IEEE Transactions on geoscience and remote sensing / IEEE Geoscience and remote sensing society (Etats-Unis) . vol 54 n° 1Paru le : 01/01/2016 |
[n° ou bulletin]
est un bulletin de IEEE Transactions on geoscience and remote sensing / IEEE Geoscience and remote sensing society (Etats-Unis) (1986 -)
[n° ou bulletin]
|
Exemplaires(1)
Code-barres | Cote | Support | Localisation | Section | Disponibilité |
---|---|---|---|---|---|
065-2016011 | SL | Revue | Centre de documentation | Revues en salle | Disponible |
Dépouillements
Ajouter le résultat dans votre panierMicrowave unmixing with video segmentation for inferring broadleaf and needleleaf brightness temperatures and abundances from mixed forest observations / Lingjia Gu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Microwave unmixing with video segmentation for inferring broadleaf and needleleaf brightness temperatures and abundances from mixed forest observations Type de document : Article/Communication Auteurs : Lingjia Gu, Auteur ; Kai Zhao, Auteur ; Bormin Huang, Auteur Année de publication : 2016 Article en page(s) : pp 279 - 286 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aiguille
[Termes IGN] densité de la végétation
[Termes IGN] feuille (végétation)
[Termes IGN] peuplement forestier
[Termes IGN] peuplement mélangé
[Termes IGN] segmentation d'image
[Termes IGN] traitement d'image
[Termes IGN] vidéo numériqueRésumé : (Auteur) Passive microwave sensors have better capability of penetrating forest layers to obtain more information from forest canopy and ground surface. For forest management, it is useful to study passive microwave signals from forests. Passive microwave sensors can detect signals from needleleaf, broadleaf, and mixed forests. The observed brightness temperature of a mixed forest can be approximated by a linear combination of the needleleaf and broadleaf brightness temperatures weighted by their respective abundances. For a mixed forest observed by an N-band microwave radiometer with horizontal and vertical polarizations, there are 2 N observed brightness temperatures. It is desirable to infer 4 N + 2 unknowns: 2 N broadleaf brightness temperatures, 2 N needleleaf brightness temperatures, 1 broadleaf abundance, and 1 needleleaf abundance. This is a challenging underdetermined problem. In this paper, we devise a novel method that combines microwave unmixing with video segmentation for inferring broadleaf and needleleaf brightness temperatures and abundances from mixed forests. We propose an improved Otsu method for video segmentation to infer broadleaf and needleleaf abundances. The brightness temperatures of needleleaf and broadleaf trees can then be solved by the nonnegative least squares solution. For our mixed forest unmixing problem, it turns out that the ordinary least squares solution yields the desired positive brightness temperatures. The experimental results demonstrate that the proposed method is able to unmix broadleaf and needleleaf brightness temperatures and abundances well. The absolute differences between the reconstructed and observed brightness temperatures of the mixed forest are well within 1 K. Numéro de notice : A2016-069 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2455151 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2455151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79831
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 279 - 286[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Passive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E / Jinyang Du in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Passive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E Type de document : Article/Communication Auteurs : Jinyang Du, Auteur ; John S. Kimball, Auteur ; Lucas A. Jones, Auteur Année de publication : 2016 Article en page(s) : pp 597 - 608 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] capteur passif
[Termes IGN] estimation statistique
[Termes IGN] humidité du sol
[Termes IGN] image Aqua-AMSR
[Termes IGN] réflectance végétale
[Termes IGN] rétrodiffusion
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] variation saisonnière
[Termes IGN] végétationRésumé : (Auteur) Accurate mapping of long-term global soil moisture is of great importance to earth science studies and a variety of applications. An approach for deriving volumetric soil moisture using satellite passive microwave radiometry from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) was developed in this study. Unlike the major AMSR-E retrieval algorithms that assume fixed scattering albedo values over the globe, the proposed algorithm adopts a weighted averaging strategy for soil moisture estimation based on a dynamic selection of albedo values that are empirically determined. The resulting soil moisture retrievals demonstrate more realistic global patterns and seasonal dynamics relative to the baseline University of Montana soil moisture product. Quantitative analysis of the new approach against in situ soil moisture measurements over four study regions also indicates improvements over the baseline algorithm, with coefficients of determination (R2) between the retrievals and in situ measurements increasing by approximately 16.9% and 41.5% and bias-corrected root-mean-square errors decreasing by about 25.0% and 38.2% for ascending and descending orbital data records, respectively. The resulting algorithm is readily applied to similar microwave sensors, including the Advanced Microwave Scanning Radiometer 2, and its retrieval strategy is also applicable to other passive microwave sensors, including lower frequency (L-band) observations from the National Aeronautics and Space Administration Soil Moisture Active Passive mission. Numéro de notice : A2016-070 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2462758 En ligne : https://doi.org/10.1109/TGRS.2015.2462758 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79832
