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Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 19 - 34 Titre : Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours Type de document : Article/Communication Auteurs : Amir Hossein Safaie, Auteur ; Heidar Rastiveis, Auteur ; Alireza Shams, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 19 - 34 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] arbre remarquable [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] sécurité routière [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] tessellation [Termes descripteurs IGN] transformation de Hough Résumé : (auteur) Trees are important road-side objects, and their geometric information plays an essential role in road studies and safety analyses. This paper proposes an efficient method for the automated creation of a road-side tree inventory using Mobile Terrestrial Lidar System (MTLS) point clouds. In the proposed method ground points are filtered through preprocessing to reduce processing time. Next, tree trunks are detected by performing a Hough Transform (HT) algorithm on several generated raster images from the point clouds. By initiating an approximate area of a tree’s foliage through a Voronoi Tessellation (VT) algorithm, the accurate boundary of the foliage is identified by applying Active Contour (AC) models. By extracting the points within this foliage boundary the geometric characteristics of each tree are obtained. This method was evaluated with two sample point clouds from different MTLS systems, and the algorithm correctly extracted all of the trees from both datasets. Additionally, comparing the calculated parameters with manually observed measures, the accuracy of the obtained geometric parameters were promising. Numéro de notice : A2021-206 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.026 date de publication en ligne : 14/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.026 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97183 [article]

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A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks / Bozhao Li in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 4 (April 2021) . - pp 717 - 740 Titre : A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks Type de document : Article/Communication Auteurs : Bozhao Li, Auteur ; Zhongliang Cai, Auteur ; Mengjun Kang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 717 - 740 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] appariement de cartes [Termes descripteurs IGN] chemin le plus court (algorithme) [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] réseau routier [Termes descripteurs IGN] taux d'échantillonnage [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] trajectoire [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Low-sampling-rate floating car data (FCD) are more challenging than those with high-sampling-rate FCD for map matching (MM) algorithms. Some MM algorithms for low-sampling-rate FCD lack sufficient efficiency nor accuracy, especially related to complex urban road networks. This paper proposes a new method named the trajectory restoration algorithm, which is based on geometry MM algorithms to ensure efficiency and accuracy. The proposed algorithm adopts the modified A* shortest path algorithm to reduce the number of function calls and fully considers road network topology and historical matched points to improve its accuracy. We test the efficiency and accuracy of the trajectory restoration algorithm with FCD data for the complex urban road networks in Beijing. The results have strong continuity which greatly improves the utilization of FCD. We show that the proposed algorithm outperforms related MM methods in efficiency and accuracy and its robustness to restore trajectories of both high and low sampling rates in complex urban road networks. Numéro de notice : A2021-269 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2020.1825721 date de publication en ligne : 20/10/2020 En ligne : https://doi.org/10.1080/13658816.2020.1825721 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97326 [article]

Evaluating the effectiveness of different cartographic design variants for influencing route choice / Stefan Fuest in Cartography and Geographic Information Science, vol 48 n° 2 (March 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 2 (March 2021) . - pp 169 - 185 Titre : Evaluating the effectiveness of different cartographic design variants for influencing route choice Type de document : Article/Communication Auteurs : Stefan Fuest, Auteur ; Susanne Grüner, Auteur ; Mark Vollrath, Auteur ; Monika Sester, Auteur Année de publication : 2021 Article en page(s) : pp 169 - 185 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes descripteurs IGN] comportement [Termes descripteurs IGN] conception cartographique [Termes descripteurs IGN] convivialité [Termes descripteurs IGN] itinéraire [Termes descripteurs IGN] représentation des détails topographiques [Termes descripteurs IGN] symbole graphique [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] visualisation cartographique Résumé : (Auteur) This paper addresses the suitability of different cartographic design variants for visually communicating recommended routes. We performed a user study, investigating the potential of six different design variants (color hue, distortion, length distortion, size, spacing, and symbols) for influencing route choice using cartographic visualization methods while recommending a longer, but less congested route. The visualizations for all design variants have been prepared in three different levels of intensity of modification (weak, medium, and strong). Although the input data (traffic density) is the same for all representation methods, variations are each visualized using different cartographic design principles. Our results showed that in general, for the majority of routing scenarios, the participants’ route choice has been significantly influenced toward choosing the recommended route – indicating that the modification of route visualizations does actually lead to a different route choice behavior. Results further revealed that for most variants, willingness to choose the recommended route increases with higher intensity of modification. While some of the design variants like symbols or length distortion have been found effective for recommending routes at all levels of intensity, others like size and spacing have not been found suitable. A comparison between route choices and estimated route characteristics suggested a close relationship between willingness to choose the recommended route and the characteristics participants associate with the representation. In particular, route visualizations that create an impression of faster, more convenient, or more fluent travel experience are more likely to influence route choice behavior. Numéro de notice : A2021-181 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1855251 date de publication en ligne : 06/01/2021 En ligne : https://doi.org/10.1080/15230406.2020.1855251 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97068 [article]

