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Deformation analysis of a reference wall towards the uncertainty investigation of terrestrial laser scanners / Berit Schmitz in Journal of applied geodesy, vol 15 n° 3 (July 2021)  

Public [article]  inJournal of applied geodesy > vol 15 n° 3 (July 2021) . - pp 189-206 Titre : Deformation analysis of a reference wall towards the uncertainty investigation of terrestrial laser scanners Type de document : Article/Communication Auteurs : Berit Schmitz, Auteur ; Heiner Kuhlmann, Auteur ; Christoph Holst, Auteur Année de publication : 2021 Article en page(s) : pp 189-206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] déformation d'édifice [Termes IGN] déformation géométrique [Termes IGN] données laser [Termes IGN] incertitude géométrique [Termes IGN] matrice de covariance [Termes IGN] modèle de déformation tectonique [Termes IGN] modèle stochastique [Termes IGN] mur [Termes IGN] qualité des données [Termes IGN] tachéomètre électronique [Termes IGN] télémètre laser terrestre Résumé : (Auteur) The perfect knowledge about the scanned object’s geometry is essential for the empirical analysis of the stochastic properties of terrestrial laser scanners (TLSs). The Bonn reference wall is intended to be used as a reference for TLS quality investigations. Therefore, it is necessary to know the geometry of the wall at each time of scanning to avoid the misinterpretation of possible movements as systematic effects in the scanner. For this reason, we investigate the stability of the Bonn reference wall in this study. This includes the definition of a geodetic datum, the quantification of displacements, and the establishment of a suited deformation model. Since we discover a movement of about 1 mm within one day and up to 7 mm over the year, it is necessary to establish a cause-response deformation model to correct the wall movements in the scans. This study proposes two dynamic deformation models to compensate for the movements of the wall within one day and within a year. Our results show that it is better to measure the initial geometry of the wall each day since 89 % of the relative movements can be reduced to a maximum of 0.25 mm with a standard deviation of 0.16 mm (0.23 mm without modeling). If the shape is not initially known each day, the standard deviation of the displacements can be reduced from 1.10 mm to 0.61 mm, but the largest residuals still amount up to 2.5 mm, which is not sufficient for stochastic TLS investigations. Numéro de notice : A2021-467 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0025 date de publication en ligne : 25/03/2021 En ligne : https://doi.org/10.1515/jag-2020-0025 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98103 [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)  

Public [article]  inRemote sensing > vol 13 n° 11 (June-1 2021) . - n° 2147 Titre : Forest height estimation from a robust TomoSAR method in the case of small tomographic aperture with airborne dataset at L-band Type de document : Article/Communication Auteurs : Xing Peng, Auteur ; Xinwu Li, Auteur ; Yanan Du, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2147 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande L [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] données TomoSAR [Termes IGN] forêt boréale [Termes IGN] hauteur des arbres [Termes IGN] image 3D [Termes IGN] image radar moirée [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] itération [Termes IGN] matrice de covariance [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] semis de points [Termes IGN] Suède [Termes IGN] tomographie radar Résumé : (auteur) Forest height is an essential input parameter for forest biomass estimation, ecological modeling, and the carbon cycle. Tomographic synthetic aperture radar (TomoSAR), as a three-dimensional imaging technique, has already been successfully used in forest areas to retrieve the forest height. The nonparametric iterative adaptive approach (IAA) has been recently introduced in TomoSAR, achieving a good compromise between high resolution and computing efficiency. However, the performance of the IAA algorithm is significantly degraded in the case of a small tomographic aperture. To overcome this shortcoming, this paper proposes the robust IAA (RIAA) algorithm for SAR tomography. The proposed approach follows the framework of the IAA algorithm, but also considers the noise term in the covariance matrix estimation. By doing so, the condition number of the covariance matrix can be prevented from being too large, improving the robustness of the forest height estimation with the IAA algorithm. A set of simulated experiments was carried out, and the results validated the superiority of the RIAA estimator in the case of a small tomographic aperture. Moreover, a number of fully polarimetric L-band airborne tomographic SAR images acquired from the ESA BioSAR 2008 campaign over the Krycklan Catchment, Northern Sweden, were collected for test purposes. The results showed that the RIAA algorithm performed better in reconstructing the vertical structure of the forest than the IAA algorithm in areas with a small tomographic aperture. Finally, the forest height was estimated by both the RIAA and IAA TomoSAR methods, and the estimation accuracy of the RIAA algorithm was 2.01 m, which is more accurate than the IAA algorithm with 3.25 m. Numéro de notice : A2021-441 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13112147 date de publication en ligne : 29/05/2021 En ligne : https://doi.org/10.3390/rs13112147 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97828 [article]