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 597 - 608[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration / Wei He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration Type de document : Article/Communication Auteurs : Wei He, Auteur ; Hongyan Zhang, Auteur ; Liangpei Zhang, Auteur ; Huanfeng Shen, Auteur Année de publication : 2016 Article en page(s) : pp 178 - 188 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] factorisation
[Termes IGN] factorisation de matrice non-négative
[Termes IGN] image hyperspectrale
[Termes IGN] matrice
[Termes IGN] restauration d'imageRésumé : (Auteur) In this paper, we present a spatial spectral hyperspectral image (HSI) mixed-noise removal method named total variation (TV)-regularized low-rank matrix factorization (LRTV). In general, HSIs are not only assumed to lie in a low-rank subspace from the spectral perspective but also assumed to be piecewise smooth in the spatial dimension. The proposed method integrates the nuclear norm, TV regularization, and L1-norm together in a unified framework. The nuclear norm is used to exploit the spectral low-rank property, and the TV regularization is adopted to explore the spatial piecewise smooth structure of the HSI. At the same time, the sparse noise, which includes stripes, impulse noise, and dead pixels, is detected by the L1-norm regularization. To tradeoff the nuclear norm and TV regularization and to further remove the Gaussian noise of the HSI, we also restrict the rank of the clean image to be no larger than the number of endmembers. A number of experiments were conducted in both simulated and real data conditions to illustrate the performance of the proposed LRTV method for HSI restoration. Numéro de notice : A2016-071 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2452812 En ligne : https://doi.org/10.1109/TGRS.2015.2452812 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79834
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 178 - 188[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible A multilinear mixing model for nonlinear spectral unmixing / Rob Heylen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : A multilinear mixing model for nonlinear spectral unmixing Type de document : Article/Communication Auteurs : Rob Heylen, Auteur ; Paul Scheunders, Auteur Année de publication : 2016 Article en page(s) : pp 240 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image hyperspectrale
[Termes IGN] modèle de mélange multilinéaire
[Termes IGN] modèle linéaireRésumé : (Auteur) In hyperspectral unmixing, bilinear and linear-quadratic models have become popular recently, and also the polynomial postnonlinear model shows promising results. These models do not consider endmember interactions involving more than two endmembers, although such interactions might compose a nontrivial part of the observed spectrum in scenarios involving bright materials and complex geometrical structures, such as vegetation and intimate mixtures. In this paper, we present an extension of these models to include an infinite number of interactions. Several technical problems, such as divergence of the resulting series, can be avoided by introducing an optical interaction probability, which becomes the only free parameter of the model in addition to the abundances. We present an unmixing strategy based on this multilinear mixing (MLM) model; present comparisons with the bilinear models and the Hapke model for intimate mixing; and show that, in several scenarios, the MLM model obtains superior results. Numéro de notice : A2016-072 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2453915 En ligne : https://doi.org/10.1109/TGRS.2015.2453915 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79837
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 240 - 251[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Spectral–spatial adaptive sparse representation for hyperspectral image denoising / Ting Lu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Spectral–spatial adaptive sparse representation for hyperspectral image denoising Type de document : Article/Communication Auteurs : Ting Lu, Auteur ; Shutao Li, Auteur ; Leyuan Fang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 373 - 385 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] bruit blanc
[Termes IGN] filtrage du bruit
