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PolGAN: A deep-learning-based unsupervised forest height estimation based on the synergy of PolInSAR and LiDAR data / Qi Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 123 - 139 Titre : PolGAN: A deep-learning-based unsupervised forest height estimation based on the synergy of PolInSAR and LiDAR data Type de document : Article/Communication Auteurs : Qi Zhang, Auteur ; Linlin Ge, Auteur ; Scott Hensley, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 123 - 139 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] analyse discriminante [Termes IGN] apprentissage non-dirigé [Termes IGN] apprentissage profond [Termes IGN] bande L [Termes IGN] données lidar [Termes IGN] forêt boréale [Termes IGN] forêt tropicale [Termes IGN] Global Ecosystem Dynamics Investigation lidar [Termes IGN] hauteur de la végétation [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] pansharpening (fusion d'images) [Termes IGN] polarimétrie radar [Termes IGN] pouvoir de résolution géométrique [Termes IGN] réseau antagoniste génératif [Termes IGN] semis de points Résumé : (auteur) This paper describes a deep-learning-based unsupervised forest height estimation method based on the synergy of the high-resolution L-band repeat-pass Polarimetric Synthetic Aperture Radar Interferometry (PolInSAR) and low-resolution large-footprint full-waveform Light Detection and Ranging (LiDAR) data. Unlike traditional PolInSAR-based methods, the proposed method reformulates the forest height inversion as a pan-sharpening process between the low-resolution LiDAR height and the high-resolution PolSAR and PolInSAR features. A tailored Generative Adversarial Network (GAN) called PolGAN with one generator and dual (coherence and spatial) discriminators is proposed to this end, where a progressive pan-sharpening strategy underpins the generator to overcome the significant difference between spatial resolutions of LiDAR and SAR-related inputs. Forest height estimates with high spatial resolution and vertical accuracy are generated through a continuous generative and adversarial process. UAVSAR PolInSAR and LVIS LiDAR data collected over tropical and boreal forest sites are used for experiments. Ablation study is conducted over the boreal site evidencing the superiority of the progressive generator with dual discriminators employed in PolGAN (RMSE: 1.21 m) in comparison with the standard generator with dual discriminators (RMSE: 2.43 m) and the progressive generator with a single coherence (RMSE: 2.74 m) or spatial discriminator (RMSE: 5.87 m). Besides that, by reducing the dependency on theoretical models and utilizing the shape, texture, and spatial information embedded in the high-spatial-resolution features, the PolGAN method achieves an RMSE of 2.37 m over the tropical forest site, which is much more accurate than the traditional PolInSAR-based Kapok method (RMSE: 8.02 m). Numéro de notice : A2022-195 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.02.008 Date de publication en ligne : 17/02/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.02.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99962 [article]

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Non-linear GNSS signal processing applied to land observation with high-rate airborne reflectometry / Hamza Issa (2022)  

