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Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data / Yaotong Cai in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)
[article]
Titre : Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data Type de document : Article/Communication Auteurs : Yaotong Cai, Auteur ; Xinyu Li, Auteur ; Meng Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102164 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] algorithme de généralisation
[Termes IGN] analyse d'image orientée objet
[Termes IGN] cartographie thématique
[Termes IGN] Chine
[Termes IGN] filtre de déchatoiement
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] prairie
[Termes IGN] rétrodiffusion
[Termes IGN] série temporelle
[Termes IGN] zone humideRésumé : (auteur) Wetland ecosystems have experienced dramatic challenges in the past few decades due to natural and human factors. Wetland maps are essential for the conservation and management of terrestrial ecosystems. This study is to obtain an accurate wetland map using an object-based stacked generalization (Stacking) method on the basis of multi-temporal Sentinel-1 and Sentinel-2 data. Firstly, the Robust Adaptive Spatial Temporal Fusion Model (RASTFM) is used to get time series Sentinel-2 NDVI, from which the vegetation phenology variables are derived by the threshold method. Subsequently, both vertical transmit-vertical receive (VV) and vertical transmit-horizontal receive (VH) polarization backscatters (σ0 VV, σ0 VH) are obtained using the time series Sentinel-1 images. Speckle noise inherent in SAR data, resulting in over-segmentation or under-segmentation, can affect image segmentation and degrade the accuracies of wetland classification. Therefore, we segment Sentinel-2 multispectral images to delineate meaningful objects in this study. Then, in order to reduce data redundancy and computation time, we analyze the optimal feature combination using the Sentinel-2 multispectral images, Sentinel-2 NDVI time series, phenological variables and other vegetation index derived from Sentinel-2 multispectral images, as well as time series Sentinel-1 backscatters at the object level. Finally, the stacked generalization algorithm is utilized to extract the wetland information based on the optimal feature combination in the Dongting Lake wetland. The overall accuracy and Kappa coefficient of the object-based stacked generalization method are 92.46% and 0.92, which are 3.88% and 0.04 higher than that using the pixel-based method. Moreover, the object-based stacked generalization algorithm is superior to single classifiers in classifying vegetation of high heterogeneity areas. Numéro de notice : A2020-748 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102164 Date de publication en ligne : 07/06/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102164 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96398
in International journal of applied Earth observation and geoinformation > vol 92 (October 2020) . - n° 102164[article]GipsyX/RTGx, a new tool set for space geodetic operations and research / Willy I. Bertiger in Advances in space research, vol 66 n° 3 (1 August 2020)
[article]
Titre : GipsyX/RTGx, a new tool set for space geodetic operations and research Type de document : Article/Communication Auteurs : Willy I. Bertiger, Auteur ; Yoaz E. Bar-Sever, Auteur ; A. Dorsey, Auteur ; Bruce J. Haines, Auteur ; N.R. Harvey, Auteur ; Dan Hemberger, Auteur ; Michael B. Heflin, Auteur ; Wenwen Lu, Auteur ; Mark Miller, Auteur ; Angelyn Moore, Auteur ; Dave Murphy, Auteur ; Paul Ries, Auteur ; L.J. Romans, Auteur ; Aurore E. Sibois, Auteur ; Ant Sibthorpe, Auteur ; Bela Szilagyi, Auteur ; Michele Vallisneri, Auteur ; Pascal Willis , Auteur Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : pp 469 - 489 Note générale : bibliographie
The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] données DORIS
[Termes IGN] données GNSS
[Termes IGN] données ITGB
[Termes IGN] données TLS (télémétrie)
[Termes IGN] filtre de Kalman
[Termes IGN] horloge atomique
[Termes IGN] horloge du satellite
[Termes IGN] logiciel d'orbitographie
[Termes IGN] positionnement ponctuel précis
[Termes IGN] série temporelle
[Termes IGN] temps réel
[Termes IGN] traitement de données GNSSRésumé : (auteur) GipsyX/RTGx is the Jet Propulsion Laboratory’s (JPL) next generation software package for positioning, navigation, timing, and Earth science using measurements from three geodetic techniques: Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS); with Very Long Baseline Interferometry (VLBI) under development. The software facilitates combined estimation of geodetic and geophysical parameters using a Kalman filter approach on real or simulated data in both post-processing and in real-time. The estimated parameters include station coordinates and velocities, satellite orbits and clocks, Earth orientation, ionospheric and tropospheric delays. The software is also capable of full realization of a dynamic terrestrial reference through analysis and combination of time series of ground station coordinates.