[Termes IGN] image hyperspectraleRésumé : (Auteur) In this paper, a novel spectral-spatial adaptive sparse representation (SSASR) method is proposed for hyperspectral image (HSI) denoising. The proposed SSASR method aims at improving noise-free estimation for noisy HSI by making full use of highly correlated spectral information and highly similar spatial information via sparse representation, which consists of the following three steps. First, according to spectral correlation across bands, the HSI is partitioned into several nonoverlapping band subsets. Each band subset contains multiple continuous bands with highly similar spectral characteristics. Then, within each band subset, shape-adaptive local regions consisting of spatially similar pixels are searched in spatial domain. This way, spectral-spatial similar pixels can be grouped. Finally, the highly correlated and similar spectral-spatial information in each group is effectively used via the joint sparse coding, in order to generate better noise-free estimation. The proposed SSASR method is evaluated by different objective metrics in both real and simulated experiments. The numerical and visual comparison results demonstrate the effectiveness and superiority of the proposed method. Numéro de notice : A2016-073 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2457614 En ligne : https://doi.org/10.1109/TGRS.2015.2457614 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79841
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 373 - 385[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Detection and labeling of sensitive areas in hydrological cartography using vector statistics / Elia Quirós in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Detection and labeling of sensitive areas in hydrological cartography using vector statistics Type de document : Article/Communication Auteurs : Elia Quirós, Auteur ; María-Eugenia Polo, Auteur ; Ángel M. Felicísimo, Auteur Année de publication : 2016 Article en page(s) : pp 189 - 196 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] carte hydrographique
[Termes IGN] détection automatique
[Termes IGN] données vectorielles
[Termes IGN] modèle numérique de terrain
[Termes IGN] réseau hydrographique
[Termes IGN] statistique descriptive
[Termes IGN] système d'information géographiqueRésumé : (Auteur) The recognition and delineation of hydrological stream lines has, traditionally, been a subjective manual task in cartography. However, digital elevation models (DEMs) are nowadays often employed to extract stream lines automatically, via the use of geographic information systems. Whereas the automatic generation of hydrological networks presents errors, their manual recognition can be almost arbitrary. In this paper, we propose a methodology with which to label potentially sensitive zones in the comparison of hydrological cartographic networks. Two different sources were analyzed: a conventional cartographic stream network, and one automatically extracted from a DEM. The 72 500 vectors of displacement, representing the spatial disagreement (or fit) between the stream networks, were also examined. A number of remarkable distributions of large errors were identified that were a cause for alarm; these errors are here denoted by “warnings” and are classified into six different groups. The displacement vectors were also analyzed in terms of modulus and azimuth, thereby allowing the analysis of the isotropy of the spatial displacements. We propose the use of all of the derived information as metadata for hydrological spatial quality, as well as the extension of the methodology to any other type of cartographic element (roads, cadastral, etc.) for which two different vector format information sources are compared. Numéro de notice : A2016-074 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2453112 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2453112 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79842
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 189 - 196[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Forcing scale invariance in multipolarization SAR change detection / Vincenzo Carotenuto in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Forcing scale invariance in multipolarization SAR change detection Type de document : Article/Communication Auteurs : Vincenzo Carotenuto, Auteur ; Antonio de Maio, Auteur ; Carmine Clemente, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 36 - 50 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] détection de changement
[Termes IGN] image radar moirée
[Termes IGN] invariance
[Termes IGN] matrice
[Termes IGN] polarimétrie radar
[Termes IGN] polarisationRésumé : (Auteur) This paper considers the problem of coherent (in the sense that both amplitudes and relative phases of the polarimetric returns are used to construct the decision statistic) multipolarization synthetic aperture radar change detection starting from the availability of image pairs exhibiting possible power mismatches/miscalibrations. The principle of invariance is used to characterize the class of scale-invariant decision rules which are insensitive to power mismatches and ensure the constant false alarm rate property. A maximal invariant statistic is derived together with the induced maximal invariant in the parameter space which significantly compresses the data/parameter domain. A generalized likelihood ratio test is synthesized both for the cases of two- and three-polarimetric channels. Interestingly, for the two-channel case, it is based on the comparison of the condition number of a data-dependent matrix with a suitable threshold. Some additional invariant decision rules are also proposed. The performance of the considered scale-invariant structures is compared to those from two noninvariant counterparts using both simulated and real radar data. The results highlight the robustness of the proposed method and the performance tradeoff involved. Numéro de notice : A2016-075 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2449332 En ligne : https://doi.org/10.1109/TGRS.2015.2449332 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79843
