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Multi-sensor prediction of Eucalyptus stand volume: A support vector approach / Guilherme Silverio Aquino de Souza in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 135 - 146 Titre : Multi-sensor prediction of Eucalyptus stand volume: A support vector approach Type de document : Article/Communication Auteurs : Guilherme Silverio Aquino de Souza, Auteur ; Vicente Paulo Soares, Auteur ; Helio Garcia Leite, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 135 - 146 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] bande L [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] Eucalyptus (genre) [Termes descripteurs IGN] image ALOS-AVNIR2 [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] radar à antenne synthétique [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] taux d'échantillonnage Résumé : (Auteur) Stem volume is a key attribute of Eucalyptus forest plantations upon which decision-making is based at diverse levels of planning. Quantifying volume through remote sensing can support a proper management of forests. Because of limitations on spaceborne optical and synthetic aperture radar sensors, this study integrated both types of datasets assembled using support vector regression (SVR) to retrieve the stand volume of Eucalyptus plantations. We assessed different combinations of sensors and a minimum number of plots to develop an SVR model. Finally, the best SVR performance was compared with other analytical methods already tested and in the literature: multilinear regression, artificial neural networks (ANN), and random forest (RF). Here, we introduce a test for comparative analysis of the performance of different methods. We found that SVR accurately predicted stem volume of Brazilian fast-growing Eucalyptus forest plantations. Gaussian radial basis was the most suitable kernel function. Integrating the optical and L-band backscatter data increased the predictive accuracy compared to a single sensor model. Combining NIR-band data from ALOS AVNIR-2 and backscatter of L-band horizontal emitted and vertical received (HV) electric fields from ALOS PALSAR produced the most accurate SVR model (with an R2 of 0.926 and root mean square error of 11.007 m3/ha). The number of field plots sufficient for model development with non-redundant explanatory variables was 77. Under this condition, SVR performed similarly to ANN and outperformed the multiple linear regression and random forest methods. Numéro de notice : A2019-319 Thématique : FORET/IMAGERIE Nature : Article DOI : doi.org/10.1016/j.isprsjprs.2019.08.002 date de publication en ligne : 20/08/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.002 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93357 [article]

Polarimétrie radar complète et partielle pour le suivi des surfaces terrestres / Pierre-Louis Frison in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - décembre 2019)

Public [article]  inRevue Française de Photogrammétrie et de Télédétection > n° 219-220 (juin - décembre 2019) . - pp 33 - 39 Titre : Polarimétrie radar complète et partielle pour le suivi des surfaces terrestres Type de document : Article/Communication Auteurs : Pierre-Louis Frison , Auteur ; Cédric Lardeux, Auteur ; Bénédicte Fruneau , Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2019 Article en page(s) : pp 33 - 39 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] classification [Termes descripteurs IGN] extraction de la végétation [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] polarimétrie radar [Termes descripteurs IGN] sédimentation [Termes descripteurs IGN] Tunisie Résumé : (auteur) This article presents some illustrations of (fully or partial) polarimetric radar data applications for the monitoring of terrestrial surfaces. The first part is dedicated to fully polarimetric radar data. Firstly, a theoretical reminder presents the specificity of fully polarimetric data. Then illustrations are given for vegetation types cartography as well as spatio-temporal processes of sedimentation in a semi-arid area in Tunisia. The second part focuses on partially polarimetric data, of the type acquired by the Sentinel-1A/1B satellite SAR sensors, which will be widely used in future years due to their significant contribution to land surface observations studies for environmental sciences. Numéro de notice : A2019-346 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93383 [article]

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Generation of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar / Yang Lei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 2 (February 2019) . - pp 770 - 787 Titre : Generation of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar Type de document : Article/Communication Auteurs : Yang Lei, Auteur ; Paul Siqueira, Auteur ; Nathan Torbick, Auteur ; Mark J. Ducey, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 770 - 787 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] bande L [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] Maine (Etats-Unis) [Termes descripteurs IGN] New Hampshire (Etats-Unis) Résumé : (Auteur) This paper provides an overview of the scattering model, inversion approach, and validation of the application results for creating large-scale moderate-resolution (hectare-level) mosaics of forest height through using spaceborne repeat-pass SAR interferometry and lidar. By incorporating several improvements to the forest height inversion and mosaicking approach, the height estimation accuracy along with the robustness of this approach have been considerably enhanced from its originally reported accuracy of RMSE of 3-4 m at a 20-hectare aggregated pixel size to RMSE of 3-4 m on the order of 3-6 hectares. Furthermore, practical data processing schemes are provided in detail. Extensive validation results are demonstrated which include: 1) a forest height mosaic (total area of 11.6 million hectares) is generated for the U.S. states of Maine and New Hampshire using Japanese Aerospace Exploration Agency's (JAXA) ALOS-1 InSAR correlation data and a small airborne lidar strip (44 000 hectares); 2) the mosaic height estimates are further compared with the available airborne lidar data and field measurements over both flat and mountainous areas; and 3) feasibility of using modern repeat-pass InSAR satellites with short repeat interval is also examined by using JAXA's ALOS-2 data. This simple and efficient approach is a potential observational prototype with much smaller error budget for the future spaceborne repeat-pass L-band InSAR systems with small spatial baseline and moderate/large temporal baseline (such as NISAR) in combination with lidar (such as GEDI) on the application of large-scale forest height/biomass mapping. It also serves as a complementary tool to the spaceborne single-pass InSAR systems using InSAR/PolInSAR methods when full-pol data are not available and/or when the underlying topography slope causes problems for these approaches. Numéro de notice : A2019-109 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2860590 date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2860590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92427 [article]

