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Semisupervised one-class support vector machine for classification of remote sensing data / Jordi Munoz-Mari in IEEE Transactions on geoscience and remote sensing, vol 48 n° 8 (August 2010)
[article]
Titre : Semisupervised one-class support vector machine for classification of remote sensing data Type de document : Article/Communication Auteurs : Jordi Munoz-Mari, Auteur ; Francesca Bovolo, Auteur ; et al., Auteur Année de publication : 2010 Article en page(s) : pp 3188 - 3197 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage semi-dirigé
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification semi-dirigée
[Termes IGN] détection de changement
[Termes IGN] détection de cibleRésumé : (Auteur) This paper presents two semisupervised one-class support vector machine (OC-SVM) classifiers for remote sensing applications. In one-class image classification, one tries to detect pixels belonging to one of the classes in the image and reject the others. When few labeled pixels of only one class are available, obtaining a reliable classifier is a difficult task. In the particular case of SVM-based classifiers, this task is even harder because the free parameters of the model need to be finely adjusted, but no clear criterion can be adopted. In order to improve the OC-SVM classifier accuracy and alleviate the problem of free-parameter selection, the information provided by unlabeled samples present in the scene can be used. In this paper, we present two state-of-the-art algorithms for semi-supervised one-class classification for remote sensing classification problems. The first proposed algorithm is based on modifying the OC-SVM kernel by modeling the data marginal distribution with the graph Laplacian built with both labeled and unlabeled samples. The second one is based on a simple modification of the standard SVM cost function which penalizes more the errors made when classifying samples of the target class. The good performance of the proposed methods is illustrated in four challenging remote sensing image classification scenarios where the goal is to detect one of the classes present on the scene. In particular, we present results for multisource urban monitoring, hyperspectral crop detection, multispectral cloud screening, and change-detection problems. Experimental results show the suitability of the proposed techniques, particularly in cases with few or poorly representative labeled samples. Numéro de notice : A2010-307 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2010.2045764 En ligne : https://doi.org/10.1109/TGRS.2010.2045764 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30501
in IEEE Transactions on geoscience and remote sensing > vol 48 n° 8 (August 2010) . - pp 3188 - 3197[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2010081 RAB Revue Centre de documentation En réserve L003 Disponible Managing sensor traffic data and forecasting unusual behaviour propagation / C. Bauzer Medeiros in Geoinformatica, vol 14 n° 3 (July 2010)
[article]
Titre : Managing sensor traffic data and forecasting unusual behaviour propagation Type de document : Article/Communication Auteurs : C. Bauzer Medeiros, Auteur ; M. Joliveau, Auteur ; Geneviève Jomier, Auteur ; F. De Vuyst, Auteur Année de publication : 2010 Article en page(s) : pp 279 - 305 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] base de données spatiotemporelles
[Termes IGN] comportement
[Termes IGN] données multicapteurs
[Termes IGN] réseau de capteurs
[Termes IGN] trafic routier
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Sensor data on traffic events have prompted a wide range of research issues, related with the so-called ITS (Intelligent Transportation Systems). Data are delivered for both static (fixed) and mobile (embedded) sensors, generating large and complex spatio-temporal series. This scenario presents several research challenges, in spatio-temporal data management and data analysis. Management issues involve, for instance, data cleaning and data fusion to support queries at distinct spatial and temporal granularities. Analysis issues include the characterization of traffic behavior for given space and/or time windows, and detection of anomalous behavior (either due to sensor malfunction, or to traffic events). This paper contributes to the solution of some of these issues through a new kind of framework to manage static sensor data. Our work is based on combining research on analytical methods to process sensor data, and data management strategies to query these data. The