PolSAR ship detection based on neighborhood polarimetric covariance matrix / Tao Liu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 6 (June 2021) . - pp 4874 - 4887 Titre : PolSAR ship detection based on neighborhood polarimetric covariance matrix Type de document : Article/Communication Auteurs : Tao Liu, Auteur ; Ziyuan Yang, Auteur ; Armando Marino, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 4874 - 4887 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] détection d'objet [Termes IGN] données polarimétriques [Termes IGN] image radar moirée [Termes IGN] image Radarsat [Termes IGN] matrice de covariance [Termes IGN] navire [Termes IGN] polarimétrie radar [Termes IGN] voisinage (topologie) Résumé : (auteur) The detection of small ships in polarimetric synthetic aperture radar (PolSAR) images is still a topic for further investigation. Recently, patch detection techniques, such as superpixel-level detection, have stimulated wide interest because they can use the information contained in similarities among neighboring pixels. In this article, we propose a novel neighborhood polarimetric covariance matrix (NPCM) to detect the small ships in PolSAR images, leading to a significant improvement in the separability between ship targets and sea clutter. The NPCM utilizes the spatial correlation between neighborhood pixels and maps the representation for a given pixel into a high-dimensional covariance matrix by embedding spatial and polarization information. Using the NPCM formalism, we apply a standard whitening filter, similar to the polarimetric whitening filter (PWF). We show how the inclusion of neighborhood information improves the performance compared with the traditional polarimetric covariance matrix. However, this is at the expense of a higher computation cost. The theory is validated via the simulated and measured data under different sea states and using different radar platforms. Numéro de notice : A2021-424 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3022181 date de publication en ligne : 22/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3018638 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97780 [article]

High-resolution geoid modeling using least squares modification of Stokes and Hotine formulas in Colorado / Mustafa Serkan Işık in Journal of geodesy, vol 95 n° 5 (May 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 5 (May 2021) . - n° 49 Titre : High-resolution geoid modeling using least squares modification of Stokes and Hotine formulas in Colorado Type de document : Article/Communication Auteurs : Mustafa Serkan Işık, Auteur ; Bihter Erol, Auteur ; Serdar Erol, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 49 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] Colorado (Etats-Unis) [Termes IGN] correction [Termes IGN] géoïde local [Termes IGN] intégrale de Stokes [Termes IGN] levé gravimétrique [Termes IGN] matrice de covariance [Termes IGN] méthode des moindres carrés [Termes IGN] modèle de géopotentiel [Termes IGN] modèle mathématique [Termes IGN] montagne [Termes IGN] nivellement [Termes IGN] système de référence altimétrique Résumé : (auteur) The Colorado geoid experiment was initiated and organized as a joint study by the Joint Working Group (JWG) 2.2.2 (1-cm geoid experiment) of the International Association of Geodesy (IAG) in 2017, and different institutions and research groups contributed to this study. The aim of this experiment was to clarify the repeatability of gravity potential values as International Height Reference System (IHRS) coordinates from different geoid determination approaches carried out with the same input dataset. The dataset included the terrestrial and airborne gravity observations, a digital terrain model, the XGM2016 global geopotential model and GPS/leveling data for model validations belonging to a mountainous area of approximately 550 km × 730 km in Colorado, US. The dataset was provided by National Geodetic Survey (NGS) department. In this frame, this article aims providing a discussion on Colorado geoid modeling through individual experimental results obtained by Istanbul Technical University-Gravity Research Group (ITU-GRG). This contribution mainly focused on modeling the Colorado geoid using the least squares modifications of Stokes and Hotine integral formulas with additive corrections. The computations using each formula were carried out using ITU-GRG software, including the solution variants based on terrestrial-only, airborne-only and combined gravity datasets. Then, the calculated experimental geoid models were validated using historical and recently measured profile-based GPS/leveling datasets, and they were also compared with the official solutions submitted by different institutions for the “1-cm geoid experiment” of IAG JWG 2.2.2. For all validation results, the Hotine and Stokes integral formulas yielded similar performances in terms of geoid accuracy; however, the models computed using the combined data had better accuracy than those using the terrestrial-only and airborne-only solutions. The geoid model solutions using the combined data had an accuracy of 2.69 cm for the Hotine method and 2.87 cm for the Stokes method in the test results using GPS/leveling data of the GSVS17 (Geoid Slope Validation Survey 2017) profile. Airborne data from the Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project contributed significantly towards improving the geoid model, especially in the mountainous parts of the area. Numéro de notice : A2021-311 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01501-z date de publication en ligne : 07/04/2021 En ligne : https://doi.org/10.1007/s00190-021-01501-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97503 [article]

