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Ground target tracking and road map extraction / W Koch in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 3-4 (December 2006)
[article]
Titre : Ground target tracking and road map extraction Type de document : Article/Communication Auteurs : W Koch, Auteur ; J. Koller, Auteur ; M. Ulmke, Auteur Année de publication : 2006 Article en page(s) : pp 197 - 208 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification bayesienne
[Termes IGN] extraction du réseau routier
[Termes IGN] image aérienne
[Termes IGN] image radar
[Termes IGN] précision des données
[Termes IGN] trafic routierRésumé : (Auteur) For analyzing dynamic scenarios with many ground moving vehicles, airborne Ground Moving Target Indicator (GMTI) radar is well-suited due to its wide-area, all-weather, day/night, and real time capabilities. The generation of GMTI tracks from these data is the backbone for ground surveillance and traffic flow analysis. In case of dense target situations, missing detections and false alarms, Multi-Hypotheses Tracking (MHT) is the method at choice to solve the inherent ambiguities in the data-targets assignment problem. The resulting MHT-tracks are suited to extract road map information which is highly up-to-date and fairly precise. Moreover, their accuracy is quantitatively described. The precision of the extracted road segments can be improved significantly using smoothed or retrodicted tracks. In turn, the extracted road information is exploited for the precise tracking of succeeding road targets. The proposed, fully Bayesian approach is illustrated by a simulated example including Doppler and terrain obscuration, providing hints to the achievable road map accuracies. Numéro de notice : A2006-604 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2006.09.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2006.09.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28327
in ISPRS Journal of photogrammetry and remote sensing > vol 61 n° 3-4 (December 2006) . - pp 197 - 208[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 081-06091 RAB Atlas / Beau livre Centre de documentation En réserve L003 Exclu du prêt Modelling and detection of geospatial objects using texture motifs / S. Bhagavathy in IEEE Transactions on geoscience and remote sensing, vol 44 n° 12 (December 2006)
[article]
Titre : Modelling and detection of geospatial objects using texture motifs Type de document : Article/Communication Auteurs : S. Bhagavathy, Auteur Année de publication : 2006 Article en page(s) : pp 3706 - 3715 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse texturale
[Termes IGN] apprentissage dirigé
[Termes IGN] détection d'objet
[Termes IGN] distribution spatiale
[Termes IGN] image aérienne
[Termes IGN] objet géographique
[Termes IGN] texture d'imageRésumé : (Auteur) We propose the use of texture motifs, or characteristic spatially recurrent patterns, for modeling and detecting geospatial objects. A method is proposed for learning a texture-motif model from object examples and detecting objects based on the learned model. The model is learned in a two-layered framework: the first learns the constituent "texture elements" of the motif and, the second, the spatial distribution of the elements. In the experimental session, we demonstrate the model training and selection methodology for objects given a set of training examples. The utility of such models for detecting the presence or absence of geospatial objects in large aerial image datasets comprising tens of thousands of image tiles is then emphasized. Copyright IEEE Numéro de notice : A2006-561 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.881741 En ligne : https://doi.org/10.1109/TGRS.2006.881741 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28284
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 12 (December 2006) . - pp 3706 - 3715[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06121 RAB Revue Centre de documentation En réserve L003 Disponible Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing / E. Belluco in Remote sensing of environment, vol 105 n° 1 (15/11/2006)
[article]
Titre : Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing Type de document : Article/Communication Auteurs : E. Belluco, Auteur ; M. Camuffo, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 54 - 67 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] flore locale
[Termes IGN] image CASI
[Termes IGN] image hyperspectrale
[Termes IGN] image Ikonos
[Termes IGN] image MIVIS
[Termes IGN] image multibande
[Termes IGN] image Quickbird
[Termes IGN] image ROSIS
[Termes IGN] marais salé
[Termes IGN] plante halophile
[Termes IGN] VeniseRésumé : (Auteur) Tidal marshes are characterized by complex patterns both in their geomorphic and ecological features. Such patterns arise through the elaboration of a network structure driven by the tidal forcing and through the interaction between hydrodynamical, geophysical and ecological components (chiefly vegetation). Intertidal morphological and ecological structures possess characteristic extent (order of kilometers) and small-scale features (down to tens of centimeters) which are not simultaneously accessible through field observations, thus making remote sensing a necessary observation tool. This paper describes a set of remote sensing observations from several satellite and airborne platforms, the collection of concurrent ground reference data and the vegetation distributions that may be inferred from them, with specific application to the Lagoon of Venice (Italy). The data set comprises ROSIS, CASI, MIVIS, IKONOS and QuickBird acquisitions, which cover a wide range of spatial and spectral resolutions. We show that spatially-detailed and quantitatively reliable vegetation maps may be derived from remote sensing in tidal environments through unsupervised (K-means) and supervised algorithms (Maximum Likelihood and Spectral Angle Mapper). We find that, for the objective of intertidal vegetation classification, hyperspectral data contain largely redundant information. This in particular implies that a reduction of the spectral features is required for the application of the Maximum Likelihood classifier. A large number of experiments with different feature extraction/selection algorithms show that the use of four bands derived from Maximum Noise Fraction transforms and four RGBI broad bands obtained by spectral averaging yield very similar classification performances. The classifications from hyperspectral data are somewhat superior to those from multispectral data, but the close performance and the results of the features reduction experiments show that spatial resolution affects classification accuracy much more importantly than spectral resolution. Monitoring schemes of tidal environment vegetation may thus be based on high-resolution satellite acquisitions accompanied by systematic ancillary field observations at a relatively limited number of reference sites, with practical consequences of some relevance. Copyright Elsevier Numéro de notice : A2006-502 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.06.006 En ligne : https://doi.org/10.1016/j.rse.2006.06.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28226