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Deep traffic light detection by overlaying synthetic context on arbitrary natural images / Jean Pablo Vieira de Mello in Computers and graphics, vol 94 n° 1 (February 2021)  

Public [article]  inComputers and graphics > vol 94 n° 1 (February 2021) . - pp 76 - 86 Titre : Deep traffic light detection by overlaying synthetic context on arbitrary natural images Type de document : Article/Communication Auteurs : Jean Pablo Vieira de Mello, Auteur ; Lucas Tabelini, Auteur ; Rodrigo F. Berriel, Auteur Année de publication : 2021 Article en page(s) : pp 76 - 86 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] échantillonnage d'image [Termes descripteurs IGN] feu de circulation [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] navigation autonome [Termes descripteurs IGN] signalisation routière [Termes descripteurs IGN] trafic routier Résumé : (auteur) Deep neural networks come as an effective solution to many problems associated with autonomous driving. By providing real image samples with traffic context to the network, the model learns to detect and classify elements of interest, such as pedestrians, traffic signs, and traffic lights. However, acquiring and annotating real data can be extremely costly in terms of time and effort. In this context, we propose a method to generate artificial traffic-related training data for deep traffic light detectors. This data is generated using basic non-realistic computer graphics to blend fake traffic scenes on top of arbitrary image backgrounds that are not related to the traffic domain. Thus, a large amount of training data can be generated without annotation efforts. Furthermore, it also tackles the intrinsic data imbalance problem in traffic light datasets, caused mainly by the low amount of samples of the yellow state. Experiments show that it is possible to achieve results comparable to those obtained with real training data from the problem domain, yielding an average mAP and an average F1-score which are each nearly 4 p.p. higher than the respective metrics obtained with a real-world reference model. Numéro de notice : A2021-151 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cag.2020.09.012 date de publication en ligne : 09/10/2020 En ligne : https://doi.org/10.1016/j.cag.2020.09.012 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97027 [article]

Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation / R. Yazdan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 18 - 35 Titre : Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation Type de document : Article/Communication Auteurs : R. Yazdan, Auteur ; M. Varshosaz, Auteur Année de publication : 2021 Article en page(s) : pp 18 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] base de données d'images [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] corrélation à l'aide de traits caractéristiques [Termes descripteurs IGN] corrélation croisée normalisée [Termes descripteurs IGN] couple stéréoscopique [Termes descripteurs IGN] détection automatique [Termes descripteurs IGN] modèle stéréoscopique [Termes descripteurs IGN] reconnaissance d'objets [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] signalisation routière [Termes descripteurs IGN] SURF (algorithme) [Termes descripteurs IGN] Téhéran [Termes descripteurs IGN] transformation de Hough [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Automatic detection and recognition of traffic signs have many applications. However, some problems can affect the accuracy of the existing algorithms, such as changes in environmental light conditions, shadows, the presence of objects of the same colour, significant changes in scale and rotation, as well as obstacles in front of the traffic signs. To overcome these difficulties, a reference image database is usually used that includes different modes of appearing the traffic signs in the images. In order to overcome the effects of scale and rotation, in this paper a new method is presented in which only one reference image is needed for each sign to recognise the traffic sign in an image. In the proposed method, imaging is done in stereo. Using the captured image pair, a virtual image is generated which is then used to recognise the sign. As a result, the recognition is carried out with a minimum number of reference images. Experiments show that the proposed algorithm significantly improves recognition results. The traffic signs are recognised with 93.1% accuracy that enjoys a 4.9% improvement over traditional methods. Numéro de notice : A2021-010 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.003 date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.003 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96304 [article]

