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Visual analytics of time-varying multivariate ionospheric scintillation data / Aurea Soriano-Vargas in Computers and graphics, vol 68 (November 2017)
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Titre : Visual analytics of time-varying multivariate ionospheric scintillation data Type de document : Article/Communication Auteurs : Aurea Soriano-Vargas, Auteur ; Bruno C. Vani, Auteur ; Milton H. Shimabukuro, Auteur ; João F.G. Monico, Auteur Année de publication : 2017 Article en page(s) : pp 96 - 107 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] analyse multivariée
[Termes IGN] données spatiotemporelles
[Termes IGN] ionosphère
[Termes IGN] scintillation
[Termes IGN] visualisation de données
[Vedettes matières IGN] GéovisualisationRésumé : (résumé) We present a clustering-based interactive approach to multivariate data analysis, motivated by the specific needs of scintillation data. Ionospheric scintillation is a rapid variation in the amplitude and/or phase of radio signals traveling through the ionosphere. This spatial and time-varying phenomenon is of great interest since it affects the reception quality of satellite signals. Specialized receivers at strategic regions can track multiple variables related to this phenomenon, generating a database of observations of regional ionospheric scintillation. We introduce a visual analytics solution to support analysis of such data, keeping in mind the general applicability of our approach to similar multivariate data analysis situations.
Taking into account typical user questions, we combine visualization and data mining algorithms that satisfy these goals: (i) derive a representation of the variables monitored that conveys their behavior in detail, at multiple user-defined aggregation levels; (ii) provide overviews of multiple variables regarding their behavioral similarity over selected time periods; (iii) support users when identifying representative variables for characterizing scintillation behavior. We illustrate the capabilities of our proposed framework by presenting case studies driven directly by questions formulated by collaborating domain experts.Numéro de notice : A2017-452 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cag.2017.08.013 En ligne : https://doi.org/10.1016/j.cag.2017.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86363
in Computers and graphics > vol 68 (November 2017) . - pp 96 - 107[article]Modeling canopy reflectance over sloping terrain based on path length correction / Gaofei Yin in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)
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Titre : Modeling canopy reflectance over sloping terrain based on path length correction Type de document : Article/Communication Auteurs : Gaofei Yin, Auteur ; Ainong Li, Auteur ; Wei Zhao, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 4597 - 4609 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] distorsion du signal
[Termes IGN] figuré du terrain
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] montagne
[Termes IGN] pente
[Termes IGN] réflectance végétaleRésumé : (Auteur) Sloping terrain induces distortion of canopy reflectance (CR), and the retrieval of biophysical variables from remote sensing data needs to account for topographic effects. We developed a 1-D model (the path length correction (PLC) based model) for simulating CR over sloping terrain. The effects of sloping terrain on single-order and diffuse scatterings are accounted for by PLC and modification of the fraction of incoming diffuse irradiance, respectively. The PLC model was validated via both Monte Carlo and remote sensing image simulations. The comparison with the Monte Carlo simulation revealed that the PLC model can capture the pattern of slope-induced reflectance distortion with high accuracy (red band: R2 = 0.88; root-mean-square error (RMSE) = 0.0045; relative RMSE (RRMSE) = 15%; near infrared response (NIR) band: R2 = 0.79; RMSE = 0.041; RRMSE = 16%). The comparison of the PLC-simulated results with remote sensing observations acquired by the Landsat8-OLI sensor revealed an accuracy similar to that with the Monte Carlo simulation (red band: R2 = 0.83; RMSE = 0.0053; RRMSE = 13%; NIR band: R2 = 0.77; RMSE = 0.023; RRMSE = 8%). To further validate the PLC model, we used it to implement topographic normalization; the results showed a large reduction in topographic effects after normalization, which implied that the PLC model captures reflectance variations caused by terrain. The PLC model provides a promising tool to improve the simulation of CR and the retrieval of biophysical variables over mountainous regions. Numéro de notice : A2017-500 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2694483 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2694483 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86442
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4597 - 4609[article]Parallax-tolerant aerial image georegistration and efficient camera pose refinement—without piecewise homographies / Hadi AliAkbarpour in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)
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Titre : Parallax-tolerant aerial image georegistration and efficient camera pose refinement—without piecewise homographies Type de document : Article/Communication Auteurs : Hadi AliAkbarpour, Auteur ; Kannappan Palaniappan, Auteur ; Guna Seetharaman, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 4618 - 4637 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] bruit (théorie du signal)
[Termes IGN] caméra numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] décomposition d'image
