Année de publication : 2022 Article en page(s) : pp 1718 - 1734 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement [Termes IGN] analyse de sensibilité [Termes IGN] carte de Kohonen [Termes IGN] représentation spatiale [Termes IGN] réseau neuronal artificiel [Termes IGN] visualisation cartographique [Termes IGN] voisinage (relation topologique) [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Spatial global sensitivity analysis (SGSA) reveals and ranks the input–output relation in spatial models. The SGSA output is twofold: (1) first-order effects which are the linear relations of every input layer with the output; and (2) high-order effects where the nonlinear interaction among input layers is depicted. The resulting sensitivity maps are twice the number of input layers which is challenging to visualize, considering the limitations of the human cognitive system or visual representations. Finding similar patterns and projecting that similarity into a 2D surface will help to tackle this voluminous visual load. This article presents the implementation of self-organizing maps (SOM), a type of artificial neural network, as a dimension reduction approach for SGSA visualization. SOM is also used for feature selection to identify the most relevant feature for model uncertainty. The winning neurons at SOM are projected as the influence map and the results are compared with conventional visualization techniques. Numéro de notice : A2022-532 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12963 Date de publication en ligne : 21/06/2022 En ligne : https://doi.org/10.1111/tgis.12963 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101080 [article]

Proxemic maps for immersive visualization / Zeinab Ghaemi in Cartography and Geographic Information Science, vol 49 n° 3 (May 2022)  

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Detecting individuals' spatial familiarity with urban environments using eye movement data / Hua Liao in Computers, Environment and Urban Systems, vol 93 (April 2022)  

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A GAN-based approach toward architectural line drawing colorization prototyping / Qian (Chayn) Sun in The Visual Computer, vol 38 n° 4 (April 2022)  

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Neural map style transfer exploration with GANs / Sidonie Christophe in International journal of cartography, vol 8 n° 1 (March 2022)  

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Possibilities for assessment and geovisualization of spatial and temporal water quality data using a webGIS application / Daniel Balla in ISPRS International journal of geo-information, vol 11 n° 2 (February 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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3D geovisualization for visual analysis of urban climate / Sidonie Christophe in Cybergeo, European journal of geography, vol 2022 ([01/01/2022])  

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Visualisation spatio-temporelle de données COVID-19 / Aymeric Dutremble (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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La géovisualisation de données massives sur le Web : entre avancées technologiques et évolutions cartographiques / Boris Mericskay in Mappemonde, n° 131 (juillet 2021)  

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