Public Titre : Non-linear GNSS signal processing applied to land observation with high-rate airborne reflectometry Type de document : Thèse/HDR Auteurs : Hamza Issa, Auteur ; Serge Reboul, Directeur de thèse ; Ghaleb Faour, Directeur de thèse Editeur : Dunkerque : Université du Littoral-Côte-d'Opale Année de publication : 2022 Importance : 213 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse en vue de l'obtention du grade de Docteur de l’Université du Littoral Côte d’Opale Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] capteur aérien [Termes IGN] données radar [Termes IGN] humidité du sol [Termes IGN] modèle statistique [Termes IGN] précision métrique [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GNSS [Termes IGN] zone humide Index. décimale : THESE Thèses et HDR Résumé : (Auteur) Soil moisture remote sensing has been an active area of research over the past few decades due to its essential role in agriculture and in the prediction of some natural disasters. GNSS-Reflectometry (GNSS-R) is an emerging bistatic remote sensing technique that uses the L-band GNSS signals as sources of opportunity to characterize Earth surface. In this passive radar system, the amplitudes of the GNSS signal reflected by soil and the GNSS signal received directly from the GNSS satellites can be used to derive measurements of reflectivity from which the soil moisture content of the surface is determined.The study of soil moisture content using reflectivity measurements can also be applied for the detection of in-land water body surfaces. In this dissertation, we propose in the first step a non-linear estimate of the GNSS signal amplitude. This estimate is based on a statistical model that we develop for the coherent detection of a GNSS signal quantized on 1 bit. We show with experimentations on synthetic and real data that the proposed estimator is more accurate than reference approaches and provide measurements of the Signal-to-Noise Ratio (SNR) at a higher rate. When the reflected GNSS signal is obtained in an airborne experiment, its evolution as a function of time is piecewise stationary. The different stationary parts are associatedto different kinds of reflecting surfaces. We propose in a second step a change point detector that takes into account the radar signal characteristics in order to segment the signal. We show on synthetic data that the proposed change point detector can detect and localize changes more accurately than reference approaches present in the literature. This work is applied to airborne GNSSR observation of Earth. We propose in the third step, a new GNSS-R sensor with its implementation on a lightweight airborne carrier. We also propose a new front-end receiver architecture, a software radio implementation of thereceiver, and the complete instrumentation of the airborne carrier. A real flight experimentation has taken place in the North of France obtaining reflections from different landforms. We show using the airborne GNSS measurements obtained, that the proposed radar technique detects different surfaces along the flight trajectory, and in particular in-land water bodies, with high temporal and spatial resolution. We also show that we can localize the edges of the detected water body surfaces at meter accuracy. Note de contenu : General Introduction 1. Remote Sensing of Soil Moisture 1.1 Introduction 1.2 L-band emissions of land covers 1.3 Soil moisture remote sensing techniques 1.4 Remote sensing using GNSS-R 1.5 Conclusion 2. Carrier-to-Noise Estimation : Application to Soil Moisture Retrieval using GNSS-R 2.1 Introduction 2.2 Signal and system model 2.3 C/N0 estimators 2.4 Soil moisture retrieval from GNSS-R 2.5 Conclusion 3. A Probabilistic Model for On-line Estimation of the GNSS Carrier?to-Noise Ratio 3.1 Introduction 3.2 1-bit coherent detection principle 3.3 GNSS front end 3.4 Estimation of the GNSS signal amplitude 3.5 Experimentation 3.6 Conclusion 4. Segmentation of the GNSS Signal Amplitudes 4.1 Introduction 4.2 Change point detection principle 4.3 On-line/Off-line change detection system 4.4 Experimentation 4.5 Conclusion 5. Airborne GNSS Reflectometry for Water Body Detection 5.1 Introduction 5.2 Airborne GNSS system 5.3 Airborne experimental setup 5.4 GNSS-R software receiver 5.5 Flight Experimentation 5.6 Data analysis 5.7 Conclusion General Conclusion Numéro de notice : 26837 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Traitement du signal et des images : Université du Littoral Côte d’Opale : 2022 Organisme de stage : Laboratoire d'Informatique Signal et Image de la Côte d'Opale LISIC nature-HAL : Thèse DOI : sans Date de publication en ligne : 03/06/2022 En ligne : https://tel.hal.science/tel-03687353 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101094

Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n° 1 (October 2021)  

Public [article]  inNatural Hazards > vol 109 n° 1 (October 2021) . - pp 1201 - 1220 Titre : Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations Type de document : Article/Communication Auteurs : Caglar Bayik, Auteur ; Saygin Abdikan, Auteur ; Alpay Ozdemir, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1201 - 1220 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse diachronique [Termes IGN] bande C [Termes IGN] bande L [Termes IGN] données géologiques [Termes IGN] données GNSS [Termes IGN] effondrement de terrain [Termes IGN] image ALOS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] Istanbul (Turquie) [Termes IGN] surveillance géologique [Termes IGN] urbanisation Résumé : (auteur) This study aims to detect recent landslide displacements caused by geological structure of the region where there is intense urbanization using advanced Interferometric Synthetic Aperture Radar (InSAR) techniques and with Global Navigation Satellite Systems (GNSS) observations in the Beylikdüzü and Esenyurt districts in Istanbul megacity, Turkey. In this study, multiple satellites with different frequencies (C-band, L-band) and periodic GNSS observations were employed. For the entire peninsula, we processed 149 images from the ascending orbit, 144 images from the descending orbit of Sentinel-1 (C-Band) and 24 ALOS-2 (L-band) images from the ascending orbit. The evaluations were carried out in the period between 2015 and 2020 for Sentinel-1 imagery and 2015–2020 for ALOS-2 imagery respectively. Since the study area is covered by dense settlements, the Persistent Scatterer InSAR (PSI) technique was utilized to determine the landslide behaviors. According to the results, for both orbits of the Sentinel-1, the horizontal displacement and the vertical displacement were observed in the range of − 10 to 6 mm. Compared to the magnitude of displacement signal measured by Sentinel-1, ALOS-2 data has higher values due to the high surface penetration of the L-band. The results showed that most of the old landslide regions are reactivated. Horizontal movement derived through Sentinel-1 showed that the highest movement overlaps with old landslides. L-band ALOS-2 provided better spatial coverage of landslide movement than C-band Sentinel-1 data, especially at the rural Numéro de notice : A2021-752 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT/URBANISME Nature : Article DOI : 10.1007/s11069-021-04875-7 Date de publication en ligne : 20/06/2021 En ligne : https://doi.org/10.1007/s11069-021-04875-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98737 [article]

