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Global forecasting of ionospheric vertical total electron contents via ConvLSTM with spectrum analysis / Jinpei Chen in GPS solutions, vol 26 n° 3 (July 2022)
[article]
Titre : Global forecasting of ionospheric vertical total electron contents via ConvLSTM with spectrum analysis Type de document : Article/Communication Auteurs : Jinpei Chen, Auteur ; Nan Zhi, Auteur ; Haofan Liao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 69 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] analyse diachronique
[Termes IGN] analyse spectrale
[Termes IGN] apprentissage profond
[Termes IGN] carte ionosphérique mondiale
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] correction ionosphérique
[Termes IGN] modèle dynamique
[Termes IGN] positionnement par GNSS
[Termes IGN] temps de convergence
[Termes IGN] teneur verticale totale en électronsRésumé : (auteur) The widely used GNSS correction services for high precision positioning take advantage of accurate real-time TEC forecasting based on vertical total electron content (VTEC) maps. The methods for modeling and forecasting are mainly based on overly simplified assumptions, which in principle cannot reflect the real situations due to limitations of the mathematical formulations. Therefore, these methods cannot comprehensively capture the features of ionospheric TEC in spatial–temporal series. To overcome the problems caused by such assumptions, we combine ConvLSTM (convolutional long short-term memory) with spectrum analysis. The method allows the extraction of high-resolution spatial–temporal patterns of the ionospheric VTEC maps and accelerates the convergence time of neural networks. Extensive experiments have been carried out for short- and long-term forecasting and demonstrated that the performance of our method is better than other state-of-the-art models developed for various time series analysis methods. Based on the data from global ionospheric maps (GIMs) products, the results show that the root-mean-square error (RMSE) of global VTEC forecasting by our method substantially improves for two hours intervals over the years 2015, 2016, 2017 and 2019 compared to existing methods, specifically, 20–50% reduction on 1 or 2 h forecasting in terms of RMSE. In addition, the method is sufficient to support real-time forecasting since it takes less than one second to output global forecasting solutions. With these properties, we can facilitate real-time and highly accurate ionosphere correction services beneficial to numerous GNSS correct services and positioning terminals. Numéro de notice : A2022-378 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01253-z Date de publication en ligne : 13/04/2022 En ligne : https://doi.org/10.1007/s10291-022-01253-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100638
in GPS solutions > vol 26 n° 3 (July 2022) . - n° 69[article]Multi-frequency phase-only PPP-RTK model applied to BeiDou data / Pengyu Hou in GPS solutions, vol 26 n° 3 (July 2022)
[article]
Titre : Multi-frequency phase-only PPP-RTK model applied to BeiDou data Type de document : Article/Communication Auteurs : Pengyu Hou, Auteur ; Baocheng Zhang, Auteur ; Yury V. Yasyukevich, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 76 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] ambiguïté entière
[Termes IGN] données BeiDou
[Termes IGN] erreur de phase
[Termes IGN] fréquence multiple
[Termes IGN] modèle de simulation
[Termes IGN] phase GNSS
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] positionnement par BeiDou
[Termes IGN] positionnement ponctuel précis
[Termes IGN] résolution d'ambiguïté
[Termes IGN] retard ionosphèrique
[Termes IGN] trajet multipleRésumé : (auteur) Typically, navigation software processes global navigation satellite system (GNSS) phase observables along with the code observables to achieve high-precision positioning. However, the unmodeled code-related errors, typically multipath effects, may deteriorate the positioning performance. Such effects are well known for the second generation BeiDou navigation satellite system (BDS-2). To prevent this adverse effect on the state-of-the-art positioning technique, namely integer ambiguity resolution-enabled precise point positioning (PPP-RTK), we propose a multi-frequency phase-only PPP-RTK model. This model excludes the code observables and addresses the rank deficiency problem underlying the phase observation equations at the undifferenced and uncombined level. To verify the model, we collect five-day triple-frequency BDS 30-s data from a network of seven reference stations (about 112 km apart) to estimate the products on the network side. Based on these products, we conduct simulated dynamic positioning at a user station to test the phase-only PPP-RTK model and compare it with the customary code-plus-phase (CPP) model. The results show that the satellite phase biases, existing only at the third frequency, have a precision of better than two centimeters, while the precision of the satellite clock and ionospheric delay is better than eight centimeters. Due to the strong correlation between individual corrections, it is necessary to assess the quality of combined products, including the satellite clock, satellite phase bias and ionospheric delay, the precision of which is several millimeters to two centimeters, which is sufficiently precise for user positioning. Regarding