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Tight integration of INS/Stereo VO/Digital map for land vehicle navigation / Fei Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 1 (January 2018)
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Titre : Tight integration of INS/Stereo VO/Digital map for land vehicle navigation Type de document : Article/Communication Auteurs : Fei Liu, Auteur ; Yashar Balazadegan, Auteur ; Yang Gao, Auteur Année de publication : 2018 Article en page(s) : pp 15 - 23 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] centrale inertielle
[Termes IGN] correction géométrique
[Termes IGN] erreur instrumentale
[Termes IGN] filtre de Kalman
[Termes IGN] navigation à l'estime
[Termes IGN] odomètre
[Termes IGN] système de numérisation mobileRésumé : (Auteur) This paper proposes a method for tight integration of IMU (Inertial Measurement Unit), stereo VO (Visual Odometry) and digital map for land vehicle navigation, which effectively limits the quick drift of DR (Dead Reckoning) navigation system. In this method, the INS provides the dynamic information of the land vehicle, which is used to predict the position and attitude of cameras in order to obtain the predicted pixel coordinates of features on the image. The difference between the measured and predicted pixel coordinates is used to reduce the accumulated errors of INS. To implement the proposed method, an Extended Kalman filter (EKF) is first used to integrate the inertial and visual sensor data. The integrated solution of position, velocity and azimuth is then applied by fuzzy logic map matching (MM) to project the vehicle location on the correct road link. The projected position on the road link and the road link azimuth can finally be used to reduce the dead reckoning drifts. In this way, the accumulated system errors can be significantly reduced. The testing results indicate that the horizontal RMSE (root-mean-square-error) of the proposed method is less than 20 meters over a traveled distance of five kilometers and the relative horizontal error is below 0.4 percent. Numéro de notice : A2018-020 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.14358/PERS.84.1.15 En ligne : https://doi.org/10.14358/PERS.84.1.15 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89167
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 1 (January 2018) . - pp 15 - 23[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018011 RAB Revue Centre de documentation En réserve L003 Disponible Toponym matching through deep neural networks / Rui Santos in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)
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Titre : Toponym matching through deep neural networks Type de document : Article/Communication Auteurs : Rui Santos, Auteur ; Patricia Murrieta-Flores, Auteur ; Pavel Calado, Auteur ; Bruno Martins, Auteur Année de publication : 2018 Article en page(s) : pp 324 - 348 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie
[Termes IGN] appariement
[Termes IGN] apprentissage profond
[Termes IGN] recherche d'information géographique
[Termes IGN] répertoire toponymique
[Termes IGN] réseau neuronal artificiel
[Termes IGN] similitude sémantique
[Termes IGN] toponyme
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Toponym matching, i.e. pairing strings that represent the same real-world location, is a fundamental problemfor several practical applications. The current state-of-the-art relies on string similarity metrics, either specifically developed for matching place names or integrated within methods that combine multiple metrics. However, these methods all rely on common sub-strings in order to establish similarity, and they do not effectively capture the character replacements involved in toponym changes due to transliterations or to changes in language and culture over time. In this article, we present a novel matching approach, leveraging a deep neural network to classify pairs of toponyms as either matching or nonmatching. The proposed network architecture uses recurrent nodes to build representations from the sequences of bytes that correspond to the strings that are to be matched. These representations are then combined and passed to feed-forward nodes, finally leading