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A robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products / Yuxin Zhu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
[article]
Titre : A robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products Type de document : Article/Communication Auteurs : Yuxin Zhu, Auteur ; Emily Lei Kang, Auteur ; Yanchen Bo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 5021 - 5035 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multirésolution
[Termes IGN] changement climatique
[Termes IGN] climat terrestre
[Termes IGN] erreur systématique
[Termes IGN] exhaustivité des données
[Termes IGN] image Aqua-MODIS
[Termes IGN] interpolation linéaire
[Termes IGN] krigeage
[Termes IGN] méthode robuste
[Termes IGN] température de surface de la merRésumé : (Auteur) Sea surface temperature (SST) plays a vital role in the Earth's atmosphere and climate systems. Complete and accurate SST observations are in great demand for forecasting tropical cyclones and projecting climate change. Satellite remote sensing has been used to retrieve SST globally, but missing values and biased observations impose difficulties on practical applications of these satellite-derived SST data. Conventional spatial statistics methods such as kriging have been widely used to fill the gaps. However, when such conventional methods are used to analyze a massive satellite data set of size n, the inversion of the n × n covariance matrix may require O(n3) computations, which make the computation very intensive or even infeasible. The fixed rank kriging (FRK) performs dimension reduction through multiresolution wavelet analysis so that it can dramatically reduce the computation cost of various kriging methods. However, the FRK cannot directly be used for incomplete data over spatially irregular regions such as SSTs, and the potential bias in the satellite data is not addressed. In this paper, we construct a data-driven bias-correction model for the correction of the bias in satellite SSTs and develop a robust FRK (R-FRK) method so that the dimension reduction can be used to the satellite data in irregular regions with missing data. We implement the bias-correction model and the R-FRK to the level-3 mapped night Moderate Resolution Imaging Spectroradiometer SSTs. The accuracy of the resulting predictions is assessed using the colocated drifting buoy SST observations, in terms of mean bias (bias), root-mean-squared error, and R squared (R2). The spatial completeness is assessed by the availability of ocean pixels. The assessment results show that the spatially. Numéro de notice : A2015-530 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2416351 Date de publication en ligne : 17/04/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2416351 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77558
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 9 (September 2015) . - pp 5021 - 5035[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015091 SL Revue Centre de documentation Revues en salle Disponible An unsupervised urban change detection procedure by using luminance and saturation for multispectral remotely sensed images / Su Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 8 (August 2015)
[article]
Titre : An unsupervised urban change detection procedure by using luminance and saturation for multispectral remotely sensed images Type de document : Article/Communication Auteurs : Su Ye, Auteur ; Dongmei Chen, Auteur Année de publication : 2015 Article en page(s) : pp 637 - 645 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification non dirigée
[Termes IGN] détection de changement
[Termes IGN] image multibande
[Termes IGN] luminance lumineuse
[Termes IGN] milieu urbain
[Termes IGN] saturation de la couleurRésumé : (auteur) Unsupervised change detection techniques have been widely employed in the remote-sensing area when suitable reference data is not available. Image (or Index) differencing is one of the most commonly used methods due to its simplicity. However, past applications of image differencing were often inefficient in separating real change and noise due to the lack of steps for feature selection and integration of contextual information. To address these issues, we propose a novel unsupervised procedure which uses two complementary features, namely luminance and saturation, extracted from multispectral images, and combines T-point thresholding, Bayes fusion, and Markov Random Fields. Through a case study, the performance of our proposed procedure was compared with other three unsupervised changedetection methods including Principle Component Analysis (PCA), Fuzzy c-means (FCM), and Expectation Maximum-Markov Random Field (EM-MRF). The change detection results from our proposed method are more compact with less noise than those from other methods over urban areas. The quantitative accuracy assessment indicates that the overall accuracy and Kappa statistic of our proposed procedure are 95.1 percent and 83.3 percent, respectively, which are significantly higher than the other three unsupervised change detection methods Numéro de notice : A2015-982 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.8.637 En ligne : http://dx.doi.org/10.14358/PERS.81.8.637 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80253
in Photogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 8 (August 2015) . - pp 637 - 645[article]A local approach to optimize the scale parameter in multiresolution segmentation for multispectral imagery / F. Cánovas-García in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)
[article]
