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Termes IGN > sciences naturelles > physique > optique > optique physique > radiométrie > rayonnement électromagnétique > spectre électromagnétique > bande spectrale > bande L
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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)
[article]
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 végétationRésumé : (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
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7272 - 7281[article]Separating the influence of vegetation changes in polarimetric differential SAR interferometry / Virginia Brancato in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Separating the influence of vegetation changes in polarimetric differential SAR interferometry Type de document : Article/Communication Auteurs : Virginia Brancato, Auteur ; Irena Hajnsek, Auteur Année de publication : 2018 Article en page(s) : pp 6871 - 6883 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] biomasse
[Termes IGN] carte de la végétation
[Termes IGN] détection de changement
[Termes IGN] données polarimétriques
[Termes IGN] humidité du sol
[Termes IGN] image AIRSAR
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] polarimétrie radar
[Termes IGN] surface cultivée
[Termes IGN] télédétection en hyperfréquenceRésumé : (auteur) Soil moisture and wet biomass changes between two noninstantaneous SAR observations markedly affect the displacement estimates obtainable with Differential Interferometric Synthetic Aperture Radar (DInSAR). The separation, the modeling of these influences besides their uncoupling from the displacement signal, and the atmospheric disturbances are still unsolved issues for several repeat-pass interferometric applications. This paper focuses on the separation of vegetation changes from the other phase contributions affecting repeat-pass measurements over vegetated areas. These phase terms mainly relate to changes in soil moisture, atmospheric delays, and surface deformation. The separation is achieved with a first-order scattering solution decomposing the observed HH and VV DInSAR phases in the sum of several phase terms. The latter mainly consider the changes in soil surface scattering and in the two-way propagation through a vertically oriented vegetation canopy. No assumption is made on the spatiotemporal evolution of the displacement and atmosphere. The overall approach is tested on a L-band data set acquired over an agricultural area. Upon calibration, the model allows for estimating changes in wet biomass based on the nonzero HH–VV DInSAR phase difference observed over several birefringent agricultural fields. The obtained biomass estimates provide then a correction for the effect of vegetation changes on the observed HH and VV DInSAR phases. Deprived of the vegetation contribution, the remainder phase terms can be more easily explored for further analyses, e.g., the estimation of soil moisture changes and/or surface movements in vertically oriented vegetated areas. Numéro de notice : A2018-551 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2845368 Date de publication en ligne : 14/08/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2845368 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91639
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 6871 - 6883[article]The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)
[article]
Titre : The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas Type de document : Article/Communication Auteurs : Emanuele Santi, Auteur ; Simonetta Paloscia, Auteur ; Simone Pettinato, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 63 - 73 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] biomasse forestière
[Termes IGN] capacité de stockage
[Termes IGN] classification par réseau neuronal
[Termes IGN] forêt méditerranéenne
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Envisat-ASAR
[Termes IGN] image radar moirée
[Termes IGN] modèle de transfert radiatif
[Termes IGN] production primaire brute
[Termes IGN] Toscane (Italie)Résumé : (auteur) The extraction of forest information from SAR images is particularly complex in Mediterranean areas, since they are characterized by high spatial fragmentation and heterogeneity. We have investigated the use of multi-frequency SAR data from different sensors (ALOS/PALSAR and ENVISAT/ASAR) for estimating forest biomass in two test areas in Central Italy (San Rossore and Molise), where detailed in-situ measurements and Airborne Laser Scanning (ALS) data were available. The study focused on the estimation of growing stock volume (GS, in m3/ha) by using an inversion algorithm based on artificial neural networks (ANN). The ANN algorithm was first appropriately trained using the available GS estimates obtained from ALS data. The potential of this algorithm was then improved through the innovative use of a simulated dataset, generated by a forward electromagnetic model based on the Radiative Transfer Theory (RTT). The algorithm is able to merge SAR data at L and C bands for predicting GS in diversified Mediterranean environments. The performed analyses indicated that GS was correctly estimated by integrating information from L and C bands on both test areas, with the following statistics: R > 0.97 and RMSE = 28.5 m3/ha for the independent test, and R = 0.86 and RMSE ≈ 77 m3/ha for the final independent validation, the latter performed on the forest stands of both areas not included in the ALS acquisitions and where conventional measurements were available. The research then illustrates the potential of using the obtained GS estimates from SAR data to drive the simulations of forest net primary production (NPP). This experiment produced spatially explicit estimates of GS current annual increments that are slightly less accurate than those obtained from ground observations (R = 0.75 and RMSE ≈ 1.5 m3/ha/year). Numéro de notice : A2017-415 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.07.038 En ligne : https://doi.org/10.1016/j.rse.2017.07.038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86307
in Remote sensing of environment > vol 200 (October 2017) . - pp 63 - 73[article]Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active–Passive Satellite and evaluation at core validation sites / Seung-Bum Kim in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)
[article]
Titre : Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active–Passive Satellite and evaluation at core validation sites Type de document : Article/Communication Auteurs : Seung-Bum Kim, Auteur ; Joel T. Johnson, Auteur ; Mahta Moghaddam, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1897 - 1914 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] croissance végétale