Applying lessons learned from its predecessors, GIPSY-OASIS and Real Time GIPSY (RTG), GipsyX/RTGx was re-designed from the ground up to offer improved precision, accuracy, usability, and operational flexibility. We present some key aspects of its new architecture, and describe some of its major applications, including Real-time orbit determination and ephemeris predictions in the U.S. Air Force Next Generation GPS Operational Control Segment (OCX), as well as in JPL’s Global Differential GPS (GDGPS) System, supporting User Range Error (URE) of
5 cm RMS; precision post-processing GNSS orbit determination, including JPL’s contributions to the International GNSS Service (IGS) with URE in the 2 cm RMS range; Precise point positioning (PPP) with ambiguity resolution, both statically and kinematically, for geodetic applications with 2 mm horizontal, and 6.5 mm vertical repeatability for static positioning; Operational orbit and clock determination for Low Earth Orbiting (LEO) satellites, such as NASA’s Gravity Recovery and Climate Experiment (GRACE) mission with GRACE relative clock alignment at the 20 ps level; calibration of radio occultation data from LEO satellites for weather forecasting and climate studies; Satellite Laser Ranging (SLR) to GNSS and LEO satellites, DORIS-based and multi-technique orbit determination for LEO; production of terrestrial reference frames and Earth rotation parameters in support of JPL’s contribution to the International Terrestrial Reference Frame (ITRF).Numéro de notice : A2020-575 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : INFORMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2020.04.015 Date de publication en ligne : 22/04/2020 En ligne : https://doi.org/10.1016/j.asr.2020.04.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96369
in Advances in space research > vol 66 n° 3 (1 August 2020) . - pp 469 - 489[article]Performance of BDS triple-frequency positioning based on the modified TCAR method / Yijun Tian in Survey review, vol 52 n° 374 (August 2020)
[article]
Titre : Performance of BDS triple-frequency positioning based on the modified TCAR method Type de document : Article/Communication Auteurs : Yijun Tian, Auteur ; Lifen Sui, Auteur ; Dongqing Zhao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 415 - 422 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] compensation Lambda
[Termes IGN] filtre de Kalman
[Termes IGN] positionnement par BeiDou
[Termes IGN] précision du positionnement
[Termes IGN] résolution d'ambiguïté
[Termes IGN] retard ionosphèrique
[Termes IGN] triple différenceRésumé : (auteur) A modified TCAR method to improve the NL ambiguity resolution over medium-long baseline is presented. The estimated DD ionospheric delay derived from the Kalman-filter floating solution is adopted to modify the floating NL ambiguities. Modified by the smooth DD ionospheric delay, the NL ambiguity residuals are mostly within 0.5 cycles over medium-long baselines, showing a significant improvement in contrast to the classical TCAR method. The positioning performances of the modified method are even better than the LAMBDA method over 72 and 634 km baselines. As the ambiguity can be correctly fixed just after several epochs, high-precision positioning can be achieved in a very short time. Numéro de notice : A2020-517 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1627507 Date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/00396265.2019.1627507 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95677
in Survey review > vol 52 n° 374 (August 2020) . - pp 415 - 422[article]A robust total Kalman filter algorithm with numerical evaluation / Sida Li in Survey review, vol 52 n° 373 (July 2020)
[article]
Titre : A robust total Kalman filter algorithm with numerical evaluation Type de document : Article/Communication Auteurs : Sida Li, Auteur ; Lintao Liu, Auteur ; Zhiping Liu, Auteur ; Guocheng Wang, Auteur Année de publication : 2020 Article en page(s) : pp 309 - 316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] filtre de Kalman
[Termes IGN] matrice
[Termes IGN] méthode des moindres carrés
[Termes IGN] méthode robuste
[Termes IGN] modèle d'erreur
[Termes IGN] précision du positionnement