to a classification decision. We present the results of a wide-ranging evaluation on the performance of the proposed method, using a large dataset collected from the GeoNames gazetteer. These results show that the proposed method can significantly outperform individual similarity metrics from previous studies, as well as previous methods based on supervised machine learning for combining multiple metrics. Numéro de notice : A2018-027 Affiliation des auteurs : non IGN Thématique : TOPONYMIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1390119 En ligne : https://doi.org/10.1080/13658816.2017.1390119 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89179
in International journal of geographical information science IJGIS > vol 32 n° 1-2 (January - February 2018) . - pp 324 - 348[article]Réservation
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Titre : Le travail invisible des données : Éléments pour une sociologie des infrastructures scripturales Type de document : Monographie Auteurs : Jérôme Denis, Auteur Editeur : Paris : Presses de l'Ecole des Mines Année de publication : 2018 Autre Editeur : Marseille : OpenEdition Press Collection : Sciences sociales Importance : 206 p. ISBN/ISSN/EAN : 978-2-35671-524-1 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Sociologie
[Termes IGN] cadre conceptuel
[Termes IGN] données massives
[Termes IGN] échange de données informatisé
[Termes IGN] production (économie)Résumé : (auteur) Ouvertes, massives, brutes … les données sont aujourd’hui au cœur de nombreux débats. Les optimistes y voient une ressource naturelle dont la récolte et la circulation sont en passe de révolutionner l’innovation et la démocratie, tandis que les pessimistes les dépeignent comme le carburant de mécanismes qui ne profiteront qu’aux puissants et renforceront les inégalités. Face aux enthousiasmes et aux affolements, face au vocabulaire de la transparence, de la fluidité et de l’automatisation qu’ils mobilisent, ce livre fait un pas de côté et défend la nécessité d’étudier les modalités concrètes de la production et de la circulation des données. Les données ne tombent en effet jamais du ciel. Elles n’affleurent pas non plus sous le sol des organisations. En amont de leurs traitements si prometteurs ou inquiétants, elles font l’objet d’un travail dont la nature, l’organisation et les processus mêmes qui mènent à son invisibilité restent à explorer. En articulant les apports de la sociologie des sciences et des techniques, de l’histoire, de l’anthropologie de l’écriture, de la sociologie du travail et des accounting studies, l’ouvrage compose un outillage conceptuel et méthodologique original pour interroger au plus près ce travail des données, qui est devenu central dans les entreprises et les administrations à partir de la fin du XIXe siècle. Numéro de notice : 17500 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Monographie DOI : 10.4000/books.pressesmines.3934 Date de publication en ligne : 01/08/2018 En ligne : http://dx.doi.org/10.4000/books.pressesmines.3934 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90379
Titre : UAV sensors for environmental monitoring Type de document : Monographie Auteurs : Felipe Gonzalez Toro, Éditeur scientifique ; Antonios Tsourdos, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2018 Importance : 660 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-03842-753-7 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] accident de la route
[Termes IGN] biodiversité
[Termes IGN] capteur aérien
[Termes IGN] capteur terrestre
[Termes IGN] détection de cible
[Termes IGN] filtre passe-bande
[Termes IGN] image captée par drone
[Termes IGN] image hyperspectrale
[Termes IGN] image optique
[Termes IGN] image radar moirée
[Termes IGN] instrument embarqué
[Termes IGN] photogrammétrie aérienne
[Termes IGN] prévention des risques
[Termes IGN] surveillance écologique
[Termes IGN] surveillance hydrologiqueRésumé : (éditeur) The rapid development and growth of UAVs as a remote sensing platform, as well as advances in the miniaturization of instrumentation and data systems, are catalyzing a renaissance in remote sensing in a variety of fields and disciplines from precision agriculture to ecology, atmospheric research, and disaster response.
