Descripteur
Termes IGN > imagerie > image numérique > image multitemporelle
image multitemporelleSynonyme(s)image multidate image diachroniqueVoir aussi |
Documents disponibles dans cette catégorie (187)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Object-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping / Yifang Ban in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)
[article]
Titre : Object-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping Type de document : Article/Communication Auteurs : Yifang Ban, Auteur ; Alexender Jacob, Auteur Année de publication : 2013 Article en page(s) : pp 1998 - 2006 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] conflation
[Termes IGN] fusion de données multisource
[Termes IGN] image Envisat-ASAR
[Termes IGN] image HJ-1B
[Termes IGN] image multibande
[Termes IGN] image multitemporelle
[Termes IGN] image radar moirée
[Termes IGN] Pékin (Chine)
[Termes IGN] segmentation d'image
[Termes IGN] zone urbaineRésumé : (Auteur) The objectives of this research are to develop robust methods for segmentation of multitemporal synthetic aperture radar (SAR) and optical data and to investigate the fusion of multitemporal ENVISAT advanced synthetic aperture radar (ASAR) and Chinese HJ-1B multispectral data for detailed urban land-cover mapping. Eight-date multiangle ENVISAT ASAR images and one-date HJ-1B charge-coupled device image acquired over Beijing in 2009 are selected for this research. The edge-aware region growing and merging (EARGM) algorithm is developed for segmentation of SAR and optical data. Edge detection using a Sobel filter is applied on SAR and optical data individually, and a majority voting approach is used to integrate all edge images. The edges are then used in a segmentation process to ensure that segments do not grow over edges. The segmentation is influenced by minimum and maximum segment sizes as well as the two homogeneity criteria, namely, a measure of color and a measure of texture. The classification is performed using support vector machines. The results show that our EARGM algorithm produces better segmentation than eCognition, particularly for built-up classes and linear features. The best classification result (80%) is achieved using the fusion of eight-date ENVISAT ASAR and HJ-1B data. This represents 5%, 11%, and 14% improvements over eCognition, HJ-1B, and ASAR classifications, respectively. The second best classification is achieved using fusion of four-date ENVISAT ASAR and HJ-1B data (78%). The result indicates that fewer multitemporal SAR images can achieve similar classification accuracy if multitemporal multiangle dual-look-direction SAR data are carefully selected. Numéro de notice : A2013-213 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2236560 En ligne : https://doi.org/10.1109/TGRS.2012.2236560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32351
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 4 Tome 1 (April 2013) . - pp 1998 - 2006[article]Crop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery / B. Luo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)
[article]
Titre : Crop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery Type de document : Article/Communication Auteurs : B. Luo, Auteur ; C. Yang, Auteur ; Jocelyn Chanussot, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 162 - 173 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] classification non dirigée
[Termes IGN] image hyperspectrale
[Termes IGN] image multitemporelle
[Termes IGN] rendement agricole
[Termes IGN] sorgho (céréale)Résumé : (Auteur) Hyperspectral imagery, which contains hundreds of spectral bands, has the potential to better describe the biological and chemical attributes on the plants than multispectral imagery and has been evaluated in this paper for the purpose of crop yield estimation. The spectrum of each pixel in a hyperspectral image is considered as a linear combinations of the spectra of the vegetation and the bare soil. Recently developed linear unmixing approaches are evaluated in this paper, which automatically extracts the spectra of the vegetation and bare soil from the images. The vegetation abundances are then computed based on the extracted spectra. In order to reduce the influences of this uncertainty and obtain a robust estimation results, the vegetation abundances extracted on two different dates on the same fields are then combined. The experiments are carried on the multidate hyperspectral images taken from two grain sorghum fields. The results show that the correlation coefficients between the vegetation abundances obtained by unsupervised linear unmixing approaches are as good as the results obtained by supervised methods, where the spectra of the vegetation and bare soil are measured in the laboratory. In addition, the combination of vegetation abundances extracted on different dates can improve the correlations (from 0.6 to 0.7). Numéro de notice : A2013-012 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2198826 Date de publication en ligne : 19/06/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2198826 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32150
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 1 (January 2013) . - pp 162 - 173[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible Super-resolution image analysis as a means of monitoring bracken (Pteridium aquilinum) distributions / Jennie Holland in ISPRS Journal of photogrammetry and remote sensing, vol 75 (January 2013)
[article]