Titre : A local approach to optimize the scale parameter in multiresolution segmentation for multispectral imagery Type de document : Article/Communication Auteurs : F. Cánovas-García, Auteur ; Francisco Alonso‐Sarría, Auteur Année de publication : 2015 Article en page(s) : pp 937 - 961 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] facteur d'échelle
[Termes IGN] image multibande
[Termes IGN] mise à l'échelle
[Termes IGN] segmentation d'image
[Termes IGN] segmentation multi-échelleRésumé : (Auteur) The results obtained using the object-based image analysis approach for remote sensing image analysis depend strongly on the quality of the segmentation step. In this paper, to optimize the scale parameter in a multiresolution segmentation, we analyse a high-resolution image of a large and heterogeneous agricultural area. This approach is based on using a set of agricultural plots extracted from official maps as uniform spatial units. The scale parameter is then optimized in each uniform spatial unit. Intra-object and inter-object heterogeneity measurements are used to evaluate each segmentation. To avoid subsegmentation, some oversegmentation is allowed, but is attenuated in a second step using the spectral difference segmentation algorithm. The statistical distribution of the scale parameter is not equal in all land uses, indicating the soundness of this local approach. A quantitative assessment of the results was also conducted for the different land covers. The results indicate that the spectral contrast between objects is larger with the local approach than with the global approach. These differences were statistically significant in all land uses except irrigated fruit trees and greenhouses. In the absence of subsegmentation, this suggests that the objects will be placed far apart in the space of variables, even if they are very close in the physical space. This is an obvious advantage in a subsequent classification of the objects. Numéro de notice : A2015-505 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1004131 Date de publication en ligne : 18/02/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2015.1004131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77422
in Geocarto international > vol 30 n° 7 - 8 (August - September 2015) . - pp 937 - 961[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Measuring the directional variations of land surface reflectance from MODIS / François-Marie Bréon in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)
[article]
Titre : Measuring the directional variations of land surface reflectance from MODIS Type de document : Article/Communication Auteurs : François-Marie Bréon, Auteur ; Eric F. Vermote, Auteur ; Emilie Fedele Murphy, Auteur ; Belen Franch, Auteur Année de publication : 2015 Article en page(s) : pp 4638 - 4649 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] filtrage du bruit
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] réflectance de surface
[Termes IGN] série temporelleRésumé : (Auteur) The directional variation of land surface reflectance generates an apparent noise in the time series acquired from satellites with variable observation geometries, which can be corrected through appropriate modeling of the bidirectional reflectance distribution function (BRDF). In a previous paper, we described and validated the VJB method that estimates a target BRDF shape and corrects for directional effects and yet retains the high temporal resolution of the measurement. Here, we analyze its potential to measure the BRDF of targets at the 0.5-km resolution of Moderate Resolution Imaging Spectroradiometer (MODIS). The description of the BRDF in the NASA MCD43A1 product shows very large temporal variations that are unrealistic. However, the reflectance time series, normalized to a standard observation geometry using this modeling, have a similar quality as those derived using VJB. Conversely, the MCD43A1 modeled reflectances for a nonstandard geometry are unrealistically variable. These results indicate that the standard BRDF model inversion used to derive the MCD43A1 product is underconstrained due to the limited directional sampling of the 16-day composite period. The apparent noise in the corrected reflectance time series is significantly larger than the one obtained at lower spatial resolution, and is very much a function of the spatial heterogeneity of the area surrounding the target. These results strongly indicate that the multitemporal MODIS measurement at high spatial resolution (0.5 km) is affected by a change in the effective resolution for off-nadir observation and by inaccurate registration. The resulting noise in the measurements precludes an accurate measurement of the BRDF at such a scale. Numéro de notice : A2015-369 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2405344 En ligne : https://doi.org/10.1109/TGRS.2015.2405344 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76806
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4638 - 4649[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015081 RAB Revue Centre de documentation En réserve L003 Disponible Sequential spectral change vector analysis for iteratively discovering and detecting multiple changes in hyperspectral images / Sicong Liu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)
[article]
Titre : Sequential spectral change vector analysis for iteratively discovering and detecting multiple changes in hyperspectral images Type de document : Article/Communication Auteurs : Sicong Liu, Auteur ; Lorenzo Bruzzone, Auteur ; Francesca Bovolo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 4363 - 4378 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection de changement
