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A soil texture categorization mapping from empirical and semi-empirical modelling of target parameters of synthetic aperture radar / Shoba Periasamy in Geocarto international, vol 36 n° 5 ([15/03/2021])  

Public [article]  inGeocarto international > vol 36 n° 5 [15/03/2021] . - pp 581 - 598 Titre : A soil texture categorization mapping from empirical and semi-empirical modelling of target parameters of synthetic aperture radar Type de document : Article/Communication Auteurs : Shoba Periasamy, Auteur ; Divya Senthil, Auteur ; Ramakrishnan S Shanmugam, Auteur Année de publication : 2021 Article en page(s) : pp 581 - 598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Argile [Termes IGN] bande C [Termes IGN] coefficient de rétrodiffusion [Termes IGN] constante diélectrique [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] indice de végétation [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] limon [Termes IGN] polarisation croisée [Termes IGN] rugosité du sol [Termes IGN] sable [Termes IGN] texture du sol Résumé : (auteur) The present study investigates the potential of synthetic aperture radar in demonstrating the relative percentage of sand, silt and clay content in the soil. The contribution of vegetation and topography in the backscattering coefficient has been significantly reduced by employing the terrain correction model, dual polarized SAR vegetation index and water cloud model. The target parameters namely ‘Soil Roughness (hrms-soil)’ and ‘Dielectric Constant’ (ε′vv−soil ) has arrived from cross-polarization ratio and modified Dubois model. The extracted target parameters are sufficiently correlated with in situ sand (R2 = 0.81) and clay measurements (R2 = 0.78). The relative percentage of silt was mapped by the novel idea of performing the correlation analysis between hrms-soil and ε′vv−soil and thus represented the percentage of silt with reasonable accuracy (R2 = 0.77). From the soil triangle formed with three estimated target parameters, we found that the clay category has shared around 35% of the total area followed by sandy loam (23%). Numéro de notice : A2021-253 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1618924 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1618924 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97276 [article]

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Advances and applications in deep learning / Marco Antonio Aceves-Fernandez (2020)  

Public Titre : Advances and applications in deep learning Type de document : Monographie Auteurs : Marco Antonio Aceves-Fernandez, Editeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 122 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-1-83962-879-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] apprentissage automatique [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] constante diélectrique [Termes IGN] méthode fondée sur le noyau [Termes IGN] programmation stochastique [Termes IGN] temps réel [Termes IGN] vision par ordinateur Résumé : (auteur) Artificial Intelligence (AI) has attracted the attention of researchers and users alike and is taking an increasingly crucial role in our modern society. From cars, smartphones, and airplanes to medical equipment, consumer applications, and industrial machines, the impact of AI is notoriously changing the world we live in. In this context, Deep Learning (DL) is one of the techniques that has taken the lead for cognitive processes, pattern recognition, object detection, and machine learning, all of which have played a crucial role in the growth of AI. As such, this book examines DL applications and future trends in the field. It is a useful resource for researchers and students alike. Note de contenu : 1- Advancements in deep learning theory and applications: Perspective in 2020 and beyond 2- Advances in convolutional neural networks 3- Transfer learning and deep domain adaptation 4- Deep learning enabled nanophotonics 5- Explainable artificial intelligence (xAI) approaches and deep meta-learning models 6- Dynamic decision-making for stabilized deep learning software platforms Numéro de notice : 28565 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.87786 En ligne : https://doi.org/10.5772/intechopen.87786 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97647

Soil and vegetation scattering contributions in L-Band and P-Band polarimetric SAR observations / S. Hamed Alemohammad in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 11 (November 2019) . - pp 8417 - 8429 Titre : Soil and vegetation scattering contributions in L-Band and P-Band polarimetric SAR observations Type de document : Article/Communication Auteurs : S. Hamed Alemohammad, Auteur ; Thomas Jagdhuber, Auteur ; Mahta Moghaddam, Auteur ; Dara Entekhabi, Auteur Année de publication : 2019 Article en page(s) : pp 8417 - 8429 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] bande P [Termes IGN] canopée [Termes IGN] constante diélectrique [Termes IGN] couvert végétal [Termes IGN] données polarimétriques [Termes IGN] humidité du sol [Termes IGN] image captée par drone [Termes IGN] image radar moirée [Termes IGN] micro-onde [Termes IGN] rugosité du sol [Termes IGN] teneur en eau de la végétation Résumé : (auteur) Active microwave-based retrieval of soil moisture in vegetated areas has uncertainties due to the sensitivity of the signal to both soil (dielectric constant and roughness) and vegetation (dielectric constant and structure) properties. A multi-frequency acquisition system would increase the number of observations that may constrain soil and/or vegetation parameter retrievals. In order to realize this constraint, an understanding of microwaves interaction with the surface and vegetation across frequencies is necessary. Different microwave frequencies have varied interactions with the soil-vegetation medium and increasing penetration into the soil and canopy with the decreasing frequency. In this study, we examine the contributions of different scattering mechanisms to coincident observations from two microwave frequencies (L and P) of airborne synthetic aperture radar instruments. We quantify contributions of surface, vegetation volume, and double-bounce scattering components. Results are analyzed and discussed to guide future multi-frequency retrieval algorithm designs. Numéro de notice : A2019-594 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2920995 date de publication en ligne : 27/06/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2920995 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94586 [article]