Stochastic model reliability in GNSS baseline solution / Aviram Borko in Journal of geodesy, vol 95 n° 2 (February 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 2 (February 2021) . - n° 20 Titre : Stochastic model reliability in GNSS baseline solution Type de document : Article/Communication Auteurs : Aviram Borko, Auteur ; Gilad Even-Tzur, Auteur Année de publication : 2021 Article en page(s) : n° 20 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données GNSS [Termes IGN] double différence [Termes IGN] fiabilité des données [Termes IGN] ligne de base [Termes IGN] matrice de covariance [Termes IGN] modèle stochastique [Termes IGN] résolution d'ambiguïté [Termes IGN] test statistique [Vedettes matières IGN] Traitement de données GNSS Résumé : (auteur) GNSS observations stochastic model influences all subsequent stages of data processing, from the possibility to reach the optimal parameters estimation, to the reliability and quality control of the solution. Nowadays, an uncontrolled use of GNSS stochastic models is common for both data processing and simulation missions, especially in commercial GNSS software packages. As a result, the variance–covariance matrices that are derived in the processing are inadequate and cause incorrect interpretations of the results. A proper method to evaluate the reliability of the stochastic model is needed to reflect the confidence level in statistic testing and simulation mission efforts. In this contribution, a novel method for evaluating the statistical nature of GNSS stochastic model is presented. The method relies on the deterministic nature of the integer ambiguity variable to examine and express the expected multinormal distribution of the double-difference adjustment results. The suggested method was used with a controlled experiment and 24 h of observations data to investigate how the statistical nature of the stochastic model is affected by different baseline lengths. The results indicate that as the baseline length increases, the stochastic model is less predictable and exposed to irregularities in the observation’s precision. Additionally, the reliability of the integer ambiguity resolution success rate (SR) was tested as part of the stochastic model evaluation. The results show a dramatic degradation in the SR prediction level when using an inadequate stochastic model, which suggests using extra caution when handling this parameter unless high-confidence reliable stochastic model is available. Numéro de notice : A2021-136 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01472-1 date de publication en ligne : 31/01/2021 En ligne : https://doi.org/10.1007/s00190-021-01472-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97009 [article]

Impact of INSAT-3D/3DR radiance data assimilation in predicting tropical cyclone Titli over the bay of Bengal / Raghu Nadimpalli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Stochastic modeling for VRS network-based GNSS RTK with residual interpolation uncertainty / Thanate Jongrujinan in Journal of applied geodesy, vol 14 n° 3 (July 2020)  

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A point cloud feature regularization method by fusing judge criterion of field force / Xijiang Chen in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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Deep SAR-Net: learning objects from signals / Zhongling Huang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)  

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2014 Hartebeesthoek co-location survey reprocessing report / Jean-Michaël Muller (2020)

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Approche bayésienne pour la sélection de modèles / Benjamin Harroué (2020)  

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Identification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data / Guo-Hui Yao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)  

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The certitude of a global sea level acceleration during the satellite altimeter era / Huseyin Baki Iz in Journal of geodetic science, vol 10 n° 1 (January 2020)  

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Robust M–M unscented Kalman filtering for GPS/IMU navigation / Cheng Yang in Journal of geodesy, vol 93 n° 8 (August 2019)  

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An improved robust Kalman filtering strategy for GNSS kinematic positioning considering small cycle slips / Wanke Liu in Advances in space research, vol 63 n° 9 (1 May 2019)  

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