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 36 - 50[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Compressive sensing for multibaseline polarimetric SAR tomography of forested areas / Xinwu Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Compressive sensing for multibaseline polarimetric SAR tomography of forested areas Type de document : Article/Communication Auteurs : Xinwu Li, Auteur ; Lei Liang, Auteur ; Huadong Guo, Auteur ; Yue Huang, Auteur Année de publication : 2016 Article en page(s) : pp 153 - 166 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande P
[Termes IGN] compression d'image
[Termes IGN] décomposition d'image
[Termes IGN] données polarimétriques
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] image aérienne
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] réflectivité
[Termes IGN] tomographie radarRésumé : (Auteur) The structure of forests is an important indicator of ecosystem dynamics and enables the modeling and monitoring of ecological change. Synthetic aperture radar tomography (TomoSAR) provides scene reflectivity estimation of vegetation along elevation coordinates. Due to the advantages of superresolution imaging and a small number of measurements, compressive sensing (CS) inversion techniques for SAR tomography were successfully developed and applied. This paper addresses the 3-D imaging of forested areas based on the framework of CS using fully polarimetric (FP) multibaseline SAR interferometric (MB-InSAR) tomography at P-band. A new CS-based FP MB-InSAR tomography method is proposed: a sum of Kronecker product (SKP) decomposition-based CS FP MB-InSAR tomography method (FP-SKPCS TomoSAR method). The method, based on an assumption that the reflectivity signal of a single scattering mechanism (SM) is more sparse than that of a composite of SMs, recovers the reflectivity profile of different SMs by using the CS technique. This method not only allows superresolution imaging with a low number of acquisitions but also can estimate the polarimetric SM of the vertical structure of forested areas. The effectiveness of these novel techniques for polarimetric SAR tomography is demonstrated using FP P-band airborne data sets acquired by the ONERA SETHI airborne system over a test site in Paracou, French Guiana, and the results of the vertical structure of forested areas derived by the method are verified by in situ test data. Numéro de notice : A2016-076 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2451992 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2451992 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79844
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 153 - 166[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Airborne DLSLA 3-D SAR image reconstruction by combination of polar formatting and L_1 regularization / Xueming Peng in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Airborne DLSLA 3-D SAR image reconstruction by combination of polar formatting and L_1 regularization Type de document : Article/Communication Auteurs : Xueming Peng, Auteur ; Weixian Tan, Auteur ; Wen Hong, Auteur Année de publication : 2016 Article en page(s) : pp 213 - 226 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande P
[Termes IGN] bande X
[Termes IGN] capteur aérien
[Termes IGN] centre de phase
[Termes IGN] image radar moirée
[Termes IGN] polarisation
[Termes IGN] reconstruction d'imageRésumé : (Auteur) Airborne downward-looking sparse linear array 3-D synthetic aperture radar (DLSLA 3-D SAR) operates downward-looking observation and obtains the 3-D microwave scattering information of the observed scene. The cross-track physical sparse linear array is often configured to obtain uniform virtual phase centers in order to adopt the frequency-domain algorithm. However, the virtual phase centers usually have to be nonuniformly and sparsely distributed due to the array elements' installation locations restricted by the airborne platform and the airborne wing tremor effect. In this state, the frequency-domain algorithm cannot be directly used. In this paper, a DLSLA 3-D SAR image reconstruction algorithm that combines polar formatting and L1 regularization is presented. Wave propagation and along-track dimensional imaging are first finished after polar formatting and wavefront curvature phase error compensation; then, cross-track dimensional imaging is completed with the L1 regularization technique. The proposed algorithm is applicable to airborne DLSLA 3-D SAR imaging under nonuniformly and sparsely distributed virtual phase centers condition. The proposed algorithm was verified by 3-D distributed scene simulation experiment (P-band circular SAR image was selected as radar cross-section input, and X-band digital elevation model of the same area was selected as the coordinate positions of the scene) and the field experiment. Image reconstruction results and image reconstruction performances, such as normalized radar cross section, height errors, and orthographic projection image grayscale distribution, are demonstrated and analyzed with different signal-to-noise ratios, different array sparsity, and the incomplete compensated residual oscillation error 3-D distributed scene simulation experiments. Simulation and field experimental results show the good performance in focusing and the robustness of the proposed algorithm. Numéro de notice : A2016-077 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2453202 En ligne : https://doi.org/10.1109/TGRS.2015.2453202 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79846
