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Interference localization from space: theoretical background / Luca Canzian in Inside GNSS, vol 11 n° 6 (November - December 2016)
[article]
Titre : Interference localization from space: theoretical background Type de document : Article/Communication Auteurs : Luca Canzian, Auteur ; Stefano Ciccotosto, Auteur ; Samuele Fantinato, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 59 - 68 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] détection automatique
[Termes IGN] géolocalisation
[Termes IGN] interférenceRésumé : (auteur) Radio Frequency Interference causes the satellite industry to lose millions of dollars per year due to detrimental effects, ranging from a degradation in the quality of service to the complete loss of service. As a consequence, it is becoming critical important to design space systems that are able to localize the source of interference, allowing actions that can prevent future repetitions of similar behaviors. This is the first of a series of articles on the issue of interference localization. This article discusses the theoretical aspects associated with single-interferer localization approaches, describing how to extract those features providing information on the interference source location from the received interference signal itself, and how to compute a position fix by merging the collected information. Numéro de notice : A2016--051 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans En ligne : http://www.insidegnss.com/node/5200 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83598
in Inside GNSS > vol 11 n° 6 (November - December 2016) . - pp 59 - 68[article]Voir aussiRéservation
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Code-barres Cote Support Localisation Section Disponibilité 238-2016061 SL Revue Centre de documentation Revues en salle Disponible A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging / Hannah Vickers in Earth and space science, vol 3 n° 11 (November 2016)
[article]
Titre : A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging Type de document : Article/Communication Auteurs : Hannah Vickers, Auteur ; M. Eckerstorfer, Auteur ; Eirik Malnes, Auteur ; Y. Larsen, Auteur ; H. Hindberg, Auteur Année de publication : 2016 Article en page(s) : pp 446 - 462 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] avalanche
[Termes IGN] détection automatique
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] Norvège
[Termes IGN] TromsRésumé : (auteur) Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide. Numéro de notice : A2016-966 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1002/2016EA000168 En ligne : http://dx.doi.org/10.1002/2016EA000168 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83624
in Earth and space science > vol 3 n° 11 (November 2016) . - pp 446 - 462[article]A probabilistic approach to detect mixed periodic patterns from moving object data / Jun Li in Geoinformatica, vol 20 n° 4 (October - December 2016)
[article]
Titre : A probabilistic approach to detect mixed periodic patterns from moving object data Type de document : Article/Communication Auteurs : Jun Li, Auteur ; Jingjing Wang, Auteur ; Junfei Zhang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 715 - 739 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] comportement
[Termes IGN] détection automatique
[Termes IGN] détection d'objet
[Termes IGN] estimation par noyau
[Termes IGN] objet mobile
[Termes IGN] séquence d'images
[Termes IGN] variable aléatoireRésumé : (Auteur) The prevalence of moving object data (MOD) brings new opportunities for behavior related research. Periodic behavior is one of the most important behaviors of moving objects. However, the existing methods of detecting periodicities assume a moving object either does not have any periodic behavior at all or just has a single periodic behavior in one place. Thus they are incapable of dealing with many real world situations whereby a moving object may have multiple periodic behaviors mixed together. Aiming at addressing this problem, this paper proposes a probabilistic periodicity detection method called MPDA. MPDA first identifies high dense regions by the kernel density method, then generates revisit time sequences based on the dense regions, and at last adopts a filter-refine paradigm to detect mixed periodicities. At the filter stage, candidate periods are identified by comparing the observed and reference distribution of revisit time intervals using the chi-square test, and at the refine stage, a periodic degree measure is defined to examine the significance of candidate periods to identify accurate periods existing in MOD. Synthetic datasets with various characteristics and two real world tracking datasets validate the effectiveness of MPDA under various scenarios. MPDA has the potential to play an important role in analyzing complicated behaviors of moving objects. Numéro de notice : A2016-814 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s10707-016-0261-2 En ligne : http://dx.doi.org/10.1007/s10707-016-0261-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82615
in Geoinformatica > vol 20 n° 4 (October - December 2016) . - pp 715 - 739[article]Automatic recognition of long period events from volcano tectonic earthquakes at Cotopaxi volcano / Román A. Lara-Cueva in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
[article]
