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Memory-based cluster sampling for remote sensing image classification / Michele Volpi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
[article]
Titre : Memory-based cluster sampling for remote sensing image classification Type de document : Article/Communication Auteurs : Michele Volpi, Auteur ; Devis Tuia, Auteur ; Mikhail Kanevski, Auteur Année de publication : 2012 Article en page(s) : pp 3096 - 3106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image à très haute résolution
[Termes IGN] image hyperspectraleRésumé : (Auteur) In this paper, we address the problem of semi-automatic definition of training sets for the classification of remotely sensed images. We propose two approaches based on active learning aiming at removing both the proximal (low diversity) and the dense (low exploration during iterations) sampling redundancies. The first is encountered when several samples carrying similar spectral information are selected by the algorithm, while the second occurs when the heuristic is unable to explore undiscovered parts of the feature space during iterations. For this purpose, kernel k-means is used to cluster a set of uncertain candidates in the same space spanned by the kernel function defined in the SVM classification step. Two heuristics are proposed to maximize the speed of convergence to high classification accuracies: The first is based on binary hierarchical partitioning of the set of selected uncertain samples, while the second extends this approach by considering memory in the selection and thus dynamically adapts to the problem throughout the iterations. Experiments on both VHR and hyperspectral imagery confirm fast convergence of the algorithm, that outperforms state-of-the-art sampling schemes. Numéro de notice : A2012-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179661 Date de publication en ligne : 21/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31829
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3096 - 3106[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible Satellite image time series analysis under time warping / F. Petitjean in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
[article]
Titre : Satellite image time series analysis under time warping Type de document : Article/Communication Auteurs : F. Petitjean, Auteur ; Jordi Inglada, Auteur ; Pierre Gançarski, Auteur Année de publication : 2012 Article en page(s) : pp 3081 - 3095 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] déformation temporelle dynamique (algorithme)
[Termes IGN] échantillon
[Termes IGN] image optique
[Termes IGN] série temporelleRésumé : (Auteur) Satellite Image Time Series are becoming increasingly available and will continue to do so in the coming years thanks to the launch of space missions which aim at providing a coverage of the Earth every few days with high spatial resolution. In the case of optical imagery, it will be possible to produce land use and cover change maps with detailed nomenclatures. However, due to meteorological phenomena, such as clouds, these time series will become irregular in terms of temporal sampling, and one will need to compare time series with different lengths. In this paper, we present an approach to image time series analysis which is able to deal with irregularly sampled series and which also allows the comparison of pairs of time series where each element of the pair has a different number of samples. We present the dynamic time warping from a theoretical point of view and illustrate its capabilities with two applications to real-time series. Numéro de notice : A2012-382 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179050 Date de publication en ligne : 31/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31828
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3081 - 3095[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible Spatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland / L. Poggio in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
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Titre : Spatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland Type de document : Article/Communication Auteurs : L. Poggio, Auteur ; A. Gimona, Auteur ; I. Brown, Auteur Année de publication : 2012 Article en page(s) : pp 56 - 72 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification pixellaire
[Termes IGN] Ecosse
[Termes IGN] image CMODIS
[Termes IGN] interpolation
[Termes IGN] krigeage
[Termes IGN] nuage
[Termes IGN] ombre
[Termes IGN] résiduRésumé : (Auteur) Time series of satellite data have an important role in the monitoring of regional and global ecosystem properties. Satellite images often present missing data due to atmospheric aerosol, clouds or other atmospheric conditions. Most methods proposed to minimise the effects of degradation and to restore signal values do not take into account the spatial and temporal correlation of the values in the pixels. The aim of this study was to propose and test a spatio-temporal interpolation method to reconstruct pixel values in MODIS data time series that are missing due to cloud cover or other image noise. The method presented and tested is an example of a hybrid Generalised Additive Model (GAM)-geostatistical space-time model, including the fitting of a smoother spatio-temporal trend and a spatial component to account for local details supported by information in covariates. The method is not limited by the type of noise or degradation of pixels values, latitude, vegetation dynamics and land uses. The application of cloud masks on the target image provided the data for a quantitative validation through the comparison between the modelled EVI values and those from the MODIS product. The method was able to restore data providing very good to adequate responses in series of simulations of missing data. The comparison of distributions showed good agreement and predictive capabilities. The spatio-temporal method always performed better and the use of kriged residuals was helpful for situations with high percentages of missing data. The spatial pattern and the local features were well preserved for cloud coverage Numéro de notice : A2012-494 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.06.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31940
