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Estimation of 3-D surface displacement based on InSAR and deformation modeling / Jun Hu in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)
[article]
Titre : Estimation of 3-D surface displacement based on InSAR and deformation modeling Type de document : Article/Communication Auteurs : Jun Hu, Auteur ; Xiao-Li Ding, Auteur ; Lei Zhang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 2007 - 2016 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] déformation de surface
[Termes IGN] dynamique des fluides
[Termes IGN] élasticité
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] modélisation 3D
[Termes IGN] test de performanceRésumé : (Auteur) A new approach is presented for mapping 3-D surface displacement caused by subsurface fluid volumetric change based on 1-D interferometric synthetic aperture radar (InSAR) line-of-sight measurements and surface deformation modeling. The relationship between surface deformation and source fluid volumetric change is modeled according to elastic half-space theory. A distinctive advantage of the proposed approach is that it effectively extends the capability of the sun-synchronous orbit side-looking synthetic aperture radar that has been essentially only able to measure 1-D displacements accurately or at most 2-D displacements when InSAR measurements from more than one orbit or platform are combined. Experimental studies are carried out with both simulated and real data sets to test the performance of the method. The results have demonstrated that the approach works very well. Numéro de notice : A2017-171 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2634087 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2634087 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84715
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 4 (April 2017) . - pp 2007 - 2016[article]Forest classification and impact of BIOMASS resolution on forest area and aboveground biomass estimation / Michael Schlund in International journal of applied Earth observation and geoinformation, vol 56 (April 2017)
[article]
Titre : Forest classification and impact of BIOMASS resolution on forest area and aboveground biomass estimation Type de document : Article/Communication Auteurs : Michael Schlund, Auteur ; Klaus Scipal, Auteur ; Malcolm W.J. Davidson, Auteur Année de publication : 2017 Article en page(s) : pp 65 - 76 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande P
[Termes IGN] base de données d'occupation du sol
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] erreur systématique
[Termes IGN] estimation statistique
[Termes IGN] image radar moiréeRésumé : (auteur) The European Space Agency (ESA) is currently implementing the BIOMASS mission as 7th Earth Explorer satellite. BIOMASS will provide for the first time global forest aboveground biomass estimates based on P-band synthetic aperture radar (SAR) imagery. This paper addresses an often overlooked element of the data processing chain required to ensure reliable and accurate forest biomass estimates: accurate identification of forest areas ahead of the inversion of radar data into forest biomass estimates. The use of the P-band data from BIOMASS itself for the classification into forest and non-forest land cover types is assessed in this paper. For airborne data in tropical, hemi-boreal and boreal forests we demonstrate that classification accuracies from 90 up to 97% can be achieved using radar backscatter and phase information. However, spaceborne data will have a lower resolution and higher noise level compared to airborne data and a higher probability of mixed pixels containing multiple land cover types. Therefore, airborne data was reduced to 50 m, 100 m and 200 m resolution. The analysis revealed that about 50–60% of the area within the resolution level must be covered by forest to classify a pixel with higher probability as forest compared to non-forest. This results in forest omission and commission leading to similar forest area estimation over all resolutions. However, the forest omission resulted in a biased underestimated biomass, which was not equaled by the forest commission. The results underline the necessity of a highly accurate pre-classification of SAR data for an accurate unbiased aboveground biomass estimation. Numéro de notice : A2017-370 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2016.12.001 En ligne : https://doi.org/10.1016/j.jag.2016.12.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85789
in International journal of applied Earth observation and geoinformation > vol 56 (April 2017) . - pp 65 - 76[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]Trace coherence : a new operator for polarimetric and interferometric SAR images / Armando Marino in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)
[article]
Titre : Trace coherence : a new operator for polarimetric and interferometric SAR images Type de document : Article/Communication Auteurs : Armando Marino, Auteur Année de publication : 2017 Article en page(s) : pp 2326 - 2339 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification
[Termes IGN] cohérence des données
[Termes IGN] détection de changement
[Termes IGN] image radar moirée
[Termes IGN] Pol-INSAR
[Termes IGN] polarimétrie radarRésumé : (Auteur) Quadratic forms play an important role in the development of several polarimetric and interferometric synthetic aperture radar (Pol-InSAR) methodologies, which are very powerful tools for earth observation. This paper investigates integrals of Pol-InSAR operators based on quadratic forms, with special interest on the Pol-InSAR coherence. A new operator, namely Trace Coherence, is introduced, which provides an approximation for the center of mass of the coherence region (CoRe). The latter is the locus of points on the polar plot containing all the possible coherence values. Such center of mass can be calculated as the integral of Pol-InSAR coherences over the scattering mechanisms (SMs). The trace coherence provides synthetic information regarding the partial target as one single entity. Therefore, it provides a representation, which is not dependent on the selection of one specific polarization channel. It may find application in change detection (e.g., coherent change detection and differential DEM), classification (e.g., building structure parameters), and modeling (e.g., for the retrieval of forest height). In calculating the integral of the Pol-InSAR coherences, an approximate trace coherence expression is derived and shown to improve the calculation speed by several orders of magnitude. The trace coherence approximation is investigated using Monte Carlo simulations and validated ESA (DLR) L-band quad-polarimetric data acquired during the AGRISAR 2006 campaign. The result of the analysis using simulated and real data is that the average error in approximating the integral of the coherence region is 0.025 in magnitude and 3° in phase (in scenarios with sufficiently high coherence). Numéro de notice : A2017-175 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2641742 En ligne : https://doi.org/10.1109/TGRS.2016.2641742 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84747
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 4 (April 2017) . - pp 2326 - 2339[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]Geometric accuracy evaluation of YG-18 satellite imagery based on RFM / Ruishan Zhao in Photogrammetric record, vol 32 n° 157 (March - May 2017)PermalinkHyperspectral SAR / Matthew Ferrara in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkImage-based target detection and radial velocity estimation methods for multichannel SAR-GMTI / Kei Suwa in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkNew point matching algorithm using sparse representation of image patch feature for SAR image registration / Jianwei Fan in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkSatellite-based probabilistic assessment of soil moisture using C-band quad-polarized RISAT1 data / Manali Pal in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkA network-based enhanced spectral diversity approach for TOPS time-series analysis / Heresh Fattahi in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)PermalinkPulse compression waveform and filter optimization for spaceborne cloud and precipitation radar / Robert M. Beauchamp in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)PermalinkPermalinkFusing meter-resolution 4-D InSAR point clouds and optical images for semantic urban infrastructure monitoring / Yuanyuan Wang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)PermalinkPermalink