in Remote sensing of environment > vol 105 n° 1 (15/11/2006) . - pp 54 - 67[article]Assessment of EOS aqua AMSR-E artic sea ice concentrations using Landsat-7 and airborne microwave imagery / D.J. Cavalieri in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 1 (November 2006)
[article]
Titre : Assessment of EOS aqua AMSR-E artic sea ice concentrations using Landsat-7 and airborne microwave imagery Type de document : Article/Communication Auteurs : D.J. Cavalieri, Auteur ; T. Markus, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 3057 - 3069 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] Arctique, océan
[Termes IGN] erreur moyenne quadratique
[Termes IGN] glace de mer
[Termes IGN] image aérienne
[Termes IGN] image Aqua-AMSR
[Termes IGN] image Landsat-ETM+
[Termes IGN] image radar
[Termes IGN] photographie aérienne
[Termes IGN] photographie numériqueRésumé : (Auteur) An assessment of Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) sea ice concentrations under winter conditions using ice concentrations derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery obtained during the March 2003 Arctic sea ice validation field campaign is presented. The National Oceanic and Atmospheric Administration Environmental Technology Laboratory's Airborne Polarimetric Scanning Radiometer Measurements, which were made from the National Aeronautics and Space Administration P 3B aircraft during the campaign, were used primarily as a diagnostic tool to understand the comparative results and to suggest improvements to the AMSR-E ice concentration algorithm. Based on the AMSR-E/ETM+ comparisons, a good overall agreement with little bias ($sim$1%) for areas of first year and young sea ice was found. Areas of new ice production result in a negative bias of about 5% in the AMSR-E ice concentration retrievals, with a root mean square error of 8%. Some areas of deep snow also resulted in an underestimate of the ice concentration ($sim$10%). For all ice types combined and for the full range of ice concentrations, the bias ranged from 0% to 3%, and the rms errors ranged from 1% to 7%, depending on the region. The new-ice and deep-snow biases are expected to be reduced through an adjustment of the new-ice and ice-type C algorithm tie points. Copyright IEEE Numéro de notice : A2006-508 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.878445 En ligne : https://doi.org/10.1109/TGRS.2006.878445 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28232
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 11 Tome 1 (November 2006) . - pp 3057 - 3069[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06111A RAB Revue Centre de documentation En réserve L003 Disponible Aerial surveillance / Anonyme in GEO: Geoconnexion international, vol 5 n° 10 (november - december2006)
[article]
Titre : Aerial surveillance Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2006 Article en page(s) : pp 38 - 39 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] coût
[Termes IGN] drone
[Termes IGN] image aérienne
[Termes IGN] mosaïque d'images
[Termes IGN] prise de vue aérienneRésumé : (Documentaliste) Les drones se développent et leur usage hors applications militaires permettent d'obtenir des images et des données à moindre coût. La société Oxford Metrics Group les utilise pour acquérir des données à haute résolution, pour des objets mobiles ou fixes. Numéro de notice : A2006-433 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28157
in GEO: Geoconnexion international > vol 5 n° 10 (november - december2006) . - pp 38 - 39[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 062-06101 RAB Revue Centre de documentation Revues en salle Disponible Calibration and validation of digital airborne cameras / P. Boccardo in Revue Française de Photogrammétrie et de Télédétection, n° 183 (Septembre 2006)PermalinkEvaluation of digital aerial sensors in an operational mapping environment / B.P. Olsen in Revue Française de Photogrammétrie et de Télédétection, n° 183 (Septembre 2006)PermalinkGeometric validation of imagery and products from a high performance airborne digital sensor / Jon P. Mills in Revue Française de Photogrammétrie et de Télédétection, n° 183 (Septembre 2006)PermalinkImage restoration for resolution improvement of digital aerial images: a comparison of large format digital cameras / S. Becker in Revue Française de Photogrammétrie et de Télédétection, n° 183 (Septembre 2006)PermalinkProposition de chaîne opérationnelle de reconstruction 3D de sites à partir de données spatiales ou aéroportées / H. Daudigny in XYZ, n° 108 (septembre - novembre 2006)PermalinkTests and performance evaluation of DMC images and new methods for their processing / Li Zhang in Revue Française de Photogrammétrie et de Télédétection, n° 183 (Septembre 2006)PermalinkThe ADS40 Vaihingen/Enz geometric performance test / Michael Cramer in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 6 (September 2006)PermalinkTowards 3D map generation from digital aerial images / L. Zebelin in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 6 (September 2006)PermalinkMapping carbon and water vapor fluxes in a chaparral ecosystem using vegetation indices derived from AVIRIS / D.A. Fuentes in Remote sensing of environment, vol 103 n° 3 (15 August 2006)PermalinkA patch-based image classification by integrating hyperspectral data with GIS / B. Zhang in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)Permalink