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Titre : Traffic prediction and analysis using a big data and visualisation approach Type de document : Article/Communication Auteurs : Declan McHugh, Auteur Editeur : Leeds [Royaume-Uni] : University of Leeds Année de publication : 2015 Conférence : GISRUK 2015, 23th GIS Research UK annual conference 15/04/2015 17/04/2015 Leeds Royaume-Uni open access proceedings Importance : pp 408 - 420 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] Dublin (Irlande ; ville)
[Termes IGN] exploration de données géographiques
[Termes IGN] modèle de simulation
[Termes IGN] prévision
[Termes IGN] régression multiple
[Termes IGN] trafic routier
[Termes IGN] Twitter
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) This abstract illustrates an approach of using big data, visualisation and data mining techniques used to predict and analyse traffic. The objective is to understand Traffic patterns in Dublin City. The prediction model was used as an estimator to identify unusual traffic patterns. The generic model was designed using data mining techniques, multivariate regression algorithms, ARIMA and visually correlated with real-time traffic tweets. Using the prediction model and tweet event detection. The result is a high-performance web application containing over 500,000,000,000 traffic observations that produce analytical dashboard providing traffic prediction and analysis. Numéro de notice : C2015-049 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83863 Documents numériques
en open access
Traffic prediction and analysisAdobe Acrobat PDF Exploring and visualizing differences in geographic and linguistic web coverage / Ramya Venkateswaran in Transactions in GIS, vol 18 n° 6 (December 2014)
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Titre : Exploring and visualizing differences in geographic and linguistic web coverage Type de document : Article/Communication Auteurs : Ramya Venkateswaran, Auteur ; Robert Weibel, Auteur ; Ross S. Purves, Auteur Année de publication : 2014 Article en page(s) : pp 852 – 876 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] couverture (données géographiques)
[Termes IGN] densité de population
[Termes IGN] exploration de données
[Termes IGN] information géographique
[Termes IGN] langage naturel (informatique)
[Termes IGN] Suisse
[Termes IGN] visualisation de donnéesRésumé : (Auteur) This article reports on a study performed to understand the geographic and linguistic coverage of web resources, focusing on the example of tourism-related themes in Switzerland. Search engine queries of web documents were used to gather counts for phrases in four different languages. The study focused on selected populated places and tourist attractions in Switzerland from three gazetteer datasets: topographic gazetteer data from the Swiss national mapping agency (SwissTopo); POI data from a commercial data provider (Tele Atlas) and user generated geographic content (geonames.org). The web counts illustrate the geographic extent and trends of web coverage of tourism for different languages. Results show that coverage for local languages, i.e. German, French and Italian, is more strongly related to the region of the spoken language. Correlation of the web counts to typical tourism indicators, e.g. population and number of hotel nights rented per year, are also computed and compared. Numéro de notice : A2014-574 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12071 Date de publication en ligne : 27/01/2014 En ligne : https://doi.org/10.1111/tgis.12071 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74764
in Transactions in GIS > vol 18 n° 6 (December 2014) . - pp 852 – 876[article]Noisy data smoothing in DEM construction using least squares support vector machines / C. Chen in Transactions in GIS, vol 18 n° 6 (December 2014)
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Titre : Noisy data smoothing in DEM construction using least squares support vector machines Type de document : Article/Communication Auteurs : C. Chen, Auteur ; Y. Li, Auteur ; H. Dai, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 896 – 910 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bruit (théorie du signal)
[Termes IGN] données lidar
[Termes IGN] modèle numérique du bâti
[Termes IGN] séparateur à vaste margeRésumé : (Auteur) Since spatial datasets are subject to sampling errors, a smoothing interpolation method should be employed to remove noise during DEM construction. Although least squares support vector machines (LSSVM) have been widely accepted as a classifier, their effect on smoothing noisy data is almost unknown. In this article, the smoothness of LSSVM was explored, and its effect on smoothing noisy data in DEM construction was tested. In order to improve the ability to deal with large datasets, a local method of LSSVM has been developed, where only the neighboring sampling points around the one to be estimated are used for computation. A numerical test indicated that LSSVM is more accurate than the classical smoothing methods including TPS and kriging, and its error surfaces are more evenly distributed. The real-world example of smoothing noise inherent in lidar-derived DEMs also showed that LSSVM has a positive smoothing effect, which is approximately as accurate as TPS. In short, LSSVM with a high efficiency can be considered as an alternative smoothing method for smoothing noisy data in DEM construction. Numéro de notice : A2014-576 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12078 Date de publication en ligne : 26/02/2014 En ligne : https://doi.org/10.1111/tgis.12078 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74766
in Transactions in GIS > vol 18 n° 6 (December 2014) . - pp 896 – 910[article]Detecting cars in UAV images with a catalog-based approach / Thomas Moranduzzo in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
[article]
Titre : Detecting cars in UAV images with a catalog-based approach Type de document : Article/Communication Auteurs : Thomas Moranduzzo, Auteur ; F. Melgani, Auteur Année de publication : 2014 Article en page(s) : pp 6356 - 6367 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] catalogue