[Termes IGN] image AVIRIS
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] image multitemporelle
[Termes IGN] méthode des vecteurs de changement
[Termes IGN] représentation du changementRésumé : (Auteur) This paper presents an effective semiautomatic method for discovering and detecting multiple changes (i.e., different kinds of changes) in multitemporal hyperspectral (HS) images. Differently from the state-of-the-art techniques, the proposed method is designed to be sensitive to the small spectral variations that can be identified in HS images but usually are not detectable in multispectral images. The method is based on the proposed sequential spectral change vector analysis, which exploits an iterative hierarchical scheme that at each iteration discovers and identifies a subset of changes. The approach is interactive and semiautomatic and allows one to study in detail the structure of changes hidden in the variations of the spectral signatures according to a top-down procedure. A novel 2-D adaptive spectral change vector representation (ASCVR) is proposed to visualize the changes. At each level this representation is optimized by an automatic definition of a reference vector that emphasizes the discrimination of changes. Finally, an interactive manual change identification is applied for extracting changes in the ASCVR domain. The proposed approach has been tested on three hyperspectral data sets, including both simulated and real multitemporal images showing multiple-change detection problems. Experimental results confirmed the effectiveness of the proposed method. Numéro de notice : A2015-385 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2396686 En ligne : https://doi.org/10.1109/TGRS.2015.2396686 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76861
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4363 - 4378[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015081 RAB Revue Centre de documentation En réserve L003 Disponible Spectral–spatial classification of hyperspectral images with a superpixel-based discriminative sparse model / Leyuan Fang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)PermalinkTesting the reliability and stability of the internal accuracy assessment of random forest for classifying tree defoliation levels using different validation methods / Samuel Adelabu in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)PermalinkDétermination de la précision planimétrique des images Google Earth haute-résolution de Rome (2ème partie) / Guiseppe Pulighe in Géomatique expert, n° 105 (juillet - août 2015)PermalinkHyperspectral and multispectral image fusion based on a sparse representation / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkLocal binary patterns and extreme learning machine for hyperspectral imagery classification / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkMulticlass feature learning for hyperspectral image classification: Sparse and hierarchical solutions / Devis Tuia in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)PermalinkA novel negative abundance‐oriented hyperspectral unmixing algorithm / Rubén Marrero in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkSemantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers / Martin Weinmann in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)PermalinkSpectral–spatial kernel regularized for hyperspectral image denoising full text / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkToward evaluating multiscale segmentations of high spatial resolution remote sensing images / Xueliang Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkAnalysis on the dynamic deformations of the images from digital film sequences / Tomasz Markowski in Geodesy and cartography, vol 64 n° 1 (June 2015)PermalinkAssessment of wildfire risk in Lebanon using geographic object-based image analysis / George Mitri in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)PermalinkExtension of the linear chromodynamics model for spectral change detection in the presence of residual spatial misregistration / Karmon Vongsy in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)PermalinkFast forward feature selection of hyperspectral images for classification with gaussian mixture models / Mathieu Fauvel in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 8 n° 6 (June 2015)PermalinkA fuzzy spatial reasoner for multi-scale GEOBIA ontologies / Argyros Argyridis in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)PermalinkIntegrating user needs on misclassification error sensitivity into image segmentation quality assessment / Hugo Costa in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)PermalinkMTF-adjusted pansharpening approach based on coupled multiresolution decompositions / Abdelaziz Kallel in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)PermalinkObject-based building change detection from a single multispectral image and pre-existing geospatial information / Georgia Doxani in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)PermalinkObject detection in optical remote sensing images based on weakly supervised learning and high-level feature learning / Junwei Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)PermalinkSemi-automated building footprint extraction from orthophotos / Rheannon Brooks in Geomatica, vol 69 n° 2 (June 2015)PermalinkSubstance dependence constrained sparse NMF for hyperspectral unmixing / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)PermalinkVery high resolution image matching based on local features and k-means clustering / Amin Sedaghat in Photogrammetric record, vol 30 n° 150 (June - 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