in ISPRS Journal of photogrammetry and remote sensing > vol 72 (August 2012) . - pp 56 - 72[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012061 SL Revue Centre de documentation Revues en salle Disponible Synthesizing urban remote sensing through application, scale, data and case studies / E.A. Wentz in Geocarto international, vol 27 n° 5 (August 2012)
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Titre : Synthesizing urban remote sensing through application, scale, data and case studies Type de document : Article/Communication Auteurs : E.A. Wentz, Auteur ; D.A. Quattrochi, Auteur ; M. Netzband, Auteur ; S.W. Myint, Auteur Année de publication : 2012 Article en page(s) : pp 425 - 442 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Atlanta (Géorgie)
[Termes IGN] chaleur
[Termes IGN] classification barycentrique
[Termes IGN] classification ISODATA
[Termes IGN] image Landsat-MSS
[Termes IGN] image Landsat-TM
[Termes IGN] image Quickbird
[Termes IGN] image Terra-ASTER
[Termes IGN] milieu urbain
[Termes IGN] Phoenix
[Termes IGN] villeRésumé : (Auteur) This article describes the outcomes of an international workshop on urban remote sensing. The workshop synthesized the needs of remote sensing scientists to better monitor and analyse urban physical and social dynamics. The workshop was held with urban land use forecasting workshop in April 2011 in Arizona. The four major themes of the jointly held workshops were application, data, scale and case studies. Application refers to how data are used to address urban problems. Data refers to the sources and types of raw data available. Scale is the ever-present concern over data reduction and resolution. Case studies examine a single urban area, typically based on one or two primary themes. One outcome was to integrate multiple case studies to form an urban typology. To respond to this need, this article integrates two case studies on the urban heat island in Atlanta, GA and Phoenix, AZ based on the four themes. Numéro de notice : A2012-372 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.687400 Date de publication en ligne : 24/05/2012 En ligne : https://doi.org/10.1080/10106049.2012.687400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31818
in Geocarto international > vol 27 n° 5 (August 2012) . - pp 425 - 442[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012051 RAB Revue Centre de documentation En réserve L003 Disponible Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
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Titre : Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan Type de document : Article/Communication Auteurs : F. Yang, Auteur ; B. Matsushita, Auteur ; T. Fukushima, Auteur ; W. Yang, Auteur Année de publication : 2012 Article en page(s) : pp 90 - 98 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges temporels
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat-TM
[Termes IGN] image optique
[Termes IGN] Japon
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelle
[Termes IGN] surface imperméableRésumé : (Auteur) As a proxy measure of the human ecological footprint, impervious surface area (ISA) has recently become a key concept in the field of urban remote sensing, with a focus on estimation of the ISA at a city-scale by using Landsat-style satellite images. However, ISA estimation is also in demand in disciplines such as the environmental assessment and policy making at a national scale. This paper proposes a new method for estimating the ISA fraction in Japan based on a temporal mixture analysis (TMA) technique. The required inputs for the proposed method are rearranged MODIS NDVI time-series datasets at the temporal stable zone (i.e., the first to the sixth largest NDVI values in a year). Three ISA distribution maps obtained from Landsat-5 TM data were used as reference maps to evaluate the performance of the proposed method. The results showed that the proposed TMA-based method achieved a large reduction in the effects of endmember variability compared with the previous methods (e.g., SMA and NSMA), and thus the new method has promising accuracy for estimating ISA in Japan. The overall root mean square error (RMSE) of the proposed method was 8.7%, with a coefficient of determination of 0.86, and there was no obvious underestimation or overestimation for the whole ISA range. Numéro de notice : A2012-495 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31941
in ISPRS Journal of photogrammetry and remote sensing > vol 72 (August 2012) . - pp 90 - 98[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012061 SL Revue Centre de documentation Revues en salle Disponible Detecting and correcting motion blur from images shot with channel-dependent exposure time / Lâmân Lelégard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkExtraction of vineyards out of aerial photo-image using texture information / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkStreamed vertical rectangle detection in terrestrial laser scans for facade database / Jérôme Demantké in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkAn automated approach for updating land cover maps based on integrated change detection and classification methods / X. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)PermalinkApplication of time series Landsat images to examining land-use / land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)PermalinkLatent class modeling for site- and non-site-specific classification accuracy assessment without ground data / Giles M. Foody in IEEE Transactions on geoscience and remote sensing, vol 50 n° 7 Tome 2 (July 2012)PermalinkRepresentative multiple Kernel learning for classification in hyperspectral imagery / Y. Gu in IEEE Transactions on geoscience and remote sensing, vol 50 n° 7 Tome 2 (July 2012)PermalinkThe potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)PermalinkVerification of 2D building outlines using oblique airborne images / A. Nyaruhuma in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)PermalinkComparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points / Y. Shao in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)Permalink