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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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4638 - 4649 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 temporelle Résumé : (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 [article]

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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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4186 - 4201 Titre : Spectral–spatial classification of hyperspectral images with a superpixel-based discriminative sparse model Type de document : Article/Communication Auteurs : Leyuan Fang, Auteur ; S. Li, Auteur ; Xudong Kang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 4186 - 4201 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme d'apprentissage [Termes IGN] analyse discriminante [Termes IGN] apprentissage automatique [Termes IGN] classification spectrale [Termes IGN] image hyperspectrale Résumé : (Auteur) A novel superpixel-based discriminative sparse model (SBDSM) for spectral-spatial classification of hyperspectral images (HSIs) is proposed. Here, a superpixel in a HSI is considered as a small spatial region whose size and shape can be adaptively adjusted for different spatial structures. In the proposed approach, the SBDSM first clusters the HSI into many superpixels using an efficient oversegmentation method. Then, pixels within each superpixel are jointly represented by a set of common atoms from a dictionary via a joint sparse regularization. The recovered sparse coefficients are utilized to determine the class label of the superpixel. In addition, instead of directly using a large number of sampled pixels as dictionary atoms, the SBDSM applies a discriminative K-SVD learning algorithm to simultaneously train a compact representation dictionary, as well as a discriminative classifier. Furthermore, by utilizing the class label information of training pixels and dictionary atoms, a class-labeled orthogonal matching pursuit is proposed to accelerate the K-SVD algorithm while still enforcing high discriminability on sparse coefficients when training the classifier. Experimental results on four real HSI datasets demonstrate the superiority of the proposed SBDSM algorithm over several well-known classification approaches in terms of both classification accuracies and computational speed. Numéro de notice : A2015-384 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2392755 En ligne : https://doi.org/10.1109/TGRS.2015.2392755 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76859 [article]

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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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4363 - 4378 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 changement Résumé : (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 [article]

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A fast classification scheme in Raman spectroscopy for the identification of mineral mixtures using a large database with correlated predictors / Corey J. Cochrane in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4259 - 4274 Titre : A fast classification scheme in Raman spectroscopy for the identification of mineral mixtures using a large database with correlated predictors Type de document : Article/Communication Auteurs : Corey J. Cochrane, Auteur ; Jordana Blacksberg, Auteur Année de publication : 2015 Article en page(s) : pp 4259 - 4274 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rayonnement électromagnétique [Termes IGN] classification automatique [Termes IGN] diffusion de Raman [Termes IGN] régression [Termes IGN] spectroscopie Résumé : (Auteur) Robust classification methods are vital to the successful implementation of many material characterization techniques, particularly where large databases exist. In this paper, we demonstrate an extremely fast classification method for the identification of mineral mixtures in Raman spectroscopy using the large RRUFF database. However, this method is equally applicable to other techniques meeting the large database criteria, these including laser-induced breakdown, X-ray diffraction, and mass spectroscopy methods. Classification of these multivariate datasets can be challenging due in part to the various obscuring features inherently present within the underlying dataset and in part to the volume and variety of information known a priori. Some of the more specific challenges include the observation of mixtures with overlapping spectral features, the use of large databases (i.e., the number of predictors far outweighs the number of observations), the use of databases that contain groups of correlated spectra, and the ever present, clouding contaminants of noise, undesired background, and spectrometer artifacts. Although many existing classification algorithms attempt to address these problems individually, not many address them as a whole. Here, we apply a multistage approach, which leverages well-established constrained regression techniques, to overcome these challenges. Our modifications to conventional algorithm implementations are shown to increase speed and performance of the classification process. Unlike many other techniques, our method is able to rapidly classify mixtures while simultaneously preserving sparsity. It is easily implemented, has very few tuning parameters, does not require extensive parameter training, and does not require data dimensionality reduction prior to classification. Numéro de notice : A2015-386 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2394377 En ligne : https://doi.org/10.1109/TGRS.2015.2394377 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76864 [article]

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Normalization of TanDEM-X DSM data in urban environments with morphological filters / Christian Geiss in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4348 - 4362 Titre : Normalization of TanDEM-X DSM data in urban environments with morphological filters Type de document : Article/Communication Auteurs : Christian Geiss, Auteur ; Michael Wurm, Auteur ; Markus Breunig, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 4348 - 4362 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Allemagne [Termes IGN] image TanDEM-X [Termes IGN] milieu urbain [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] montagne [Termes IGN] morphologie mathématique [Termes IGN] Turquie Résumé : (Auteur) The TanDEM-X mission (TDM) is a spaceborne radar interferometer which delivers a global digital surface model (DSM) with an unprecedented spatial resolution. This allows resolving objects above ground such as buildings. Extracting and characterizing those objects in an automated manner represents a challenging problem but opens simultaneously a broad range of large-area applications. In this paper, we discuss and evaluate the suitability of morphological filters (MFs) for the derivation of normalized DSMs from the TDM in complex urban environments and introduce a novel region-growing-based progressive MF procedure. This approach is jointly proposed and can be combined with a postclassification processing scheme to specifically allow for a viable reconstruction of urban morphology in a challenging terrain. The filter approach comprises a multistep procedure using concepts of morphological image filtering, region growing, and interpolation techniques. Therefore, it extends the idea of progressive MFs. The latter aim to identify nonground pixels in the DSM by gradually increasing the size of a structuring element and applying iteratively an elevation difference threshold. After the identification of initial nonground pixels, here, potential nonground pixels are identified within each iteration, and their similarity with respect to neighboring nonground pixels is assessed. Pixels are finally labeled as nonground if a constraint is fulfilled. The postclassification processing scheme adapts techniques of object-based image analyses to further refine regions of classified nonground pixels. Digital terrain models are subsequently generated by interpolating between identified ground pixels. Experimental results are obtained for settlement areas that cover large parts of the cities of Izmir (Turkey) and Wuppertal (Germany). They confirm the capability of the proposed approaches for a reduction of omission errors compared to basic MF-based methods when classifying ground pixe- s, which is favorable in a mountainous terrain with steep slopes. Numéro de notice : A2015-387 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2396195 En ligne : https://doi.org/10.1109/TGRS.2015.2396195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76866 [article]