Polarization orientation angle and polarimetric SAR scattering characteristics of steep terrain / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7272 - 7281 Titre : Polarization orientation angle and polarimetric SAR scattering characteristics of steep terrain Type de document : Article/Communication Auteurs : Jong-Sen Lee, Auteur ; Thomas L. Ainsworth, Auteur ; Yanting Wang, Auteur Année de publication : 2018 Article en page(s) : pp 7272 - 7281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] angle de visée [Termes IGN] bande C [Termes IGN] bande L [Termes IGN] constante diélectrique [Termes IGN] données polarimétriques [Termes IGN] escarpement [Termes IGN] humidité du sol [Termes IGN] image radar moirée [Termes IGN] image TOPSAR [Termes IGN] modèle de diffusion du rayonnement [Termes IGN] montagne [Termes IGN] pente [Termes IGN] polarimétrie radar [Termes IGN] polarisation croisée [Termes IGN] réflectance spectrale [Termes IGN] rétrodiffusion de Bragg [Termes IGN] teneur en eau de la végétation Résumé : (auteur) Polarization orientation angle (POA) is an important parameter of polarimetric radar scattering from slopes in mountainous region. It is known that surface tilted in azimuth direction and buildings not aligned in the along-track direction induce polarization orientation shifts. Earlier research has established orientation angle as a function of radar imaging geometry and surface slopes, and that POA estimation can be derived from polarimetric radar data using circular polarization. Besides these, polarimetric scattering from steep slopes and its relation to POA remain not well understood. In this paper, we address these issues by adopting a tilted surface model based on Bragg scattering. We have found that, as the azimuthal slope increases, |VV| decreases at a faster rate than |HH|, they become equal, when POA is ±45°, and |HH| > |VV| afterward. In other words, the Pauli component, |HH-VV| reduced to zero at POA = ± 45°, and the typical Bragg scattering characteristics of |VV| > |HH| does not apply when steep slope is present inducing |POA| > 45°. Furthermore, the cross-pol |HV| does not always increase with azimuth slope but also reaches a maximum then decreases to zero. In addition, we investigate the effect of soil moisture on polarimetric SAR (PolSAR) scattering characteristics of steep terrain and the effect of vegetation over surface on POA estimation. The latter is demonstrated with NASA/JPL TOPSAR L-band PolSAR data and C-band InSAR data. Another significance of this paper is that it provides a direct and rigorous derivation of POA equations. The earlier version was derived from a different concept. Numéro de notice : A2018-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2849931 date de publication en ligne : 01/08/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2849931 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91662 [article]

Measure of temporal variation of P-Band radar cross section and temporal coherence of a temperate tree / Clément Albinet in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 11 (November 2016) . - pp 6255 - 6264 Titre : Measure of temporal variation of P-Band radar cross section and temporal coherence of a temperate tree Type de document : Article/Communication Auteurs : Clément Albinet, Auteur ; Pierre Borderies, Auteur ; Nicolas Floury, Auteur ; Eric Pottier, Auteur Année de publication : 2016 Article en page(s) : pp 6255 - 6264 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande P [Termes IGN] Cedrus (genre) [Termes IGN] constante diélectrique [Termes IGN] diffusomètre [Termes IGN] polarimétrie radar [Termes IGN] surface équivalente radar Résumé : (Auteur) This paper deals with a ground experiment based on a P-band scatterometer that measured the evolution of the radar cross section (RCS) and coherence of a temperate tree in HV polarization, during four periods spread over nine months, over a cedar tree. Watering of the tree has limited influence in time on the RCS, i.e., limited to around 30 min, but impacts the coherence over a longer period of time. Analysis of the series shows that according to the season considered, clear daily cycles from 1 to 2 dB may appear on the coherence only (autumn) or on both coherence and RCS (spring), whereas in winter, they are absent on both results. It was analyzed in the literature that the variations in RCS are strongly correlated to the variations in the dielectric constant in trunks and branches. In addition, it was shown that the HV RCS presents seasonal trends with a yearly cycle of roughly 3 dB following similar trends reported for trunk moisture content time series. Numéro de notice : A2016-910 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2016.2565384 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83132 [article]

Multitemporal fluctuations in L-Band Backscatter from a japanese forest / Manabu Watanabe in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)  

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Image-domain estimation of wall parameters for autofocusing of through-the-wall SAR imagery / Tian Jin in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 2 (March 2013)  

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Physical limitations on detecting tunnels using underground-focusing spotlight synthetic aperture radar / J. Martinez-Lorenzo in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 1 (January 2011)  

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Snow permitivity retrieval inversion algorithm for estimating snow wetness / G. Singh in Geocarto international, vol 25 n° 3 (June 2010)  

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Utilizing calibrated GPS reflected signals to estimate soil reflectivity and dielectric constant: results from SMEX02 / S.J. Katzberg in Remote sensing of environment, vol 100 n° 1 (15/01/2006)

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Backscatter and dielectric measurements from rocks of south-eastern Utah at C-band, X-band and KU-band / R. Swanson in International Journal of Remote Sensing IJRS, vol 9 n° 4 (April 1988)

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Electrostatique, courants continus, magnétisme / Pierre Fleury (1967)

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