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Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data / Yi Qiang in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2434 - 2450 Titre : Empirical assessment of road network resilience in natural hazards using crowdsourced traffic data Type de document : Article/Communication Auteurs : Yi Qiang, Auteur ; Jinwen Xu, Auteur Année de publication : 2020 Article en page(s) : pp 2434 - 2450 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] étude empirique [Termes descripteurs IGN] Google Maps [Termes descripteurs IGN] Ohio (Etats-Unis) [Termes descripteurs IGN] participation du public [Termes descripteurs IGN] réseau routier [Termes descripteurs IGN] résilience [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] trafic routier Résumé : (auteur) Climate change and natural hazards pose great threats to road transport systems which are ‘lifelines’ of human society. However, there is generally a lack of empirical data and approaches for assessing resilience of road networks in real hazard events. This study introduces an empirical approach to evaluate road network resilience using crowdsourced traffic data in Google Maps. Based on the conceptualization of resilience and the Hansen accessibility index, resilience of road network is measured from accumulated accessibility reduction over time during a hazard. The utility of this approach is demonstrated in a case study of the Cleveland metropolitan area (Ohio) in Winter Storm Harper. The results reveal strong spatial variations of the disturbance and recovery rate of road network performance during the hazard. The major findings of the case study are: (1) longer distance travels have higher increasing ratios of travel time during the hazard; (2) communities with low accessibility at the normal condition have lower road network resilience; (3) spatial clusters of low resilience are identified, including communities with low socio-economic capacities. The introduced approach provides ground-truth validation for existing quantitative models and supports disaster management and transportation planning to reduce hazard impacts on road network. Numéro de notice : A2020-691 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1694681 date de publication en ligne : 25/11/2020 En ligne : https://doi.org/10.1080/13658816.2019.1694681 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96229 [article]

Fifty shades of Roboto: text design choices and categories in multi-scale maps / Sébastien Biniek (2019)    

Public Titre : Fifty shades of Roboto: text design choices and categories in multi-scale maps Type de document : Article/Communication Auteurs : Sébastien Biniek , Auteur ; Guillaume Touya , Auteur ; Gilles Rouffineau, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2019 Autre Editeur : Göttingen : Copernicus publications Collection : Advances in cartography and GIScience Projets : 1-Pas de projet / Conférence : ICC 2019, 29th International Cartographic Conference ICA, Mapping everything for everyone 15/07/2019 20/07/2019 Tokyo Japon Open Access Advances ... of the ICA Importance : 8 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes descripteurs IGN] 1:30.000 [Termes descripteurs IGN] 1:40.000 [Termes descripteurs IGN] composition typographique [Termes descripteurs IGN] conception cartographique [Termes descripteurs IGN] géoportail BRGM-IGN [Termes descripteurs IGN] Google Maps [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] placement automatique des écritures [Termes descripteurs IGN] sémiologie graphique Résumé : (auteur) The impetus induced by the development of multi-scale, multi-style maps calls for thinking our resources and protocols with greater interoperability. In the field of toponymy, this requires, in particular, thinking of categories and their structuring with more granularity. Assuming that typography, as a device for visualizing toponyms, is a tool whose potential is still under-exploited, we ask ourselves how the field of typographic design can improve our understanding of toponymic categories and help to structure them in a multi-scale logic. The approach adopted to answer this question is to analyse several existing maps to find good and bad practices. We identified different styles of place names and we built a typology of text features in the surveyed maps. The surveyed maps are the 1 : 35 000 scale, in IGN-France, OSM and GoogleMaps portals. Numéro de notice : C2019-012 Affiliation des auteurs : LaSTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-adv-1-2-2019 date de publication en ligne : 03/07/2019 En ligne : http://dx.doi.org/10.5194/ica-adv-1-2-2019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93260

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Urban impervious surface estimation from remote sensing and social data / Yan Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 12 (December 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 12 (December 2018) . - pp 771 - 780 Titre : Urban impervious surface estimation from remote sensing and social data Type de document : Article/Communication Auteurs : Yan Yu, Auteur ; Jun Li, Auteur ; Changyu Zhu, Auteur ; Antonio J. Plaza, Auteur Année de publication : 2018 Article en page(s) : pp 771 - 780 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse des mélanges spectraux [Termes descripteurs IGN] base de données routières [Termes descripteurs IGN] Canton (Kouangtoung) [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] données vectorielles [Termes descripteurs IGN] Google Maps [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] régression multiple [Termes descripteurs IGN] réseau routier [Termes descripteurs IGN] surface imperméable [Termes descripteurs IGN] zone urbaine Résumé : (auteur) We propose an inspiring approach for accurate impervious surface estimation based on the integration of remote sensing and social data. The proposed approach exploits the strengths of two kind of heterogeneous features, i.e., physical features and social features, where the former ones are derived by a morphological attribute profiles-guided spectral mixture analysis model using remote sensing imagery, and the latter ones are obtained from the normalized kernel density of point of interest and vector road datasets. These two features are then integrated using a multivariable linear regression model to estimate impervious surfaces. The proposed method has been tested in the main urban area of Guangzhou, China, in pixel level and parcel level, respectively. The obtained results, with the overall RMSE of 10.98% and 10.90% for pixel level and parcel level, respectively, demonstrate the good performance of integrating remote sensing imagery and social data for mapping of urban impervious surface. Numéro de notice : A2018-549 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.12.771 date de publication en ligne : 01/12/2018 En ligne : https://doi.org/10.14358/PERS.84.12.771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91622 [article]