first aspect is geared towards supporting pattern matching. This leads to a model to study and predict unusual traffic behavior along an urban road network. The second aspect deals with spatio-temporal database issues, taking into account information produced by the model. This allows distinct granularities and modalities of analysis of sensor data in space and time. This work was conducted within a project that uses real data, with tests conducted on 1,000 sensors, during 3 years, in a large French city. Copyright Springer Numéro de notice : A2010-102 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1007/s10707-010-0102-7 Date de publication en ligne : 28/01/2010 En ligne : https://doi.org/10.1007/s10707-010-0102-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30298
in Geoinformatica > vol 14 n° 3 (July 2010) . - pp 279 - 305[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2010031 RAB Revue Centre de documentation En réserve L003 Disponible Spatio-temporal trajectory analysis of mobile objects following the same itinerary / Laurent Etienne (26/05/2010)
Titre : Spatio-temporal trajectory analysis of mobile objects following the same itinerary Type de document : Article/Communication Auteurs : Laurent Etienne, Auteur ; Thomas Devogele , Auteur ; Alain Bouju, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 26/05/2010 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 38-2 Conférence : SDH 2010, 14th International Symposium on Spatial Data Handling, joint conference with ISPRS 26/05/2010 28/05/2010 Hong-Kong Hong-Kong Proceedings Springer Importance : 6 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] comportement
[Termes IGN] exploration de données géographiques
[Termes IGN] navire
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] trajectoire (véhicule non spatial)Résumé : (Auteur) More and more mobile objects are now equipped with sensors allowing real time monitoring of their movements. Nowadays, the data produced by these sensors can be stored in spatio-temporal databases. The main goal of this article is to perform a data mining on a huge quantity of mobile object's positions moving in an open space in order to deduce its behaviour. New tools must be defined to ease the detection of outliers. First of all, a zone graph is set up in order to define itineraries. Then, trajectories of mobile objects following the same itinerary are extracted from the spatio-temporal database and clustered. A statistical analysis on this set of trajectories lead to spatio-temporal patterns such as the main route and spatio-temporal channel followed by most of trajectories of the set. Using these patterns, unusual situations can be detected. Furthermore, a mobile object's behaviour can be defined by comparing its positions with these spatio-temporal patterns. In this article, this technique is applied to ships' movements in an open maritime area. Unusual behaviours such as being ahead of schedule or delayed or veering to the left or to the right of the main route are detected. A case study illustrates these processes based on ships' positions recorded during two years around the Brest area. This method can be extended to almost all kinds of mobile objects (pedestrians, aircrafts, hurricanes, ...) moving in an open area. Numéro de notice : C2010-047 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVIII/part2/Papers/50_Paper.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64319 Documents numériques
en open access
14253_ctap_isprs_vol38part2_50_paper_devogele.pdfAdobe Acrobat PDF Global 4DVAR assimilation and forecast experiments using AMSU observations over land. Part II: Impacts of assimilating surface-sensitive channels on the African monsoon during AMMA / Fatima Karbou in Weather and Forecasting, vol 25 n° 1 (February 2010)
[article]
Titre : Global 4DVAR assimilation and forecast experiments using AMSU observations over land. Part II: Impacts of assimilating surface-sensitive channels on the African monsoon during AMMA Type de document : Article/Communication Auteurs : Fatima Karbou, Auteur ; Florence Rabier, Auteur ; Jean-Philippe Lafore, Auteur ; Jean-Luc Redelsperger, Auteur ; Olivier Bock , Auteur Année de publication : 2010 Projets : AMMA & AMMA-2 / Janicot, Serge Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] Afrique occidentale
[Termes IGN] assimilation des données
[Termes IGN] coordonnées GPS
[Termes IGN] données météorologiques
[Termes IGN] emissivité
[Termes IGN] étude de faisabilité
[Termes IGN] humidité de l'air
[Termes IGN] image NOAA-AMSU
[Termes IGN] mousson
