Centre de documentation
scientifique

Un algorithme pour battre le record du SwissTrainChallenge : poser le pied dans chacun des 26 cantons le plus rapidement possible en utilisant uniquement des transports publics / Emmanuel Clédat in XYZ, n° 157 (décembre 2018 - février 2019)

Public [article]  inXYZ > n° 157 (décembre 2018 - février 2019) . - pp 30 - 36 Titre : Un algorithme pour battre le record du SwissTrainChallenge : poser le pied dans chacun des 26 cantons le plus rapidement possible en utilisant uniquement des transports publics Type de document : Article/Communication Auteurs : Emmanuel Clédat , Auteur ; Dirk Lauinger, Auteur Année de publication : 2018 Article en page(s) : pp 30 - 36 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] calcul d'itinéraire [Termes IGN] chemin le plus rapide, algorithme du [Termes IGN] connexité (graphes) [Termes IGN] durée de trajet [Termes IGN] multilatération [Termes IGN] programmation linéaire [Termes IGN] réseau ferroviaire [Termes IGN] Suisse [Termes IGN] train [Termes IGN] transport public [Termes IGN] vitesse Résumé : (auteur) The Swiss Train Challenge is to set foot in all 26 cantons of Switzerland in as little time as possible, using only public transportation. Relying on human intuition informed by a geographical information system to select the relevant train stations, and on computational power to solve the resulting mixed-integer linear optimization problem, we find a solution that beats the current record of 17 hours and 19 minutes, by 25 minutes. When testing our itinerary in practice, we made all connections but one for which the arriving train was 20 minutes delayed - a rare event in switzerland. This is the first time that an algorithm has been used to calculate the Swiss Train Challenge itinerary. Numéro de notice : A2018-532 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91577 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
112-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

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 IGN] analyse des mélanges spectraux [Termes IGN] base de données routières [Termes IGN] Canton (Kouangtoung) [Termes IGN] contenu généré par les utilisateurs [Termes IGN] données issues des réseaux sociaux [Termes IGN] données localisées des bénévoles [Termes IGN] données vectorielles [Termes IGN] Google Maps [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] OpenStreetMap [Termes IGN] point d'intérêt [Termes IGN] régression multiple [Termes IGN] réseau routier [Termes IGN] surface imperméable [Termes 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]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2018121	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Using Network Segments in the Visualization of Urban Isochrones / Jeff Allen in Cartographica, vol 53 n° 4 (Winter 2018)  

Public [article]  inCartographica > vol 53 n° 4 (Winter 2018) . - pp 262 - 270 Titre : Using Network Segments in the Visualization of Urban Isochrones Type de document : Article/Communication Auteurs : Jeff Allen, Auteur Année de publication : 2018 Article en page(s) : pp 262 - 270 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] accessibilité [Termes IGN] carte de zones isochrones [Termes IGN] cartographie urbaine [Termes IGN] données localisées [Termes IGN] données ouvertes [Termes IGN] mobilité urbaine [Termes IGN] OpenStreetMap [Termes IGN] QGIS [Termes IGN] réseau de transport [Termes IGN] Toronto [Termes IGN] transport urbain [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Since the early twentieth century, thematic mapping techniques such as isochrones have been used for visualizing the accessibility and mobility provided by urban transportation networks. These maps typically depict the area accessible from a point within a certain time or distance threshold. This article details a design alternative to conventional isochrones, which links travel times to network edges. Benefits of this technique include highlighting the network structure of transport networks and comparing travel times for different travel scenarios. This article details methods for producing these maps using free and open-source data and software and provides examples of visualizing different accessibility scenarios in Toronto, Canada. Numéro de notice : A2018-576 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Numéro de périodique DOI : 10.3138/cart.53.4.2018-0013 Date de publication en ligne : 20/02/2019 En ligne : https://doi.org/10.3138/cart.53.4.2018-0013 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92305 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
031-2018041	SL	Revue	Centre de documentation	Revues en salle	Disponible

Multi-scale object detection in remote sensing imagery with convolutional neural networks / Zhipeng Deng in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part A (November 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 145 - part A (November 2018) . - pp 3 - 22 Titre : Multi-scale object detection in remote sensing imagery with convolutional neural networks Type de document : Article/Communication Auteurs : Zhipeng Deng, Auteur ; Hao Sun, Auteur ; Shilin Zhou, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 3 - 22 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] aéroport [Termes IGN] détection d'objet [Termes IGN] image aérienne [Termes IGN] image optique [Termes IGN] image Sentinel-SAR [Termes IGN] réseau neuronal convolutif [Termes IGN] ville Résumé : (Auteur) Automatic detection of multi-class objects in remote sensing images is a fundamental but challenging problem faced for remote sensing image analysis. Traditional methods are based on hand-crafted or shallow-learning-based features with limited representation power. Recently, deep learning algorithms, especially Faster region based convolutional neural networks (FRCN), has shown their much stronger detection power in computer vision field. However, several challenges limit the applications of FRCN in multi-class objects detection from remote sensing images: (1) Objects often appear at very different scales in remote sensing images, and FRCN with a fixed receptive field cannot match the scale variability of different objects; (2) Objects in large-scale remote sensing images are relatively small in size and densely peaked, and FRCN has poor localization performance with small objects; (3) Manual annotation is generally expensive and the available manual annotation of objects for training FRCN are not sufficient in number. To address these problems, this paper proposes a unified and effective method for simultaneously detecting multi-class objects in remote sensing images with large scales variability. Firstly, we redesign the feature extractor by adopting Concatenated ReLU and Inception module, which can increases the variety of receptive field size. Then, the detection is preformed by two sub-networks: a multi-scale object proposal network (MS-OPN) for object-like region generation from several intermediate layers, whose receptive fields match different object scales, and an accurate object detection network (AODN) for object detection based on fused feature maps, which combines several feature maps that enables small and densely packed objects to produce stronger response. For large-scale remote sensing images with limited manual annotations, we use cropped image blocks for training and augment them with re-scalings and rotations. The quantitative comparison results on the challenging NWPU VHR-10 data set, aircraft data set, Aerial-Vehicle data set and SAR-Ship data set show that our method is more accurate than existing algorithms and is effective for multi-modal remote sensing images. Numéro de notice : A2018-488 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.003 Date de publication en ligne : 02/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91224 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018111	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018113	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018112	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