[Termes IGN] données hétérogènes
[Termes IGN] humidité du sol
[Termes IGN] image radar moirée
[Termes IGN] mission SMAP
[Termes IGN] pente
[Termes IGN] polarisation
[Termes IGN] problème inverse
[Termes IGN] série temporelleRésumé : (Auteur) This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active-Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture retrievals using radar observations have been challenging in the past due to complicating factors of surface roughness and vegetation scattering. Here, physically based forward models of radar scattering for individual vegetation types are inverted using a time-series approach to retrieve soil moisture while correcting for the effects of static roughness and dynamic vegetation. Compared with the past studies in homogeneous field scales, this paper performs a stringent test with the satellite data in the presence of terrain slope, subpixel heterogeneity, and vegetation growth. The retrieval process also addresses any deficiencies in the forward model by removing any time-averaged bias between model and observations and by adjusting the strength of vegetation contributions. The retrievals are assessed at 14 core validation sites representing a wide range of global soil and vegetation conditions over grass, pasture, shrub, woody savanna, corn, wheat, and soybean fields. The predictions of the forward models used agree with SMAP measurements to within 0.5 dB unbiased-root-mean-square error (ubRMSE) and -0.05 dB (bias) for both copolarizations. Soil moisture retrievals have an accuracy of 0.052 m3/m3 ubRMSE, -0.015 m3/m3 bias, and a correlation of 0.50, compared to in situ measurements, thus meeting the accuracy target of 0.06 m3/m3 ubRMSE. The successful retrieval demonstrates the feasibility of a physically based time series retrieval with L-band SAR data for characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetation. Numéro de notice : A2017-169 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2631126 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2631126 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84713
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 4 (April 2017) . - pp 1897 - 1914[article]Active interseismic shallow deformation of the Pingting terraces (Longitudinal Valley – Eastern Taiwan) from UAV high-resolution topographic data combined with InSAR time series / Benoit Deffontaines in Geomatics, Natural Hazards and Risk, vol 8 (2017)
[article]
Titre : Active interseismic shallow deformation of the Pingting terraces (Longitudinal Valley – Eastern Taiwan) from UAV high-resolution topographic data combined with InSAR time series Type de document : Article/Communication Auteurs : Benoit Deffontaines , Auteur ; Kuo-Jen Chang, Auteur ; Johann Champenois, Auteur ; Bénédicte Fruneau , Auteur ; Erwan Pathier, Auteur ; Jyr-Ching Hu, Auteur ; Shih-Ting Lu, Auteur ; Yen-Chiu Liu, Auteur Année de publication : 2017 Projets : 1-Pas de projet / Article en page(s) : pp 120 - 136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande L
[Termes IGN] champ de vitesse
[Termes IGN] déformation de la croute terrestre
[Termes IGN] drone
[Termes IGN] faille géologique
[Termes IGN] image aérienne
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] modèle numérique de terrain
[Termes IGN] TaïwanRésumé : (auteur) We focus herein on the location, characterization and the quantification of the most active structural feature of Taiwan: the Longitudinal Valley Fault that corresponds to the suture in between the Philippine and Eurasian Plates. In order to determine and monitor its present inter-seismic deformation, we focus on the Pingting Terraces area, situated in the South Longitudinal Valley (Eastern Taiwan). We first determine the structural geometry issued from both photo-interpretation deduced from new unmanned aerial vehicle (UAV) high-resolution Digital Terrain Model data that we acquired (34.78 km2 with 7.73 cm ground sampling distance), combined with geological field work. In order to characterize and quantify the present deformational patterns over the Pingting terraces, we used an InSAR time series Interferometry algorithm (MT-InSAR) applied to nine L-band SAR images from ALOS satellite acquired over the period 2007–2010. The unprecedented density of measurements (about 120 points per km2 for a total of 6,400 points) gives a continuous overview of the inter-seismic shallow deformation. The structural geometry combined with the mean velocity map (MT-InSAR) reveals two clear active faults situated above the scarps of the Pingting terraces and responsible for up to 7 and 20 mm/yr velocity offset along the radar line of sight. A temporal analysis of the deformation is performed with one measurement at each SAR acquisition date, giving major improvements in the characterization and quantification of the Longitudinal Valley active Fault trace. Numéro de notice : A2017-840 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2016.1181678 Date de publication en ligne : 25/07/2016 En ligne : https://doi.org/10.1080/19475705.2016.1181678 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89350
in Geomatics, Natural Hazards and Risk > vol 8 (2017) . - pp 120 - 136[article]Detection of ground surface deformation caused by the 2016 Kumamoto earthquake by InSAR using ALOS-2 data / Basara Miyahara in Bulletin of the GeoSpatial Information authority of Japan, vol 64 (December 2016)PermalinkImaging the internal structure of an alpine glacier via L-band airborne SAR tomography / Stefano Tebaldini in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkSMAP L-Band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations / Priscilla N. Mohammed in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)PermalinkInvestigation of ionospheric effects on SAR Interferometry (InSAR): A case study of Hong Kong / Wu Zhu in Advances in space research, vol 58 n° 4 (August 2016)PermalinkSoil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data / Lian He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkGlobal sensitivity analysis of the L-MEB model for retrieving soil moisture / Zengyan Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 5 (May 2016)PermalinkGLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring / Erwan Motte in Sensors, vol 16 n° 5 (May 2016)PermalinkToward operational compensation of ionospheric effects in SAR interferograms: the split-spectrum method / Giorgio Gomba in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)PermalinkApport de la télédétection radar satellitaire pour la cartographie de la forêt des Landes / Yousra Hamrouni (2016)PermalinkRadar based classification prior to biomass retrieval from P-Band SAR data / Pierre-Louis Frison (2016)Permalink