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Inferencing hourly traffic volume using data-driven machine learning and graph theory / Zhiyan Yi in Computers, Environment and Urban Systems, vol 85 (January 2021)  

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Route intersection reduction with connected autonomous vehicles / Sadegh Motallebi in Geoinformatica [en ligne], vol 25 n° 1 (January 2021)  

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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)  

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Using multi-agent simulation to predict natural crossing points for pedestrians and choose locations for mid-block crosswalks / Egor Smirrnov in Geo-spatial Information Science, vol 23 n° 4 (December 2020)  

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Unfolding spatial-temporal patterns of taxi trip based on an improved network kernel density estimation / Boxi Shen in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)  

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A graph convolutional network model for evaluating potential congestion spots based on local urban built environments / Kun Qin in Transactions in GIS, Vol 24 n° 5 (October 2020)  

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Machine‐learning prediction models for pedestrian traffic flow levels: Towards optimizing walking routes for blind pedestrians / Achituv Cohen in Transactions in GIS, Vol 24 n° 5 (October 2020)  

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Network-constrained bivariate clustering method for detecting urban black holes and volcanoes / Qiliang Liu in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

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Measuring accessibility of bus system based on multi-source traffic data / Yufan Zuo in Geo-spatial Information Science, vol 23 n° 3 (September 2020)  

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Semi-automated framework for generating cycling lane centerlines on roads with roadside barriers from noisy MLS data / Yang Ma in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

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Determining the road traffic accident hotspots using GIS-based temporal-spatial statistical analytic techniques in Hanoi, Vietnam / Khanh Giang Le in Geo-spatial Information Science, vol 23 n° 2 (June 2020)  

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A hybrid deep learning–based model for automatic car extraction from high-resolution airborne imagery / Mehdi Khoshboresh Masouleh in Applied geomatics, vol 12 n° 2 (June 2020)  

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A multi-factor spatial optimization approach for emergency medical facilities in Beijing / Liang Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

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Prediction of traffic accidents hot spots using fuzzy logic and GIS / Aslam Al-Omari in Applied geomatics, vol 12 n° 2 (June 2020)  

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Traffic signal detection from in-vehicle GPS speed profiles using functional data analysis and machine learning / Yann Méneroux in International Journal of Data Science and Analytics JDSA, vol 10 n° 1 (June 2020)    

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Dynamic floating stations model for emergency medical services with a consideration of traffic data / Chih-Hong Sun in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

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Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network / Adil Alim in Geoinformatica [en ligne], vol 24 n° 2 (April 2020)  

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An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)  

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Assessing public transit performance using real-time data: spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA / Yongha Park in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

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WeCount, le trafic compté par les citoyens / Victor Oxombre (2020) 

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A reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy / Yan Zhou in Transactions in GIS, Vol 23 n° 5 (October 2019)  

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A space-time varying graph for modelling places and events in a network / Ikechukwu Maduako in International journal of geographical information science IJGIS, vol 33 n° 10 (October 2019)  

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Detecting and mapping traffic signs from Google Street View images using deep learning and GIS / Andrew Campbell in Computers, Environment and Urban Systems, vol 77 (september 2019)  

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Pavement marking retroreflectivity estimation and evaluation using mobile Lidar data / Erzhuo Che in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 8 (August 2019)  

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Automatisation du traitement de données "mobile mapping" : extraction d'éléments linéaires et ponctuels / Loïc Elsholz in XYZ, n° 159 (juin 2019)  

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Analyse spatiotemporelle des tournées de livraison d’une entreprise de livraison à domicile / Khaled Belhassine in Revue internationale de géomatique, vol 29 n° 2 (avril - juin 2019)  

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Embedding road networks and travel time into distance metrics for urban modelling / Henry Crosby in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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Analyse d’images par méthode de Deep Learning appliquée au contexte routier en conditions météorologiques dégradées / Khouloud Dahmane (2019)  

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Méthodes d'apprentissage statistique pour la détection de la signalisation routière à partir de véhicules traceurs / Yann Méneroux (2019)  

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Towards visual urban scene understanding for autonomous vehicle path tracking using GPS positioning data / Citlalli Gamez Serna (2019)  

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Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree / José Antonio Martin-Jimenez in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