Titre : Automatic recognition of long period events from volcano tectonic earthquakes at Cotopaxi volcano Type de document : Article/Communication Auteurs : Román A. Lara-Cueva, Auteur ; Diego S. Benítez, Auteur ; Enrique V. Carrera, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 5247 - 5257 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] classification par arbre de décision
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] Cotopaxi (volcan)
[Termes IGN] détection automatique
[Termes IGN] détection de changement
[Termes IGN] détection du signal
[Termes IGN] Equateur (état)Résumé : (Auteur) Geophysics experts are interested in understanding the behavior of volcanoes and forecasting possible eruptions by monitoring and detecting the increment on volcano-seismic activity, with the aim of safeguarding human lives and material losses. This paper presents an automatic volcanic event detection and classification system, which considers feature extraction and feature selection stages, to reduce the processing time toward a reliable real-time volcano early warning system (RT-VEWS). We built the proposed approach in terms of the seismicity presented in 2009 and 2010 at the Cotopaxi Volcano located in Ecuador. In the detection stage, the recordings were time segmented by using a nonoverlapping 15-s window, and in the classification stage, the detected seismic signals were 1-min long. For each detected signal conveying seismic events, a comprehensive set of statistical, temporal, spectral, and scale-domain features were compiled and extracted, aiming to separate long-period (LP) events from volcano-tectonic (VT) earthquakes. We benchmarked two commonly used types of feature selection techniques, namely, wrapper (recursive feature extraction) and embedded (cross-validation and pruning). Each technique was used within a suitable and appropriate classification algorithm, either the support vector machine (SVM) or the decision trees. The best result was obtained by using the SVM classifier, yielding up to 99% accuracy in the detection stage and 97% accuracy and sensitivity in the event classification stage. Selected features and their interpretation were consistent among different input spaces in simple terms of the spectral content of the frequency bands at 3.1 and 6.8 Hz. A comparative analysis showed that the most relevant features for automatic discrimination between LP and VT events were one in the time domain, five in the frequency domain, and nine in the scale domain. Our study provides the framework for an event classification system with high accuracy and reduced computational requirements, according to the orientation toward a future RT-VEWS. Numéro de notice : A2016-897 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2559440 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2559440 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83090
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5247 - 5257[article]Towards automated detection of visual cadastral boundaries / Yismaw Wassie in GIM international [en ligne], vol 30 n° 8 (August 2016)
[article]
Titre : Towards automated detection of visual cadastral boundaries Type de document : Article/Communication Auteurs : Yismaw Wassie, Auteur ; Mila Koeva, Auteur ; Rohan Bennett, Auteur Année de publication : 2016 Article en page(s) : pp 23 - 25 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger
[Termes IGN] cartographie cadastrale
[Termes IGN] détail topographique
[Termes IGN] détection automatique
[Termes IGN] limite cadastraleRésumé : (auteur) The technology push behind emerging automated feature identification and line generation techniques provides a new opportunity for the domain of fit-for-purpose land administration. It could help to further automate the process of boundary generation in cadastral system – particularly in contexts where large areas remain unmapped and cadastral boundaries align with topographic or visual boundaries. Numéro de notice : A2016-509 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81535
in GIM international [en ligne] > vol 30 n° 8 (August 2016) . - pp 23 - 25[article]Comparison of quality measures for building outline extraction / Markéta Potůčková in Photogrammetric record, vol 31 n° 154 (June - August 2016)PermalinkContext-dependent detection of non-linearly distributed points for vegetation classification in airborne LiDAR / Denis Horvat in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)PermalinkListening for RF noise : An analysis of pre-despreading GNSS interference detection techniques / Ali Jafarnia-Jahromi in Inside GNSS, vol 11 n° 3 (May - June 2016)PermalinkA multi-scale plane-detection method based on the Hough transform and region growing / Xiaoxu Leng in Photogrammetric record, vol 31 n° 154 (June - August 2016)PermalinkToward a generalizable image representation for large-scale change detection : application to generic damage analysis / Lionel Gueguen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkAutomatic detection and reconstruction of 2-D/3-D building shapes from spaceborne TomoSAR point clouds / Muhammad Shahzad in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)PermalinkDetection and labeling of sensitive areas in hydrological cartography using vector statistics / Elia Quirós in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkForêts aléatoires pour la détection des feux tricolores à partir de profils de vitesse GPS / Yann Méneroux (2016)PermalinkQualification des données Stéréopolis et étude d'un algorithme de détection d'objets / Guillaume Curtet (2016)PermalinkThe art of seeing / Philippe Roy in GEO: Geoconnexion international, vol 15 n° 1 (January 2016)Permalink