Seawater Debye model function at L-band and its impact on salinity retrieval from Aquarius satellite data / Yiwen Zhou in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 10 (October 2021) . - pp 8103 - 8116 Titre : Seawater Debye model function at L-band and its impact on salinity retrieval from Aquarius satellite data Type de document : Article/Communication Auteurs : Yiwen Zhou, Auteur ; Roger H. Lang, Auteur ; Emmanuel P. Dinnat, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 8103 - 8116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] constante diélectrique [Termes IGN] eau de mer [Termes IGN] image SAC-D-Aquarius [Termes IGN] salinité [Termes IGN] température de surface de la mer Résumé : (auteur) A model function of seawater, which specifies the dielectric constant of seawater as a function of salinity, temperature, and frequency, is important for the retrieval of sea surface salinity using satellite data. In 2017, a model function has been developed based on measurement data at 1.4134 GHz using a third-order polynomial expression in salinity ( S ) and temperature ( T ). Although the model showed improvements in salinity retrieval, it had an inconsistent behavior between partitioned salinities. To improve the stability of the model, new dielectric measurements of seawater have been made recently over a broad range of salinities and temperatures to expand the data set used for developing the model function. The structure of the model function has been changed from a polynomial expansion in S and T to a physics-based model consisting of a Debye molecular resonance term plus a conductivity term. Each unknown parameter is expressed in S and T based on the expanded measurement data set. Physical arguments have been used to limit the number of unknown coefficients in these expressions to improve the stability of the model function. The new model function has been employed in the retrieval algorithm of the Aquarius satellite mission to obtain a global salinity map. The retrieved salinity using a different model function is compared with in situ data collected by Argo floats to evaluate the impact and the performance of model functions. The results indicate that the new model function has significant improvements in salinity retrieval compared with other existing models. Numéro de notice : A2021-767 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3045771 Date de publication en ligne : 14/01/2021 En ligne : https://doi.org/10.1109/TGRS.2020.3045771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98606 [article]

Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data / Fang Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7487 - 7499 Titre : Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data Type de document : Article/Communication Auteurs : Fang Shang, Auteur ; Taiga Saito, Auteur ; Saya Ohi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7487 - 7499 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] détection de changement [Termes IGN] détection de cible [Termes IGN] distribution spatiale [Termes IGN] forêt de feuillus [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] Japon [Termes IGN] Pinophyta [Termes IGN] polarimétrie radar Résumé : (auteur) This article proposes a coniferous and broad-leaved forest distinguishing method using L-band polarimetric SAR data based on the structure-orientation parameter. The structure-orientation parameter is one of the averaged Stokes vector-based discriminators which is sensitive to the composition of equivalent horizontal and vertical structures. In the proposed method, the structure-orientation parameters is compensated by employing the scattered power information to remove the influence of the topography. The final distinguishing result is generated based on the statistical feature of the compensated parameters. The experiments using several sets of ALOS2-PALSAR2 level 1.1 data prove that the proposed method has high performance for forest-type distinguishing. Numéro de notice : A2021-648 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3032468 Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3032468 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98355 [article]

Forest height estimation from a robust TomoSAR method in the case of small tomographic aperture with airborne dataset at L-band / Xing Peng in Remote sensing, vol 13 n° 11 (June-1 2021)  

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Graph convolutional networks by architecture search for PolSAR image classification / Hongying Liu in Remote sensing, vol 13 n° 7 (April-1 2021)  

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Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques / Yue Huang in Remote sensing, Vol 13 n° 3 (February 2021)  

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Optimizing flood mapping using multi-synthetic aperture radar images for regions of the lower mekong basin in Vietnam / Vu Anh Tuan in European journal of remote sensing, vol 54 n° 1 (2021)  

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Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning / Maryam Pourshamsi in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)  

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Slope engineering / Ali Ismet Kanlı (2021)  

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L’Ultra Wideband, un système de positionnement topographique sans satellite / Joël Van Cranenbroeck in XYZ, n° 165 (décembre 2020)

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Bistatic specular scattering measurements for the estimation of rice crop growth variables using fuzzy inference system at X-, C-, and L-bands / Ajeet Kumar Vishwakarma in Geocarto international, vol 35 n° 13 ([01/10/2020])  

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Ground-based remote sensing of forests exploiting GNSS signals / Leila Guerriero in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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L-band SAR for estimating aboveground biomass of rubber plantation in Java Island, Indonesia / Bambang H Trisasongko in Geocarto international, vol 35 n° 12 ([01/09/2020])  

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