[Termes IGN] valeur aberranteRésumé : (auteur) In this study, the observation model of Kalman Filter (KF) is extended to an errors-in-variables (EIV) model because the observations may exist in the design matrix of the observation model. Then, a robust total least squares method (RTLS) is introduced into the KF, and a robust total Kalman filter (RTKF) algorithm is derived. The RTKF is a simple, flexible and effective algorithm. It is simple because its computational formulae are similar to the computational formulae of a standard KF; it is flexible because it can be used in a wide range of applications; it is effective because the influence of outliers on estimated results is weakened. Finally, the simulated example of the indoor location and the empirical example of pseudorange differential positioning are used to demonstrate the performance of the RTKF algorithm. The results prove the validity, robustness, and reliability of the RTKF in dealing with the outliers that exist in both observation vector and design matrix of the EIV model. Furthermore, the results of the empirical example show that the RTKF improves the precision of a pseudorange differential positioning compared with KF and robust Kalman filter (RKF) algorithms regardless the observation model has outliers or not in this empirical example. Numéro de notice : A2020-457 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1563392 Date de publication en ligne : 08/01/2019 En ligne : https://doi.org/10.1080/00396265.2018.1563392 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95556
in Survey review > vol 52 n° 373 (July 2020) . - pp 309 - 316[article]Semi-automatic identification of submarine pipelines with synthetic aperture sonar Images / Victor Hugo Fernandes in Marine geodesy, Vol 43 n° 4 (July 2020)
[article]
Titre : Semi-automatic identification of submarine pipelines with synthetic aperture sonar Images Type de document : Article/Communication Auteurs : Victor Hugo Fernandes, Auteur ; Nilcilene Das Graças Medeiros, Auteur ; Dalto Domingues Rodrigues, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 376 - 395 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] canalisation
[Termes IGN] détection de contours
[Termes IGN] filtrage du bruit
[Termes IGN] scène sous-marine
[Termes IGN] sonarRésumé : (Auteur) Synthetic Aperture Sonar (SAS) is a sensor that was designed for hydrographic survey of the seabed. It detects small targets, enabling high geometric resolution images. However, the images generated by SAS are susceptible to speckle noise, which makes digital processing difficult, since the noises are confused with the targets of interest. The goal of this study was to develop a semi-automatic routine for SAS image processing to verify the structural integrity of submarine pipelines. The method presented incorporates four stages: pre-processing to reduce noise and highlight the targets of interest; extraction of features aiming to recognize features related to the pipelines; post-processing to reduce the fragmentation generated during feature extraction; validation to quantify the results from the reference images to estimate the performance of the proposed methodology. The results showed that more than 80% of the submarine pipelines were mapped in the semi-automatic mode, which considerably reduced the time needed to manually identify a large number of pipelines operating on offshore oilfields. Numéro de notice : A2020-248 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2020.1755916 Date de publication en ligne : 25/04/2020 En ligne : https://doi.org/10.1080/01490419.2020.1755916 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95362
in Marine geodesy > Vol 43 n° 4 (July 2020) . - pp 376 - 395[article]Impact of temperature stabilization on the strapdown airborne gravimetry: a case study in Central Turkey / Mehmet Simav in Journal of geodesy, vol 94 n°4 (April 2020)PermalinkMultiscale Intensity Propagation to Remove Multiplicative Stripe Noise From Remote Sensing Images / Hao Cui in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)PermalinkPerformance of real-time undifferenced precise positioning assisted by remote IGS multi-GNSS stations / Zhiqiang Liu in GPS solutions, vol 24 n° 2 (April 2020)PermalinkA Single Model CNN for Hyperspectral Image Denoising / Alessandro Maffei in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)PermalinkWavelet-adaptive neural subtractive clustering fuzzy inference system to enhance low-cost and high-speed INS/GPS navigation system / Elahe S. Abdolkarimi in GPS solutions, vol 24 n° 2 (April 2020)PermalinkWavelet and non-parametric statistical based approach for long term land cover trend analysis using time series EVI data / Niraj Priyadarshi in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkEdge-reinforced convolutional neural network for road detection in very-high-resolution remote sensing imagery / Xiaoyan Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 3 (March 2020)PermalinkEvaluation of the high-rate GNSS-PPP method for vertical structural motion / Mosbeh R. Kaloop in Survey review, vol 52 n° 371 (March 2020)PermalinkPoststack seismic data denoising based on 3-D convolutional neural network / Dawei Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkA sequential Monte Carlo framework for noise filtering in InSAR time series / Mehdi Khaki in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)Permalink