Titre : Super-resolution image analysis as a means of monitoring bracken (Pteridium aquilinum) distributions Type de document : Article/Communication Auteurs : Jennie Holland, Auteur ; Paul Alpin, Auteur Année de publication : 2013 Article en page(s) : pp 48 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification dirigée
[Termes IGN] Filicophyta
[Termes IGN] image Ikonos
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] plante non ligneuse
[Termes IGN] surveillance de la végétationRésumé : (Auteur) The bracken (Pteridium aquilinum) fern is environmentally significant due to its great abundance and swift colonisation, and its perception as a problem plant in degrading agricultural or ecologically sensitive land. Various attempts have been made to map bracken using remote sensing, but these have proved relatively unsuccessful, often apparently constrained by the lack of spatial detail associated with medium spatial resolution satellite sensors such as the Landsat series. In this study, bracken was characterised using a combination of 30 m Landsat sensor imagery and 4 m IKONOS imagery. Different classification techniques were compared, including hard maximum likelihood classification and a super-resolution approach comprising soft classification and sub-pixel contouring. These techniques were applied to a range of image dates, including summer, winter and multitemporal images. Image analysis was supported by extensive field data collection, comprising both a land cover survey and stakeholder interviews. For the hard classified Landsat sensor imagery, the summer image proved least able to characterise bracken, due largely to the spectral similarity between (green) growing bracken and grasses and other vegetation. The winter images were more successful for identifying bracken due to the strong contrast between dead (brown/red) bracken and other vegetation. However, the multitemporal Landsat image was considerably more accurate than any of the single date images. The hard classified IKONOS image was more accurate overall than the Landsat sensor images for classifying land cover. Surprisingly, though, it was not comprehensively more accurate for mapping the bracken class. Notably, the producers accuracy of bracken was lower for the IKONOS image than the Landsat sensor images. This suggests image spatial resolution, although influential on the success of bracken characterisation, is not necessarily the sole or main determinant of classification accuracy. Also important are the temporal nature of image acquisition (here the multitemporal Landsat sensor image proved of considerable benefit) and the spectral characteristics of the imagery (here IKONOS’s four visible and near infrared spectral wavebands proved limited compared to the Landsat sensors’ six visible, near and shortwave infrared bands). Following soft classification of the multitemporal Landsat image, super-resolution sub-pixel contouring was applied to identify the boundary of bracken patches. Predicted bracken boundaries were assessed against actual boundaries identified using field observation and IKONOS image interpretation. For comparison, the bracken boundaries identified through hard classification (i.e. using pixel edges) were also assessed against the actual boundaries. Overall, the spatial accuracy of the super-resolution approach proved considerably higher than that of hard classification. Numéro de notice : A2013-032 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.10.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.10.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32170
in ISPRS Journal of photogrammetry and remote sensing > vol 75 (January 2013) . - pp 48 - 63[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013011 RAB Revue Centre de documentation En réserve L003 Disponible Updating land-cover maps by classification of image time series : A novel change-detection-driven transfer learning approach / Begüm Demir in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)
[article]
Titre : Updating land-cover maps by classification of image time series : A novel change-detection-driven transfer learning approach Type de document : Article/Communication Auteurs : Begüm Demir, Auteur ; Francesca Bovolo, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2013 Article en page(s) : pp 300 - 312 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage dirigé
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification automatique
[Termes IGN] détection de changement
[Termes IGN] image multitemporelle
[Termes IGN] mise à jour de base de données
[Termes IGN] série temporelleRésumé : (Auteur) This paper proposes a novel change-detection-driven transfer learning (TL) approach to update land-cover maps by classifying remote-sensing images acquired on the same area at different times (i.e., image time series). The proposed approach requires that a reliable training set is available only for one of the images (i.e., the source domain) in the time series whereas it is not for another image to be classified (i.e., the target domain). Unlike other literature TL methods, no additional assumptions on either the similarity between class distributions or the presence of the same set of land-cover classes in the two domains are required. The proposed method aims at defining a reliable training set for the target domain, taking advantage of the already available knowledge on the source domain. This is done by applying an unsupervised-change-detection method to target and source domains and transferring class labels of detected unchanged training samples from the source to the target domain to initialize the target-domain training set. The training set is then optimized by a properly defined novel active learning (AL) procedure. At the early iterations of AL, priority in labeling is given to samples detected as being changed, whereas in the remaining ones, the most informative samples are selected from changed and unchanged unlabeled samples. Finally, the target image is classified. Experimental results show that transferring the class labels from the source domain to the target domain provides a reliable initial training set and that the priority rule for AL results in a fast convergence to the desired accuracy with respect to Standard AL. Numéro de notice : A2013-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2195727 En ligne : https://doi.org/10.1109/TGRS.2012.2195727 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32153