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 213 - 226[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible A probabilistic approach for InSAR time-series postprocessing / Ling Chang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : A probabilistic approach for InSAR time-series postprocessing Type de document : Article/Communication Auteurs : Ling Chang, Auteur ; Ramon F. Hanssen, Auteur Année de publication : 2016 Article en page(s) : pp 421 - 430 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] estimation statistique
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] post-traitement
[Termes IGN] processus stochastique
[Termes IGN] série temporelleRésumé : (Auteur) Monitoring the kinematic behavior of enormous amounts of points and objects anywhere on Earth is now feasible on a weekly basis using radar interferometry from Earth-orbiting satellites. An increasing number of satellite missions are capable of delivering data that can be used to monitor geophysical processes, mining and construction activities, public infrastructure, or even individual buildings. The parameters estimated from these data are used to better understand various natural hazards, improve public safety, or enhance asset management activities. Yet, the mathematical estimation of kinematic parameters from interferometric data is an ill-posed problem as there is no unique solution, and small changes in the data may lead to significantly different parameter estimates. This problem results in multiple possible outcomes given the same data, hampering public acceptance, particularly in critical conditions. Here, we propose a method to address this problem in a probabilistic way, which is based on multiple hypotheses testing. We demonstrate that it is possible to systematically evaluate competing kinematic models in order to find an optimal model and to assign likelihoods to the results. Using the B-method of testing, a numerically efficient implementation is achieved, which is able to evaluate hundreds of competing models per point. Our approach will not solve the nonuniqueness problem of interferometric synthetic aperture radar (InSAR), but it will allow users to critically evaluate (conflicting) results, avoid overinterpretation, and thereby consolidate InSAR as a geodetic technique. Numéro de notice : A2016-078 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2459037 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2459037 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79858
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 421 - 430[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Geodetic SAR tomography / Xiao Xiang Zhu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)
[article]
Titre : Geodetic SAR tomography Type de document : Article/Communication Auteurs : Xiao Xiang Zhu, Auteur ; Sina Montazeri, Auteur ; Christoph Gisinger, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 18 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] positionnement absolu
[Termes IGN] semis de points
[Termes IGN] tomographie radarRésumé : (auteur) In this paper, we propose a framework referred to as “geodetic synthetic aperture radar (SAR) tomography” that fuses the SAR imaging geodesy and tomographic SAR inversion (TomoSAR) approaches to obtain absolute 3-D positions of a large amount of natural scatterers. The methodology is applied on four very high resolution TerraSAR-X spotlight image stacks acquired over the city of Berlin. Since all the TomoSAR estimates are relative to the same reference point object whose absolute 3-D positions are retrieved by means of stereo SAR, the point clouds reconstructed using data acquired from different viewing angles can be geodetically fused. To assess the accuracy of the position estimates, the resulting absolute shadow-free 3-D TomoSAR point clouds are compared with a digital surface model obtained by airborne LiDAR. It is demonstrated that an absolute positioning accuracy of around 20 cm and a meter-order relative positioning accuracy can be achieved by the proposed framework using TerraSAR-X data. Numéro de notice : A2016-112 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2448686 En ligne : https://doi.org/10.1109/TGRS.2015.2448686 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79987
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 1 (January 2016) . - pp 18 - 35[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2016011 SL Revue Centre de documentation Revues en salle Disponible Documents numériques
en open access
A2016-112 - Geodetic SAR tomographyHTML text data (RFC 1866)