[Termes IGN] détection d'objet
[Termes IGN] extraction automatique
[Termes IGN] histogramme
[Termes IGN] séparateur à vaste marge
[Termes IGN] traitement automatique de données
[Termes IGN] véhicule automobileRésumé : (Auteur) This paper presents a new method for the automatic detection of cars in unmanned aerial vehicle (UAV) images acquired over urban contexts. UAV images are characterized by an extremely high spatial resolution, which makes the detection of cars particularly challenging. The proposed method starts with a screening operation in which the asphalted areas are identified in order to make the car detection process faster and more robust. Subsequently, filtering operations in the horizontal and vertical directions are performed to extract histogram-of-gradient features and to yield a preliminary detection of cars after the computation of a similarity measure with a catalog of cars used as reference. Three different strategies for computing the similarity are investigated. Successively, for the image points identified as potential cars, an orientation value is computed by searching for the highest similarity value in 36 possible directions. The last step is devoted to the merging of the points which belong to the same car because it is likely that a car is identified by more than one point due to the extremely high resolution of UAV images. As outcomes, the proposed method provides the number of cars in the image, as well as the position and orientation for each of them. Interesting experimental results, conducted on a set of real UAV images acquired over an urban area, are presented and discussed. Numéro de notice : A2014-484 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2296351 En ligne : https://doi.org/10.1109/TGRS.2013.2296351 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74067
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 10 tome 1 (October 2014) . - pp 6356 - 6367[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014101A RAB Revue Centre de documentation En réserve L003 Disponible Characterisation of building alignments with new measures using C4.5 decision tree algorithm / Sinan Cetinkaya in Geodetski vestnik, vol 58 n° 3 ([01/09/2014])
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Titre : Characterisation of building alignments with new measures using C4.5 decision tree algorithm Type de document : Article/Communication Auteurs : Sinan Cetinkaya, Auteur ; Melih Basaraner, Auteur Année de publication : 2014 Article en page(s) : pp 552 - 567 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] alignement
[Termes IGN] arbre de décision
[Termes IGN] bati
[Termes IGN] caractérisation
[Termes IGN] classification dirigée
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] régression
[Termes IGN] triangulation de DelaunayRésumé : (auteur) Detection and characterisation of spatial patterns is crucial for cartographic generalisation since it entails preserving the patterns as much as possible within scale limits. Building alignments are commonly confronted patterns in the topographic maps/databases. They are perceptually recognised in accordance with relevant Gestalt factors, namely proximity, similarity, common orientation and continuity. This study is concentrated on how to characterise building alignments detected by automated or manual methods. To this end, new measures based on Delaunay triangulation and regression line/curve are established to correspond to the Gestalt factors. The relationship between the measures and Gestalt principles has been illustrated with a decision tree. An index value was computed by total sum of measures’ values to compare and order alignments from quality aspect. Additionally, a supervised classification was performed with C4.5 algorithm thus a decision tree was obtained to be able to both associate the quality categories with the measure values and automatically assign alignments into a quality class. The findings demonstrate that proposed measures are substantially effective for representing Gestalt factors. The proposed methods can potentially enhance and ease the characterisation of building alignments in topographic map generalization. Numéro de notice : A2014-560 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.15292/geodetski-vestnik.2014.03.552-567 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2014.03.552-567 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74701
in Geodetski vestnik > vol 58 n° 3 [01/09/2014] . - pp 552 - 567[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Land cover and soil type mapping from spaceborne PolSAR Data at L-Band with probabilistic neural network / Oleg Antropov in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkRegional land-use allocation using a coupled MAS and GA model: from local simulation to global optimization, a case study in Caidian District, Wuhan, China / Man Yuan in Cartography and Geographic Information Science, vol 41 n° 4 (September 2014)PermalinkSystème multi-agent pour la modélisation des écoulements de surface sur un petit bassin versant viticole du Layon / Mahefa Mamy Rakotoarisoa in Revue internationale de géomatique, vol 24 n° 3 (septembre - novembre 2014)PermalinkCombining hyperspectral and Lidar data for vegetation mapping in the Florida Everglades / Caiyun Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)PermalinkHyperspectral remote sensing image subpixel target detection based on supervised metric learning / Lefei Zhang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)PermalinkDetection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning / Andrès Serna in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)PermalinkOrbit computation of the TELECOM-2D satellite with a genetic algorithm / Florent Deleflie in Proceedings of the International astronomical union, vol 9 S310 (Juillet 2014)PermalinkA polygon-based clustering and analysis framework for mining spatial datasets / Sujing Wang in Geoinformatica, vol 18 n° 3 (July 2014)PermalinkPredictive policing / Jeremy Heffner in GEO: Geoconnexion international, vol 13 n° 7 (July 2014)PermalinkKnowledge and reasoning in spatial analysis / Andreas Hall in Transactions in GIS, vol 18 n° 3 (June 2014)Permalink