BDS-2 positioning, the time-to-first-fix (TTFF) of the CPP PPP-RTK is 12 epochs, while it is only three epochs for the phase-only PPP-RTK. The reason why the CPP model underperforms the phase-only model is that the BDS-2 data collected are subject to notable code multipath. We show that the code multipath in the third-generation BDS (BDS-3) data is mild, so the CPP PPP-RTK achieves instantaneous centimeter-level positioning with a TTFF of one epoch. The BDS-3 phase-only PPP-RTK obtains virtually the same positioning results, but the TTFF is two epochs. When combining BDS-2 with BDS-3, the TTFF of both models remains unchanged compared to that of the BDS-3 solutions, implying that ambiguity resolution based on the stronger dual-system CPP model is robust to the BDS-2 code multipath. However, the ambiguity-float solution of the CPP PPP-RTK is adversely affected by the code multipath and requires 43 epochs to convergence, while its phase-only counterpart needs 36 epochs. Numéro de notice : A2022-377 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01263-x Date de publication en ligne : 10/05/2022 En ligne : https://doi.org/10.1007/s10291-022-01263-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100637
in GPS solutions > vol 26 n° 3 (July 2022) . - n° 76[article]Outliers and uncertainties in GNSS ZTD estimates from double-difference processing and precise point positioning / Katarzyna Stępniak in GPS solutions, vol 26 n° 3 (July 2022)
[article]
Titre : Outliers and uncertainties in GNSS ZTD estimates from double-difference processing and precise point positioning Type de document : Article/Communication Auteurs : Katarzyna Stępniak, Auteur ; Olivier Bock , Auteur ; Pierre Bosser , Auteur ; Pawel Wielgosz, Auteur Année de publication : 2022 Projets : VEGAN / Bock, Olivier Article en page(s) : n° 74 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données GNSS
[Termes IGN] double différence
[Termes IGN] ERA5
[Termes IGN] incertitude des données
[Termes IGN] positionnement ponctuel précis
[Termes IGN] retard troposphérique zénithal
[Termes IGN] valeur aberrante
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) Double-difference (DD) analysis and precise point positioning (PPP) are two widely used processing approaches to analyze ground-based GNSS measurements. We investigate the quality of the zenith tropospheric delay (ZTD) estimates produced from both processing approaches for a regional network over 1 year and show that DD solutions contain more numerous and larger ZTD outliers. The accuracy of both DD and PPP solutions strongly depends on the data processing procedure and models. We analyze the impact of mapping functions, satellite orbit and clock products and ambiguity resolution (fixed vs. float) on ZTD estimates. The results are assessed from station position repeatability and ZTD differences with respect to the ERA5 reanalysis. As expected, mapping functions have the strongest impact, with VMF1 being more accurate than GMF. Surprisingly, the impact of the ambiguity resolution and satellite products is rather weak in the PPP solution. We speculate that this results from the fact that final satellite products have reached a high level of accuracy and that other error sources now dominate static PPP solutions. A time and frequency analysis reveal unprecedented spurious sub-daily signals in the ZTD time series, which occur at the frequency of the GPS satellite repeat period and its harmonics. This suggests that sub-daily GPS ZTD estimates contain a significant part of the residual modeling errors due to satellite orbits, tidal models, mapping functions and multipath, which still need to be improved. Numéro de notice : A2022-359 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-022-01261-z Date de publication en ligne : 29/04/2022 En ligne : https://doi.org/10.1007/s10291-022-01261-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100578
in GPS solutions > vol 26 n° 3 (July 2022) . - n° 74[article]Simulation-driven 3D forest growth forecasting based on airborne topographic LiDAR data and shading / Štefan Kohek in International journal of applied Earth observation and geoinformation, vol 111 (July 2022)
[article]
Titre : Simulation-driven 3D forest growth forecasting based on airborne topographic LiDAR data and shading Type de document : Article/Communication Auteurs : Štefan Kohek, Auteur ; Borut Žalik, Auteur ; Damjan Strnad, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102844 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de sensibilité
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] dissymétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] houppier
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] modèle numérique de terrain
[Termes IGN] modélisation de la forêt
[Termes IGN] ombre
[Termes IGN] semis de points