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La signalisation routière intégrée au SIG d’une communauté de communes / Axel Orger in Géomatique expert, n° 125 (novembre - décembre 2018)

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Mining and visual exploration of closed contiguous sequential patterns in trajectories / Can Yang in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)  

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Apport des SIG et de la réalité virtuelle à la modélisation et la simulation du trafic urbain / Julien Richard (2018)  

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Convolutional neural network for traffic signal inference based on GPS traces / Yann Méneroux (2018) 

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Deep learning based vehicular mobility models for intelligent transportation systems / Jian Zhang (2018)  

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Detection and localization of traffic signals with GPS floating car data and Random Forest / Yann Méneroux (2018)    

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UAV sensors for environmental monitoring / Felipe Gonzalez Toro (2018)  

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Utilisation de véhicules traceurs pour la détection et la localisation de l'infrastructure routière par apprentissage automatique / Yann Méneroux (2018) 

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Localisation des caméras ANPR sur le réseau routier pour le profilage géographique / Marie Trotta in Revue internationale de géomatique, vol 27 n° 4 (octobre - décembre 2017)  

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Advances in cartography and GIScience / Michael P. Peterson (2017)  

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Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data / Luliang Tang in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)  

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Interurban visibility diagnosis from point clouds / Oscar Iglesias in European journal of remote sensing, vol 49 (2016)  

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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)  

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Generative models for road network reconstruction / Colin Kuntzsch in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

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Allier analyse géographique et expertise locale dans un SIG pour une stratégie territoriale de sécurité routière / Eliane Propeck-Zimmermann in Revue internationale de géomatique, vol 26 n° 2 (avril - juin 2016)  

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vol 26 n° 2 - avril - juin 2016 - Systèmes d'information pour le transport et la mobilité (Bulletin de Revue internationale de géomatique) / Cyril Ray  

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Forêts aléatoires pour la détection des feux tricolores à partir de profils de vitesse GPS / Yann Méneroux (2016) 

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Landmark based localization: LBA refinement using MCMC-optimized projections of RJMCMC-extracted road marks / Bahman Soheilian (2016)  

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Localisation à base d’amers visuels : Cartographie et mise en correspondance de marquages au sol et intégration dans LBA / Bahman Soheilian (2016)    

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Spatial analysis of geometric design consistency and road sight distance / Maria Castro in International journal of geographical information science IJGIS, vol 29 n° 12 (December 2015)  

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Trajectory reconstruction from mobile positioning data using cell-to-cell travel time information / Toivo Vajakas in International journal of geographical information science IJGIS, vol 29 n° 11 (November 2015)  

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Planning unobstructed paths in traffic-aware spatial networks / Shuo Shang in Geoinformatica [en ligne], vol 19 n° 4 (October - December 2015)  

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Exploring alternative map products to enhance transportation option awareness / Jessica V. Fayne in Cartography and Geographic Information Science, Vol 42 n° 4 (September 2015)  

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Hierarchical polygonization for generating and updating lane-based road network information for navigation from road markings / Anthony G.O. Yeh in International journal of geographical information science IJGIS, vol 29 n° 9 (September 2015)  

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Tracking 3D moving objects based on GPS/IMU navigation solution, laser scanner point cloud and GIS data / Siavash Hosseinyalamdary in ISPRS International journal of geo-information, vol 4 n°3 (September 2015)  

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Vehicular internet: security & privacy challenges and opportunities / Kamran Zaidi in Future internet, vol 7 n° 3 (September 2015)  

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enviroCar: A citizen science platform for analyzing and mapping crowd-sourced car sensor data / Arne Bröring in Transactions in GIS, vol 19 n° 3 (June 2015)  

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Road marking extraction using a model&data-driven RJ-MCMC / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3 W4 (March 2015)    

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Augmenting vehicle localization accuracy with cameras and 3D road infrastructure database / Lijun Wei (2015)  

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A novel approach for generating routable road maps from vehicle GPS traces / Jing Wang in International journal of geographical information science IJGIS, vol 29 n° 1 (January 2015)  

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Traffic prediction and analysis using a big data and visualisation approach / Declan McHugh (2015) 

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Vehicle localization using mono-camera and geo-referenced traffic signs / Xiaozhi Qu (2015)  