[Termes IGN] géoréférencement
[Termes IGN] image aérienne
[Termes IGN] métadonnées
[Termes IGN] orthorectification
[Termes IGN] reconstruction 3D
[Termes IGN] structure-from-motionRésumé : (Auteur) We describe a fast and efficient camera pose refinement and Structure from Motion (SfM) method for sequential aerial imagery with applications to georegistration and 3-D reconstruction. Inputs to the system are 2-D images combined with initial noisy camera metadata measurements, available from on-board sensors (e.g., camera, global positioning system, and inertial measurement unit). Georegistration is required to stabilize the ground-plane motion to separate camera-induced motion from object motion to support vehicle tracking in aerial imagery. In the proposed approach, we recover accurate camera pose and (sparse) 3-D structure using bundle adjustment for sequential imagery (BA4S) and then stabilize the video from the moving platform by analytically solving for the image-plane-to-ground-plane homography transformation. Using this approach, we avoid relying upon image-to-image registration, which requires estimating feature correspondences (i.e., matching) followed by warping between images (in a 2-D space) that is an error prone process for complex scenes with parallax, appearance, and illumination changes. Both our SfM (BA4S) and our analytical ground-plane georegistration method avoid the use of iterative consensus combinatorial methods like RANdom SAmple Consensus which is a core part of many published approaches. BA4S is very efficient for long sequential imagery and is more than 130 times faster than VisualSfM, 35 times faster than MavMap, and about 274 times faster than Pix4D. Various experimental results demonstrate the efficiency and robustness of the proposed pipeline for the refinement of camera parameters in sequential aerial imagery and georegistration. Numéro de notice : A2017-501 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2695172 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2695172 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86444
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4618 - 4637[article]Enhanced resolution stripmap mode using dynamic metasurface antennas / Andreas Pedross-Engel in IEEE Transactions on geoscience and remote sensing, vol 55 n° 7 (July 2017)
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Titre : Enhanced resolution stripmap mode using dynamic metasurface antennas Type de document : Article/Communication Auteurs : Andreas Pedross-Engel, Auteur ; Claire M. Watts, Auteur ; David R. Smith, Auteur ; Matthew S. Reynolds, Auteur Année de publication : 2017 Article en page(s) : pp 3764 - 3772 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] faisceau
[Termes IGN] radar à antenne synthétique
[Termes IGN] rapport signal sur bruit
[Termes IGN] traitement du signalRésumé : (Auteur) To maintain sufficient signal-to-noise ratio (SNR) for image reconstruction and image interpretation, conventional synthetic aperture radar (SAR) systems must trade off resolution and scene size. This paper proposes a new SAR mode of operation, which improves resolution while maintaining good SNR and a large scene size. It leverages the unique properties of dynamic metasurface antennas (MSAs) to subsample a large virtual beamwidth utilizing multiple small distinct antenna beams. Due to this parallelization in scene sampling, the constraints on the azimuth sampling rate can be relaxed while maintaining an aliasing-free cross range. Due to the versatile properties of MSAs and their cost effective manufacturing process, this paper proposes SAR systems, which can obtain high resolution images over a wide scene size with lower cost and complexity than competing approaches. Point-spread functions and proof-of-concept SAR simulations are shown to verify this approach. In addition, laboratory experiments using a commercial prototype MSA are presented, which show an improvement of 62% in cross-range resolution of the proposed approach, compared with the cross-range resolution of stripmap mode SAR with the same aperture. Numéro de notice : A2017-486 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2679438 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2679438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86413
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 7 (July 2017) . - pp 3764 - 3772[article]Gold – A novel deconvolution algorithm with optimization for waveform LiDAR processing / Tan Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)
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Titre : Gold – A novel deconvolution algorithm with optimization for waveform LiDAR processing Type de document : Article/Communication Auteurs : Tan Zhou, Auteur ; Sorin C. Popescu, Auteur ; Keith Krause, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 131 - 150 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] déconvolution
[Termes IGN] forme d'onde
[Termes IGN] optimisation (mathématiques)
[Termes IGN] traitement du signalRésumé : (Auteur) Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: (1) direct decomposition, (2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms – the Richardson-Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from the corresponding reference data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference ( Numéro de notice : A2017-349 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.04.021 En ligne : https://dx.doi.org/10.1016/j.isprsjprs.2017.04.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85622
in ISPRS Journal of photogrammetry and remote sensing > vol 129 (July 2017) . - pp 131 - 150[article]Réservation
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