Polarimetric radar vegetation index for biomass estimation in desert fringe ecosystems / Jisung Geba Chang 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 7102 - 7108 Titre : Polarimetric radar vegetation index for biomass estimation in desert fringe ecosystems Type de document : Article/Communication Auteurs : Jisung Geba Chang, Auteur ; Maxim Shoshany, Auteur ; Yisok Oh, Auteur Année de publication : 2018 Article en page(s) : pp 7102 - 7108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] allométrie [Termes descripteurs IGN] bande C [Termes descripteurs IGN] bande L [Termes descripteurs IGN] bassin méditerranéen [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] carte de la végétation [Termes descripteurs IGN] coefficient de rétrodiffusion [Termes descripteurs IGN] données de terrain [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] polarimétrie radar [Termes descripteurs IGN] zone aride [Termes descripteurs IGN] zone semi-aride Résumé : (auteur) Biomass estimation of eastern Mediterranean shrublands was investigated using PALSAR full- and dual-polarization L-band and Sentinel-1 dual-polarization C-band data. First, we conducted an empirical assessment of single and multiple regressions between polarized backscattering coefficients and shrubland biomass distribution along the climatic gradient between semiarid and arid regions. We then found that the PALSAR L-band HV-polarized backscattering coefficient has higher biomass information content than Sentinel-1 C-band data. Based on a theoretical volume scattering model and a semiempirical model, we propose a new polarimetric radar vegetation index (PRVI) that utilizes the degree of polarization and the cross-polarized backscattering coefficient. The relationship between the new index and the biomass was assessed with reference to normalized difference vegetation index-based biomass estimates calculated using Landsat imagery. The PRVI was found to have higher correlation with biomass compared with other radar polarization parameters, in general, and an existing radar vegetation index (RVI), in particular. Assessment of PRVI-based biomass predictions compared with allometric data extracted from air photographs, Lidar, and field data for 67 sites across the desert fringe zone indicated moderate performance with an RMSE of 0.329 kg/m 2 , while an RVI-based biomass estimation had an RMSE of 0.439 kg/m². Numéro de notice : A2018-553 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2848285 date de publication en ligne : 03/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2848285 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91659 [article]

Active tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) / Benoit Deffontaines in Natural Hazards and Earth System Sciences, vol 18 n° 3 ([01/03/2018])  

Public [article]  inNatural Hazards and Earth System Sciences > vol 18 n° 3 [01/03/2018] . - pp 829 - 845 Titre : Active tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) Type de document : Article/Communication Auteurs : Benoit Deffontaines , Auteur ; Kuo-Jen Chang, Auteur ; Johann Champenois, Auteur ; Kuan-Chuan Lin, Auteur ; Chyi-Tyi Lee, Auteur ; Rou-Fei Chen, Auteur ; Jyr-Ching Hu, Auteur ; Samuel Magalhaes, Auteur Année de publication : 2018 Article en page(s) : pp 829 - 845 Note générale : bibliographie This project was partially supported by LIA ADEPT (now D3E) no. 536, French CNRS-NSC (now MOST) and Taiwan MOST 105-2116-M-027-003. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] faille géologique [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] séisme [Termes descripteurs IGN] Taïwan Résumé : (auteur) Characterizing active faults and quantifying their activity are major concerns in Taiwan, especially following the major Chichi earthquake on 21 September 1999. Among the targets that still remain poorly understood in terms of active tectonics are the Hengchun and Kenting faults (Southern Taiwan). From a geodynamic point of view, the faults affect the outcropping top of the Manila accretionary prism of the Manila subduction zone that runs from Luzon (northern Philippines) to Taiwan. In order to better locate and quantify the location and quantify the activity of the Hengchun Fault, we start from existing geological maps, which we update thanks to the use of two products derived from unmanned aircraft system acquisitions: (1) a very high precision ( Numéro de notice : A2018-239 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/nhess-18-829-2018 date de publication en ligne : 15/03/2018 En ligne : https://doi.org/10.5194/nhess-18-829-2018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90191 [article]

Exploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 2018)  

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Bayesian data combination for the estimation of ionospheric effects in SAR interferograms / Giorgio Gomba in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)  

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The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)  

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An information fusion approach for PALSAR data to retrieve soil moisture / Ankita Jain in Geocarto international, vol 32 n° 9 (September 2017)  

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Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect / Pooja Mishra in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)  

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Mise en place d'une méthode semi-automatique de cartographie de l'occupation des sols à partir d'images SAR polarimétriques / Monique Moine in Revue Française de Photogrammétrie et de Télédétection, n° 215 (mai - août 2017)

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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)  

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Relative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation / Alyssa Endres in European journal of remote sensing, vol 49 (2016)  

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Investigation 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)  

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Toward 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)  

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