A cross-analysis framework for multi-source volunteered, crowdsourced, and authoritative geographic information : The case study of volunteered personal traces analysis against transport network data / Gloria Bordogna in Geo-spatial Information Science, vol 21 n° 3 (October 2018)  

Public [article]  inGeo-spatial Information Science > vol 21 n° 3 (October 2018) . - pp 257 - 271 Titre : A cross-analysis framework for multi-source volunteered, crowdsourced, and authoritative geographic information : The case study of volunteered personal traces analysis against transport network data Type de document : Article/Communication Auteurs : Gloria Bordogna, Auteur ; Steven Capelli, Auteur ; Daniele E. Ciriello, Auteur ; Guiseppe Psaila, Auteur Année de publication : 2018 Article en page(s) : pp 257 - 271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Bergame [Termes IGN] cadre conceptuel [Termes IGN] données hétérogènes [Termes IGN] données localisées de référence [Termes IGN] données localisées des bénévoles [Termes IGN] format JSON [Termes IGN] mobilité urbaine [Termes IGN] requête spatiale [Termes IGN] réseau de transport [Termes IGN] segmentation sémantique [Termes IGN] trace numérique Résumé : (Auteur) The paper discusses the need of a high-level query language to allow analysts, geographers and, in general, non-programmers to easily cross-analyze multi-source VGI created by means of apps, crowd-sourced data from social networks and authoritative geo-referenced data, usually represented as JSON data sets (nowadays, the de facto standard for data exported by social networks). Since an easy to use high-level language for querying and manipulating collections of possibly geo-tagged JSON objects is still unavailable, we propose a truly declarative language, named J-CO-QL, that is based on a well-defined execution model. A plug-in for a GIS permits to visualize geo-tagged data sets stored in a NoSQL database such as MongoDB; furthermore, the same plug-in can be used to write and execute J-CO-QL queries on those databases. The paper introduces the language by exemplifying its operators within a real study case, the aim of which is to understand the mobility of people in the neighborhood of Bergamo city. Cross-analysis of data about transportation networks and VGI from travelers is performed, by means of J-CO-QL language, capable to manipulate and transform, combine and join possibly geo-tagged JSON objects, in order to produce new possibly geo-tagged JSON objects satisfying users’ needs. Numéro de notice : A2018-646 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2017.1374703 Date de publication en ligne : 21/09/2018 En ligne : https://doi.org/10.1080/10095020.2017.1374703 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93316 [article]

A multi‐objective framework for analysis of road network vulnerability for relief facility location during flood hazards : A case study of relief location analysis in Bankura District, India / Omprakash Chakraborty in Transactions in GIS, vol 22 n° 5 (October 2018)  

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La campagne géodésique de SNCF Réseau pour la régénération de son infrastructure : de la préparation à la diffusion / Florian Birot in XYZ, n° 156 (septembre - novembre 2018)

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La cartographie mobile et le géoréférencement précis de réseaux souterrains / Garance Weller in XYZ, n° 156 (septembre - novembre 2018)

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Pedestrian network information extraction based on VGI / Xuejing Xie in Geomatica, vol 72 n° 3 (September 2018)  

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Sea-land interdependence in the global maritime network: the case of Australian port cities / Justin Berli in Networks and Spatial Economics, vol 18 n° 3 (September 2018)  

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Processing BIM and GIS models in practice: Experiences and recommendations from a geoBIM project in The Netherlands / Ken Arroyo Ohori in ISPRS International journal of geo-information, vol 7 n° 8 (August 2018)  

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The use of geomatic techniques to improve the management of metro infrastructure / Maria Amparo Núñez-Andrés in Survey review, vol 50 n° 362 (August 2018)  

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Aerial data acquisition for a digital railway / James Dunthorne in GIM international, vol 32 n° 4 (July - August 2018)  

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Altamétris : des drones et des rails / Anonyme in Géomatique expert, n° 122 (mai-juin 2018)

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A context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks / Shaohua Wang in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)  

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