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Change-detection map learning using matching pursuit / Y. Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4712 - 4723 Titre : Change-detection map learning using matching pursuit Type de document : Article/Communication Auteurs : Y. Li, Auteur ; Maoguo Gong, Auteur ; Licheng Jiao, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 4712 - 4723 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage automatique [Termes IGN] apprentissage dirigé [Termes IGN] couple stéréoscopique [Termes IGN] détection de changement [Termes IGN] Fleuve jaune (Chine) [Termes IGN] image ERS-SAR Résumé : (Auteur) Learning can be of great use when dealing with problems in various fields. Inspired by locally linear embedding from manifold, we propose a novel automatic change-detection method through an offline learning approach. The proposed method comprises three steps. First, two coupled dictionaries of the difference image (DI) patches and change-detection map patches are generated from known image pairs. Second, we approximately represent each patch of the input DI with respect to the DI dictionary by using the matching the pursuit algorithm. Third, the coefficients of this representation are applied with the change-detection map dictionary to generate the output change-detection map. This way, we exploit the relationship between the DI patches and the corresponding change-detection map patches based on two coupled dictionaries. In addition, the relationship guides us to construct the change-detection map for any given input DI. Experimental results on real synthetic aperture radar databases show that the proposed method is superior to its counterparts. Our method can obtain promising results, even though the dictionaries are prepared by simple random sampling from fixed training images. Numéro de notice : A2015-388 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2407953 En ligne : https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7059248 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76867 [article]

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A worldwide ionospheric model for fast precise point positioning / Adria Rovira-Garcia in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4596 - 4604 Titre : A worldwide ionospheric model for fast precise point positioning Type de document : Article/Communication Auteurs : Adria Rovira-Garcia, Auteur ; José Miguel Juan, Auteur ; Jaume Sanz, Auteur ; Guillermo Gonzalez-Casado, Auteur Année de publication : 2015 Article en page(s) : pp 4596 - 4604 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] correction ionosphérique [Termes IGN] modèle ionosphérique [Termes IGN] positionnement par GNSS [Termes IGN] positionnement ponctuel précis [Termes IGN] résolution d'ambiguïté [Termes IGN] temps réel [Vedettes matières IGN] Traitement de données GNSS Résumé : (Auteur) Fast precise point positioning (Fast-PPP) is a satellite-based navigation technique using an accurate real-time ionospheric modeling to achieve high accuracy quickly. In this paper, an end-to-end performance assessment of Fast-PPP is presented in near-maximum Solar Cycle conditions; from the accuracy of the Central Processing Facility corrections, to the user positioning. A planetary distribution of permanent receivers including challenging conditions at equatorial latitudes, is navigated in pure kinematic mode, located from 100 to 1300 km away from the nearest reference station used to derive the ionospheric model. It is shown that satellite orbits and clocks accurate to few centimeters and few tenths of nanoseconds, used in conjunction with an ionosphere with an accuracy better than 1 Total Electron Content Unit (16 cm in L1) reduce the convergence time of dual-frequency Precise Point Positioning, to decimeter-level (3-D) solutions. Horizontal convergence times are shortened 40% to 90%, whereas the vertical components are reduced by 20% to 60%. A metric to evaluate the quality of any ionospheric model for Global Navigation Satellite System is also proposed. The ionospheric modeling accuracy is directly translated to mass-market single-frequency users. The 95th percentile of horizontal and vertical accuracies is shown to be 40 and 60 cm for single-frequency users and 9 and 16 cm for dual-frequency users. The tradeoff between the formal and actual positioning errors has been carefully studied to set realistic confidence levels to the corrections. Numéro de notice : A2015-389 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2402598 En ligne : https://doi.org/10.1109/TGRS.2015.2402598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76869 [article]

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Lidars with narrow FOV for daylight measurements / Ronald Eixmann in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4548 - 4553 Titre : Lidars with narrow FOV for daylight measurements Type de document : Article/Communication Auteurs : Ronald Eixmann, Auteur ; Michael Gerding, Auteur ; Josef Höffner, Auteur ; Maren Kopp, Auteur Année de publication : 2015 Article en page(s) : pp 4548 - 4553 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Atmosphère [Termes IGN] atmosphère terrestre [Termes IGN] faisceau laser [Termes IGN] Lidar [Termes IGN] téléscope Résumé : (Auteur) Daytime lidar operation in the middle atmosphere requires a narrow field of view (FOV) of the receiving telescope for effective background reduction and a high-transmission narrow-band detection. The laser beam position in the atmosphere relative to the optical axis of the receiving telescope is subject to high-frequency disturbances such as turbulence, vibration, and wind as well as comparable slow drift (thermal effects of the laser, stability of the building, etc.). We developed a beam stabilization system (BSS) that ensured a pulse-to-pulse stabilization of the laser beam with ~ 3 μrad remaining jitter, allowing ~ 60 μrad FOV. With BSS and single-pulse data acquisition system, the optimal alignment of the laser and telescope can be controlled, and information on the FOV and laser divergence in the far field can be derived. The capability of the BSS is to stabilize the laser against all internal and external disturbances below the repetition rate of the laser. Numéro de notice : A2015-390 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2401333 En ligne : https://doi.org/10.1109/TGRS.2015.2401333 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76871 [article]

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