This Special Issue was open for submissions that highlight advances in the development and use of sensors deployed on UAVs. Topics include, but were not limited, to:
- Optical, multi-spectral, hyperspectral, laser, and optical SAR technologies
- Gas analyzers and sensors
- Artificial intelligence and data mining based strategies from UAVs
- UAV onboard data storage, transmission, and retrieval
- Collaborative strategies and mechanisms to control multiple UAVs and sensor networks
- UAV sensor applications: precision agriculture; pest detection, forestry, mammal species tracking search and rescue; target tracking, the monitoring of the atmosphere; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring, pollution monitoring, micro-climates and land useNote de contenu : Preface
1- UAV-based photogrammetry and integrated technologies for architectural applications—methodological strategies for the after-quake survey of vertical structures in Mantua (Italy)
2- Towards the development of a low cost airborne sensing system to monitor dust particles after blasting at open-pit mine sites
3- Multi-UAV routing for area coverage and remote sensing with minimum time
4- UAV deployment exercise for mapping purposes: evaluation of emergency
response applications
5- Automated identification of river hydromorphological features using UAV high
resolution aerial imagery
6- Autonomous aerial refueling ground test demonstration—a sensor-in-the-loop,
non-tracking method
7- A new calibration method using low cost MEM IMUs to verify the performance of
UAV-borne MMS payloads
8- Adaptive environmental source localization and tracking with unknown permittivity and pathloss coefficients
9- Vision-based detection and distance estimation of micro unmanned aerial vehicles
10- Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation
11- UAVs task and motion planning in the presence of obstacles and prioritized targets
12- Towards the development of a smart flying sensor: Illustration in the field of
precision agriculture
13- Flight test result for the ground-based radio navigation system sensor with an
unmanned air vehicle
12- Multisensor super resolution using directionally-adaptive regularization for UAV images
13- UAV control on the basis of 3D landmark bearing-only observations
14- Cooperative surveillance and pursuit using unmanned aerial vehicles and unattended ground sensors
15- A multispectral image creating method for a new airborne four-camera system with
different bandpass filters
16- Vision and control for UAVs: A survey of general methods and of inexpensive platforms for infrastructure inspection
17- Feasibility of using synthetic aperture radar to aid UAV navigation
18- Towards an autonomous vision-based unmanned aerial system against wildlife poachers
19- Formation flight of multiple UAVs via onboard sensor information sharing
20- Mini-UAV based sensory system for measuring environmental variables in greenhouses
21- Mini-UAV based sensory system for measuring environmental variables in greenhouses
22- Dual-stack single-radio communication architecture for UAV acting as a mobile node to collect data in WSNs
23- Development and evaluation of a UAV-photogrammetry system for precise 3D
environmental modeling
24- Prototyping a GNSS-based passiveRadar for UAVs: An instrument to classify the
waterContent feature of lands
25- Enabling UAV navigation with sensor and environmental uncertainty in cluttered
and GPS-denied environments
26- UAV-based estimation of carbon exports from heterogeneous soil landscapes—a case
study from the carboZALF experimental area
27- Wavelength-adaptive dehazing using histogram merging-based classification for
UAV images
28- A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle
Routing in Traffic Incident Monitoring ApplicationsNuméro de notice : 25930 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie En ligne : https://doi.org/10.3390/books978-3-03842-754-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96199 Unveiling movement uncertainty for robust trajectory similarity analysis / Andre Salvaro Furtado in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)
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Titre : Unveiling movement uncertainty for robust trajectory similarity analysis Type de document : Article/Communication Auteurs : Andre Salvaro Furtado, Auteur ; Luis Otavio Alvares, Auteur ; Nikos Pelekis, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 140 - 168 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] distance
[Termes IGN] données localisées
[Termes IGN] incertitude des données
[Termes IGN] mesure de similitude multidimensionnelle
[Termes IGN] méthode robuste
[Termes IGN] trace GPS
[Termes IGN] trajet (mobilité)Résumé : (Auteur) Trajectory data analysis and mining require distance and similarity measures, and the quality of their results is directly related to those measures. Several similarity measures originally proposed for time-series were adapted to work with trajectory data, but these approaches were developed for well-behaved data that usually do not have the uncertainty and heterogeneity introduced by the sampling process to obtain trajectories. More recently, similarity measures were proposed specifically for trajectory data, but they rely on simplistic movement uncertainty representations, such as linear interpolation. In this article, we propose a new distance function, and a new similarity measure that uses an elliptical representation of trajectories, being more robust to the movement uncertainty caused by the sampling rate and the heterogeneity of this kind of data. Experiments using real data show that our proposal is more accurate and robust than related work. Numéro de notice : A2018-023 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1372763 En ligne : https://doi.org/10.1080/13658816.2017.1372763 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89175
in International journal of geographical information science IJGIS > vol 32 n° 1-2 (January - February 2018) . - pp 140 - 168[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018011 RAB Revue Centre de documentation En réserve L003 Disponible Les usages des systèmes d’informations géographiques en matière de gestion de mobilité en milieu urbain : la mise en accessibilité aux personnes à mobilité réduite des arrêts de bus en Seine-Seine-Denis / Thi-Lieu Gremont-Dong (2018)
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