[Termes IGN] SlovénieRésumé : (auteur) Reliable forest growth forecasting requires detailed tree data for forest simulation, while manual on-site collection of relevant data is work-intensive and unfeasible in larger forests. This paper proposes a complete methodology for fully automated forest growth simulation that relies primarily on airborne topographic Light Detection And Ranging (LiDAR) point clouds of individual trees. The proposed method estimates tree parameters and performs growth of individual trees based on an individual-based forest growth simulator, named BWINPro. In addition, competition and detailed asymmetric tree crown growth are modeled regarding the shading of tree crowns, which is estimated from the surrounding environment and neighbor trees. The result of the proposed approach is a new point cloud for subsequent analyses. The proposed method was validated by comparing canopy height models derived from the point clouds of the simulated trees with canopy height models derived from more recent ground truth point clouds. The results demonstrate the efficacy of the proposed method which achieves a 9.4% higher accuracy than the averaged linear regression model and, in the case of datasets with more distinct self-standing trees, where a tree crown boundary plays major role, a 4.1% higher accuracy than the directly fitted linear regression model. Numéro de notice : A2022-552 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102844 Date de publication en ligne : 04/06/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102844 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101156
in International journal of applied Earth observation and geoinformation > vol 111 (July 2022) . - n° 102844[article]DART-Lux: An unbiased and rapid Monte Carlo radiative transfer method for simulating remote sensing images / Yingjie Wang in Remote sensing of environment, vol 274 (June 2022)
[article]
Titre : DART-Lux: An unbiased and rapid Monte Carlo radiative transfer method for simulating remote sensing images Type de document : Article/Communication Auteurs : Yingjie Wang, Auteur ; Abdelaziz Kallel, Auteur ; Xuebo Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112973 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande spectrale
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] image à haute résolution
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de transfert radiatif
[Termes IGN] radiance
[Termes IGN] réflectance directionnelle
[Termes IGN] scène forestière
[Termes IGN] scène urbaineRésumé : (auteur) Accurate and efficient simulation of remote sensing images is increasingly needed in order to better exploit remote sensing observations and to better design remote sensing missions. DART (Discrete Anisotropic Radiative Transfer), developed since 1992 based on the discrete ordinates method (i.e., standard mode DART-FT), is one of the most accurate and comprehensive 3D radiative transfer models to simulate the radiative budget and remote sensing observations of urban and natural landscapes. Recently, a new method, called DART-Lux, was integrated into DART model to address the requirements of massive remote sensing data simulation for large-scale and complex landscapes. It is developed based on efficient Monte Carlo light transport algorithms (i.e., bidirectional path tracing) and on DART model framework. DART-Lux can accurately and rapidly simulate the bidirectional reflectance factor (BRF) and spectral images of arbitrary landscapes. This paper presents its theory, implementation, and evaluation. Its accuracy, efficiency and advantages are also discussed. The comparison with standard DART-FT in a variety of scenarios shows that DART-Lux is consistent with DART-FT (relative differences Numéro de notice : A2022-398 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.112973 Date de publication en ligne : 26/03/2022 En ligne : https://doi.org/10.1016/j.rse.2022.112973 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100698
in Remote sensing of environment > vol 274 (June 2022) . - n° 112973[article]Variance based fusion of VCI and TCI for efficient classification of agriculture drought using MODIS data / Anjana N.J. Kukunuri in Geocarto international, vol 37 n° 10 ([01/06/2022])PermalinkCalibration of a light hemispherical radiance field imaging system / Manchun Lei in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-1-2022 (2022 edition)PermalinkVegetation cover mapping from RGB webcam time series for land surface emissivity retrieval in high mountain areas / Benedikt Hiebl in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)PermalinkDetection and mapping of snow avalanche debris from Western Himalaya, India using remote sensing satellite images / Kamal Kant Singh in Geocarto international, vol 37 n° 9 ([15/05/2022])PermalinkRegional ionospheric corrections for high accuracy GNSS positioning / Tam Dao in Remote sensing, vol 14 n° 10 (May-2 2022)PermalinkAlternative procedure to improve the positioning accuracy of orthomosaic images acquired with Agisoft Metashape and DJI P4 multispectral for crop growth observation / Toshihiro Sakamoto in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 5 (May 2022)PermalinkEfficient convolutional neural architecture search for LiDAR DSM classification / Aili Wang in IEEE Transactions on geoscience and remote sensing, vol 60 n° 5 (May 2022)PermalinkLandslide susceptibility assessment considering spatial agglomeration and dispersion characteristics: A case study of Bijie City in Guizhou Province, China / Kezhen Yao in ISPRS International journal of geo-information, vol 11 n° 5 (May 2022)PermalinkMulti-modal temporal attention models for crop mapping from satellite time series / Vivien Sainte Fare Garnot in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)PermalinkUnmixing-based spatiotemporal image fusion accounting for complex land cover changes / Xiaolu Jiang in IEEE Transactions on geoscience and remote sensing, vol 60 n° 5 (May 2022)Permalink