[Termes IGN] prévision météorologiqueRésumé : (auteur) Observations from Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B) have been more intensively used over sea than over land because of large uncertainties about the land surface emissivity and the skin temperature. Several methods based on a direct estimation of the land emissivity from satellite observations have been found to be very useful for improving the assimilation of sounding channels over land. Feasibility studies have been conducted within the Météo-France global assimilation system in order to examine the possibility of assimilating low-level atmospheric observations receiving a contribution from the land surface. The present study reports on three 2-month assimilation and forecast experiments, which include the assimilation of surface-sensitive observations from AMSU-A and -B together with a control experiment, which represents the operational model. The assimilation experiments have been compared with the control, and important changes in the analyzed atmospheric fields and in the precipitation forecasts over parts of the tropics, and especially over West Africa, have been noticed. The experiments seem to emphasize the atmospheric moistening in India, South America, and in West Africa, together with atmospheric drying over Saudi Arabia and northeast Africa. The drying or moistening of the atmosphere has been successfully evaluated using independent measurements from the GPS African Monsoon Multidisciplinary Analysis (AMMA) network. Precipitation and OLR forecasts have also been examined and compared with independent measurements. Physically, the changes result in a better-organized African monsoon with a stronger ITCZ in terms of ascent, vorticity, and precipitation, but there is no northward shift of the monsoon system. Low-level humidity observations have been found to have important impacts on the analysis and to produce positive impacts on forecast scores over the tropics. Numéro de notice : A2010-664 Affiliation des auteurs : LAREG+Ext (1991-2011) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1175/2009WAF2222244.1 Date de publication en ligne : 01/02/2010 En ligne : https://doi.org/10.1175/2009WAF2222244.1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91770
in Weather and Forecasting > vol 25 n° 1 (February 2010) . - pp[article]Documents numériques
en open access
Global 4DVAR assimilation and forecast experiments ... - pdf éditeurAdobe Acrobat PDF Accuracy 2010 : Proceedings of the Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, 20 - 23 juillet 2010 / Nicholas J. Tate (2010)
Titre : Accuracy 2010 : Proceedings of the Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, 20 - 23 juillet 2010 Type de document : Actes de congrès Auteurs : Nicholas J. Tate, Éditeur scientifique ; Peter F. Fisher, Éditeur scientifique Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2010 Autre Editeur : International Spatial Accuracy Research Association ISARA Conférence : Accuracy 2010, 9th international symposium on spatial accuracy assessment in natural resources and environmental sciences 20/07/2010 23/07/2010 Leicester Royaume-Uni OA Proceedings Importance : 436 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Termes IGN] données localisées des bénévoles
[Termes IGN] géostatistique
[Termes IGN] géovisualisation
[Termes IGN] incertitude des données
[Termes IGN] incertitude géométrique
[Termes IGN] incertitude temporelle
[Termes IGN] précision des données
[Termes IGN] propagation d'erreur
[Termes IGN] sous ensemble flou
[Termes IGN] traitement de données localiséesIndex. décimale : CG2010 Actes de congrès en 2010 Note de contenu : 1 - Keynotes
2 - Remote sensing and image interpretation
3 - Fuzzy uncertainty 1
4 - Uncertainty in space and time
5 - Geostatistics 1
6 - ISPRS session
7 - Uncertainty propagation
8 - Land use and land cover
9 - DEM uncertainty 1
10 - Remote sensing
11 - Geoprocessing
12 - Model uncertainty and validation
13 - Vizualisation
14 - Sampling design
15 - Spatio-temporal uncertainty
16 - DEM uncertainty 2
17 - Geostatistics 2
18 - Fuzzy uncertainty 2
19 - DEM uncertainty 3
20 - Remote sensing classification
21 - Environmental quality
22 - Small area concerns
23 - Ecology and forestry
24 - VGI and web-based geoprocessing
25 - Geocoding and adress coding
26 - PostersNuméro de notice : 21370 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Actes DOI : sans En ligne : http://spatialaccuracy.org/spatial-accuracy-2010/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90097 ContientRéservation
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