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Combinatorial clustering and its application to 3D polygonal traffic sign reconstruction from multiple images / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3 (September 2014)  

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TARS: traffic-aware route search / Roy Levin in Geoinformatica, vol 18 n° 3 (July 2014)  

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The Bulger Case : A Spatial Story / Les Roberts in Cartographic journal (the), vol 51 n° 2 (May 2014)

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Analysing landmarks in nature and elements of geospatial images to support wayfinding / Pyry Kettunen (2014) 

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Using mobile laser scanning data for automated extraction of road markings / Haiyan Guan in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)

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Image-based rendering of LOD1 3D city models for traffic-augmented immersive street-view navigation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3 W3 (November 2013)  

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A random set approach for modeling integrated uncertainties of traffic islands derived from airborne laser scanning points / Liang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 9 (September 2013)  

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A hierarchical approach to change detection in very high resolution SAR images for surveillance applications / Francesca Bovolo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)  

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Detection and 3D reconstruction of traffic signs from multiple view color images / Bahman Soheilian in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)  

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From signs to minds : Spatial information design and mental maps / M. Skiles in Cartographic journal (the), vol 49 n° 4 (November 2012)  

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Visibility monitoring using conventional roadside cameras : Emerging applications / Raouf Babari in Transportation Research - Part C: Emerging Technologies, vol 22 (June 2012)  

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Automatic extraction of road markings from mobile Lidar point clouds / B. Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)  

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Détection et localisation 3D de panneaux de signalisation [diaporama] / Bahman Soheilian (08/03/2012) 

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A model-driven approach to estimate atmospheric visibility with ordinary cameras / Raouf Babari in Atmospheric Environment, vol 45 n° 30 (September 2011)  

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Intégration d'infos-trafic temps réel dans un moteur de calcul d'itinéraires : Projet des élèves ingénieur de l'ENSG / Alexandre Pauthonnier in Géomatique expert, n° 81 (01/07/2011)  

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Collaborative web-GIS design: a case study for road risk analysis and monitoring / Francesco Pirotti in Transactions in GIS, vol 15 n° 2 (April 2011)  

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Journées de la recherche [IGN] / Anonyme in Géomatique expert, n° 79 (01/03/2011)

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Construction of digital 3D highway model using stereo IKONOS satellite imagery / Ahmed Shaker in Geocarto international, vol 26 n° 1 (February 2011)  

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Géographie de la mortalité routière en Europe / V. Eksler in Revue internationale de géomatique, vol 20 n° 4 (décembre 2010 – février 2011)  

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Road sign detection in images : a case study / Rachid Belaroussi (01/08/2010)

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3D road marking reconstruction from street-level calibrated stereo pairs / Bahman Soheilian in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 4 (July - August 2010)  

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Managing sensor traffic data and forecasting unusual behaviour propagation / C. Bauzer Medeiros in Geoinformatica, vol 14 n° 3 (July 2010)  

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Detection of roadway sign condition changes using multi-scale sign image matching (M-SIM) / Y.J. Tsai in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 4 (April 2010)  

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Mobile mapping at work in Belgium / K. Spratlin in GEO: Geoconnexion international, vol 9 n° 4 (april 2010)

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Extraction de panneaux de signalisation routière dans des images couleurs / Bahman Soheilian (19/01/2010)    

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GIS for building and managing infrastructure / Environmental Systems Research Institute ESRI (2010)

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Mobilités urbaines et risques des transports / Arnaud Banos (2010)

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A geometric stochastic approach based on marked point processes for road mark detection from high resolution aerial images / Olivier Tournaire in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 6 (November - December 2009)  

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Multi-scale spatiotemporal analyses of moose-vehicle collisions: a case study in northern Vermont / Giorgos Mountrakis in International journal of geographical information science IJGIS, vol 23 n°11-12 (november 2009)

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Street-based topological representations and analyses for predicting traffic flow in GIS / Bin Jiang in International journal of geographical information science IJGIS, vol 23 n°9-10 (september 2009)

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Street hierarchies: a minority of streets account for a majority of traffic flow / Bin Jiang in International journal of geographical information science IJGIS, vol 23 n° 7-8 (july 2009)

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New perspectives on the use of GPS and GIS to support a highway performance study / D. Tong in Transactions in GIS, vol 13 n° 1 (February 2009)

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