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Measured and perceived visual complexity : a comparative study among three online map providers / Susan Schnur in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 3 (May 2018) . - pp 238 - 254 Titre : Measured and perceived visual complexity : a comparative study among three online map providers Type de document : Article/Communication Auteurs : Susan Schnur, Auteur ; Kenan Bektas, Auteur ; Arzu Çöltekin, Auteur Année de publication : 2018 Article en page(s) : pp 238 - 254 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Bing Maps [Termes descripteurs IGN] complexité de la carte [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] Google Maps [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] perception [Termes descripteurs IGN] utilisateur Résumé : (Auteur) We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use. Numéro de notice : A2018-131 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2017.1323676 date de publication en ligne : 06/06/2017 En ligne : https://doi.org/10.1080/15230406.2017.1323676 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89663 [article]

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From Google Maps to a fine-grained catalog of street trees / Steve Branson in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 135 (January 2018) . - pp 13 - 30 Titre : From Google Maps to a fine-grained catalog of street trees Type de document : Article/Communication Auteurs : Steve Branson, Auteur ; Jan Dirk Wegner, Auteur ; David Hall, Auteur ; Nico Lang, Auteur ; Konrad Schindler, Auteur ; Pietro Perona, Auteur Année de publication : 2018 Article en page(s) : pp 13 - 30 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] architecture pipeline [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] Google Maps [Termes descripteurs IGN] inventaire de la végétation [Termes descripteurs IGN] Pasadena [Termes descripteurs IGN] photo-interprétation assistée par ordinateur [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] ville Résumé : (Auteur) Up-to-date catalogs of the urban tree population are of importance for municipalities to monitor and improve quality of life in cities. Despite much research on automation of tree mapping, mainly relying on dedicated airborne LiDAR or hyperspectral campaigns, tree detection and species recognition is still mostly done manually in practice. We present a fully automated tree detection and species recognition pipeline that can process thousands of trees within a few hours using publicly available aerial and street view images of Google MapsTM. These data provide rich information from different viewpoints and at different scales from global tree shapes to bark textures. Our work-flow is built around a supervised classification that automatically learns the most discriminative features from thousands of trees and corresponding, publicly available tree inventory data. In addition, we introduce a change tracker that recognizes changes of individual trees at city-scale, which is essential to keep an urban tree inventory up-to-date. The system takes street-level images of the same tree location at two different times and classifies the type of change (e.g., tree has been removed). Drawing on recent advances in computer vision and machine learning, we apply convolutional neural networks (CNN) for all classification tasks. We propose the following pipeline: download all available panoramas and overhead images of an area of interest, detect trees per image and combine multi-view detections in a probabilistic framework, adding prior knowledge; recognize fine-grained species of detected trees. In a later, separate module, track trees over time, detect significant changes and classify the type of change. We believe this is the first work to exploit publicly available image data for city-scale street tree detection, species recognition and change tracking, exhaustively over several square kilometers, respectively many thousands of trees. Experiments in the city of Pasadena, California, USA show that we can detect >70% of the street trees, assign correct species to >80% for 40 different species, and correctly detect and classify changes in >90% of the cases. Numéro de notice : A2018-068 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.11.008 date de publication en ligne : 20/11/2017 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.11.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89426 [article]

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Utilisation de données satellites dans le combat contre l'esclavage moderne / Florent Negrel-Teodori (2017) 

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Voyage au pays des apps / Françoise de Blomac in DécryptaGéo le mag, n° 177 (mai 2016)

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Beyond the basemap / Matt Toon in GEO: Geoconnexion international, vol 14 n° 7 (July 2015)

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Android 5 / Nazim Benbourahla (2015)

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A comparative analysis of routes generated by Web Mapping APIs / Monsak Socharoentum in Cartography and Geographic Information Science, Vol 42 n° 1 (January 2015)  

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La cartographie numérique / Jean-Christophe Plantin (2014)

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The universal map / Matt Toon in GEO: Geoconnexion international, vol 12 n° 6 (june 2013)

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Mise à jour et modernisation d'un index géographique national en ligne / Elias Couppe (2013) 

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PlotGoogleMaps: The R-based web-mapping tool for thematic spatial data / M. Kilibarda in Geomatica, vol 66 n° 1 (March 2012)

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Home energy assessment technologies / G. Hay in GIM international, vol 24 n° 3 (March 2010)

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