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SNR-based water height retrieval in rivers: Application to high amplitude asymmetric tides in the Garonne river / Pierre Zeiger in Remote sensing, vol 13 n° 9 (May 2021)  

Public [article]  inRemote sensing > vol 13 n° 9 (May 2021) . - n° 1856 Titre : SNR-based water height retrieval in rivers: Application to high amplitude asymmetric tides in the Garonne river Type de document : Article/Communication Auteurs : Pierre Zeiger, Auteur ; Frédéric Frappart, Auteur ; José Darrozes, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 1856 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] crue [Termes IGN] filtrage du bruit [Termes IGN] Garonne (bassin) [Termes IGN] interférence [Termes IGN] marée océanique [Termes IGN] modèle d'inversion [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] série temporelle [Termes IGN] surveillance hydrologique Résumé : (auteur) Signal-to-noise ratio (SNR) time series acquired by a geodetic antenna were analyzed to retrieve water heights during asymmetric tides on a narrow river using the Interference Pattern Technique (IPT) from Global Navigation Satellite System Reflectometry (GNSS-R). The dynamic SNR method was selected because the elevation rate of the reflecting surface during rising tides is high in the Garonne River with macro tidal conditions. A new process was developed to filter out the noise introduced by the environmental conditions on the reflected signal due to the narrowness of the river compared to the size of the Fresnel areas, the presence of vegetation on the river banks, and the presence of boats causing multiple reflections. This process involved the removal of multipeaks in the Lomb-Scargle Periodogram (LSP) output and an iterative least square estimation (LSE) of the output heights. Evaluation of the results was performed against pressure-derived water heights. The best results were obtained using all GNSS bands (L1, L2, and L5) simultaneously: R = 0.99, ubRMSD = 0.31 m. We showed that the quality of the retrieved heights was consistent, whatever the vertical velocity of the reflecting surface, and was highly dependent on the number of satellites visible. The sampling period of our solution was 1 min with a 5-min moving window, and no tide models or fit were used in the inversion process. This highlights the potential of the dynamic SNR method to detect and monitor extreme events with GNSS-R, including those affecting inland waters such as flash floods. Numéro de notice : A2021-406 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.3390/rs13091856 date de publication en ligne : 10/05/2021 En ligne : https://doi.org/10.3390/rs13091856 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97722 [article]

A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms / Dimitrios Bellos in Machine Vision and Applications, vol 32 n° 3 (May 2021)  

Public [article]  inMachine Vision and Applications > vol 32 n° 3 (May 2021) . - n° 75 Titre : A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms Type de document : Article/Communication Auteurs : Dimitrios Bellos, Auteur ; Mark Basham, Auteur ; Tony Pridmore, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 75 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] acquisition de connaissances [Termes IGN] apprentissage profond [Termes IGN] échantillonnage [Termes IGN] filtrage du bruit [Termes IGN] rapport signal sur bruit [Termes IGN] rayon X [Termes IGN] reconstruction d'image [Termes IGN] segmentation sémantique [Termes IGN] série temporelle [Termes IGN] tomographie Résumé : (auteur) Over recent years, many approaches have been proposed for the denoising or semantic segmentation of X-ray computed tomography (CT) scans. In most cases, high-quality CT reconstructions are used; however, such reconstructions are not always available. When the X-ray exposure time has to be limited, undersampled tomograms (in terms of their component projections) are attained. This low number of projections offers low-quality reconstructions that are difficult to segment. Here, we consider CT time-series (i.e. 4D data), where the limited time for capturing fast-occurring temporal events results in the time-series tomograms being necessarily undersampled. Fortunately, in these collections, it is common practice to obtain representative highly sampled tomograms before or after the time-critical portion of the experiment. In this paper, we propose an end-to-end network that can learn to denoise and segment the time-series’ undersampled CTs, by training with the earlier highly sampled representative CTs. Our single network can offer two desired outputs while only training once, with the denoised output improving the accuracy of the final segmentation. Our method is able to outperform state-of-the-art methods in the task of semantic segmentation and offer comparable results in regard to denoising. Additionally, we propose a knowledge transfer scheme using synthetic tomograms. This not only allows accurate segmentation and denoising using less real-world data, but also increases segmentation accuracy. Finally, we make our datasets, as well as the code, publicly available. Numéro de notice : A2021-456 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00138-021-01196-4 date de publication en ligne : 27/04/2021 En ligne : https://doi.org/10.1007/s00138-021-01196-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97902 [article]

Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS) / Langning Huo in Remote sensing of environment, Vol 255 (March 2021)  

Public [article]  inRemote sensing of environment > Vol 255 (March 2021) . - n° 112240 Titre : Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS) Type de document : Article/Communication Auteurs : Langning Huo, Auteur ; Henrik J. Persson, Auteur ; Eva Lindberg, Auteur Année de publication : 2021 Article en page(s) : n° 112240 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande infrarouge [Termes IGN] écho radar [Termes IGN] houppier [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de stress [Termes IGN] indice de végétation [Termes IGN] insecte nuisible [Termes IGN] maladie parasitaire [Termes IGN] Picea mariana [Termes IGN] Scolytinae [Termes IGN] signature spectrale [Termes IGN] Suède [Termes IGN] vulnérabilité Résumé : (auteur) The European spruce bark beetle (Ips typographus [L.]) is one of the most damaging pest insects of European spruce forests. A crucial measure in pest control is the removal of infested trees before the beetles leave the bark, which generally happens before the end of June. However, stressed tree crowns do not show any significant color changes in the visible spectrum at this early-stage of infestation, making early detection difficult. In order to detect the related forest stress at an early stage, we investigated the differences in radar and spectral signals of healthy and stressed trees. How the characteristics of stressed trees changed over time was analyzed for the whole vegetation season, which covered the period before attacks (April), early-stage infestation (‘green-attacks’, May to July), and middle to late-stage infestation (August to October). The results show that spectral differences already existed at the beginning of the vegetation season, before the attacks. The spectral separability between the healthy and infested samples did not change significantly during the ‘green-attack’ stage. The results indicate that the trees were stressed before the attacks and had spectral signatures that differed from healthy ones. These stress-induced spectral changes could be more efficient indicators of early infestations than the ‘green-attack’ symptoms. In this study we used Sentinel-1 and 2 images of a test site in southern Sweden from April to October in 2018 and 2019. The red and SWIR bands from Sentinel-2 showed the highest separability of healthy and stressed samples. The backscatter from Sentinel-1 and additional bands from Sentinel-2 contributed only slightly in the Random Forest classification models. We therefore propose the Normalized Distance Red & SWIR (NDRS) index as a new index based on our observations and the linear relationship between the red and SWIR bands. This index identified stressed forest with accuracies from 0.80 to 0.88 before the attacks, from 0.80 to 0.82 in the early-stage infestation, and from 0.81 to 0.91 in middle- and late-stage infestations. These accuracies are higher than those attained by established vegetation indices aimed at ‘green-attack’ detection, such as the Normalized Difference Water Index, Ratio Drought Index, and Disease Stress Water Index. By using the proposed method, we highlight the potential of using NDRS with Sentinel-2 images to estimate forest vulnerability to European spruce bark beetle attacks early in the vegetation season. Numéro de notice : A2021-190 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112240 date de publication en ligne : 20/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112240 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97111 [article]

Denoising Sentinel-1 extra-wide mode cross-polarization images over sea ice / Yan Sun in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 2116 - 2131 Titre : Denoising Sentinel-1 extra-wide mode cross-polarization images over sea ice Type de document : Article/Communication Auteurs : Yan Sun, Auteur ; Xiao-Ming Li, Auteur Année de publication : 2021 Article en page(s) : pp 2116 - 2131 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] Austral (océan) [Termes IGN] bruit thermique [Termes IGN] étalonnage radiométrique [Termes IGN] filtrage du bruit [Termes IGN] glace de mer [Termes IGN] image Sentinel-SAR [Termes IGN] image TOPSAR [Termes IGN] polarisation croisée [Termes IGN] rapport signal sur bruit Résumé : (Auteur) Sentinel-1 (S1) extra-wide (EW) swath data in cross-polarization (horizontal–vertical, HV or vertical–horizontal, VH) are strongly affected by the scalloping effect and thermal noise, particularly over areas with weak backscattered signals, such as sea surfaces. Although noise vectors in both the azimuth and range directions are provided in the standard S1 EW data for subtraction, the residual thermal noise still significantly affects sea ice detection by the EW data. In this article, we improve the denoising method developed in previous studies to remove the additive noise for the S1 EW data in cross-polarization. Furthermore, we propose a new method for eliminating the residual noise (i.e., multiplicative noise) at the subswath boundaries of the EW data, which cannot be well processed by simply subtracting the reconstructed 2-D noise field. The proposed method of removing both the additive and multiplicative noise was applied to EW HV-polarized images processed using different Instrument Processing Facility (IPF) versions. The results suggest that the proposed algorithm significantly improves the quality of EW HV-polarized images under various sea ice conditions and sea states in the marginal ice zone (MIZ) of the Arctic. This is of great support for the utilization of cross-polarization synthetic aperture radar (SAR) images in wide swaths for intensive sea ice monitoring in polar regions. Numéro de notice : A2021-214 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3005831 date de publication en ligne : 09/07/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3005831 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97202 [article]