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 1 (January 2013) . - pp 300 - 312[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible Correlation of multi-temporal ground-based optical images for landslide monitoring: Application, potential and limitations / J. Travelleti in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
[article]
Titre : Correlation of multi-temporal ground-based optical images for landslide monitoring: Application, potential and limitations Type de document : Article/Communication Auteurs : J. Travelleti, Auteur ; C. Delacourt, Auteur ; P. Allemand, Auteur ; Jean-Philippe Malet, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 39 - 55 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Alpes-de-haute-provence (04)
[Termes IGN] appariement d'images
[Termes IGN] effondrement de terrain
[Termes IGN] image à très haute résolution
[Termes IGN] image multitemporelle
[Termes IGN] interpolation
[Termes IGN] modèle numérique de terrain
[Termes IGN] risque naturel
[Termes IGN] surveillance géologiqueRésumé : (Auteur) The objective of this work is to present a low-cost methodology to monitor the displacement of continuously active landslides from ground-based optical images analyzed with a normalized image correlation technique. The performance of the method is evaluated on a series of images acquired on the Super-Sauze landslide (South French Alps) over the period 2008–2009. The image monitoring system consists of a high resolution optical camera installed on a concrete pillar located on a stable crest in front of the landslide and controlled by a datalogger. The data are processed with a cross-correlation algorithm applied to the full resolution images in the acquisition geometry. Then, the calculated 2D displacement field is orthorectified with a back projection technique using a high resolution DEM interpolated from Airborne Laser Scanning (ALS) data. The heterogeneous displacement field of the landslide is thus characterized in time and space. The performance of the technique is assessed using differential GPS surveys as reference. The sources of error affecting the results are then discussed. The strongest limitations for the application of the technique are related to the meteorological, illumination and ground surface conditions inducing partial or complete loss of coherence among the images. Small movements of the camera and the use of a mono-temporal DEM are the most important factors affecting the accuracy of the orthorectification of the displacement field. As the proposed methodology can be routinely and automatically applied, it offers promising perspectives for operational applications like, for instance, in early warning systems. Numéro de notice : A2012-288 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31734
in ISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 39 - 55[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012041 SL Revue Centre de documentation Revues en salle Disponible A framework for automatic and unsupervised detection of multiple changes in multitemporal images / Francesca Bovolo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)PermalinkRelative radiometric correction of multi-temporal ALOS AVNIR-2 data for the estimation of forest attributes / Q. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 68 (March 2012)PermalinkAutomatic cloud detection from multi-temporal satellite images: towards the use of Pléiades time series / Nicolas Champion (2012)PermalinkDamage assessment of 2010 Haïti earthquake with post-earthquake satellite image by support vector selection and adaptation / Gülsen Taskin Kaya in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 10 (October 2011)PermalinkLand cover classification of cloud-contaminated multitemporal high-resolution images / A. Salberg in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 2 (January 2011)PermalinkLand use and land cover change detection using satellite remote sensing techniques in the mountainous Three Gorges Area, China / Z. Chen in International Journal of Remote Sensing IJRS, vol 31 n° 6 (March 2010)PermalinkInfluence of resolution in irrigated area mapping and area estimations / N. Velpuri in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 12 (December 2009)PermalinkEvaluating the temporal and spatial urban expansion patterns of Guangzhou from 1979 to 2003 by remote sensing and GIS methods / F. Fan in International journal of geographical information science IJGIS, vol 23 n°11-12 (november 2009)PermalinkA matching algorithm for detecting land use changes using case-based reasoning / X. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 11 (November 2009)PermalinkApplications of remote sensing and geographic information systems for urban land-cover change studies in Mongolia / D. Amarsaikhan in Geocarto international, vol 24 n° 4 (August - September 2009)Permalink