Mitigating high latitude ionospheric scintillation effects on GNSS Precise Point Positioning exploiting 1-s scintillation indices / Kai Guo in Journal of geodesy, vol 95 n° 3 (March 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 3 (March 2021) . - n° 30 Titre : Mitigating high latitude ionospheric scintillation effects on GNSS Precise Point Positioning exploiting 1-s scintillation indices Type de document : Article/Communication Auteurs : Kai Guo, Auteur ; Sreeja Vadakke Veettil, Auteur ; Brian Jerald Weaver, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] Antarctique [Termes IGN] atténuation du signal [Termes IGN] Canada [Termes IGN] erreur de positionnement [Termes IGN] latitude [Termes IGN] positionnement par GNSS [Termes IGN] positionnement ponctuel précis [Termes IGN] récepteur GNSS [Termes IGN] scintillation [Termes IGN] tempête magnétique Résumé : (auteur) Ionospheric scintillation refers to rapid and random fluctuations in radio frequency signal intensity and phase, which occurs more frequently and severely at high latitudes under strong solar and geomagnetic activity. As one of the most challenging error sources affecting Global Navigation Satellite System (GNSS), scintillation can significantly degrade the performance of GNSS receivers, thereby leading to increased positioning errors. This study analyzes Global Positioning System (GPS) scintillation data recorded by two ionospheric scintillation monitoring receivers operational, respectively, in the Arctic and northern Canada during a geomagnetic storm in 2019. A novel approach is proposed to calculate 1-s scintillation indices. The 1-s receiver tracking error variances are then estimated, which are further used to mitigate the high latitude scintillation effects on GPS Precise Point Positioning. Results show that the 1-s scintillation indices can describe the signal fluctuations under scintillation more accurately. With the mitigation approach, the 3D positioning error is greatly reduced under scintillation analyzed in this study. Additionally, the 1-s tracking error variance achieves a better performance in scintillation mitigation compared with the previous approach which exploits 1-min tracking error variance estimated by the commonly used 1-min scintillation indices. This work is relevant for a better understanding of the high latitude scintillation effects on GNSS and is also beneficial for developing scintillation mitigation tools for GNSS positioning. Numéro de notice : A2021-222 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01475-y date de publication en ligne : 22/02/2021 En ligne : https://doi.org/10.1007/s00190-021-01475-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97191 [article]

On the polarimetric variable improvement via alignment of subarray channels in PPAR using weather returns / Igor R. Ivić in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

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Radar measurements of snow depth over sea ice on an unmanned aerial vehicle / Adrian Eng-Choon Tan in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

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G-band radar for humidity and cloud remote sensing / Ken B. Cooper in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)  

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Performance of 6 different global navigation satellite system receivers at low latitude under moderate and strong scintillation / E.R. de Paula in Earth and space science, vol 8 n° 2 (February 2021)  

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Study of systematic bias in measuring surface deformation with SAR interferometry / Homa Ansari in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)  

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Evaluation of multipath mitigation performance using signal-to-noise ratio (SNR) based signal selection methods / Valanon Uaratanawong in Journal of applied geodesy, vol 15 n° 1 (January 2021)  

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Underwater object detection and reconstruction based on active single-pixel imaging and super-resolution convolutional neural network / Mengdi Li in Sensors, vol 21 n° 1 (January 2021)  

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Integrated Kalman filter of accurate ranging and tracking with wideband radar / Shaopeng Wei in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)  

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Acquisition of weak GPS signals using wavelet-based de-noising methods / Mohaddeseh Sharie in Survey review, vol 52 n° 375 (November 2020)  

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A low-cost integrated MEMS-based INS/GPS vehicle navigation system with challenging conditions based on an optimized IT2FNN in occluded environments / Elahe S. Abdolkarimi in GPS solutions, Vol 24 n° 4 (October 2020)  

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