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Robust unsupervised small area change detection from SAR imagery using deep learning / Xinzheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)
[article]
Titre : Robust unsupervised small area change detection from SAR imagery using deep learning Type de document : Article/Communication Auteurs : Xinzheng Zhang, Auteur ; Hang Su, Auteur ; Ce Zhang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 79 - 94 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage profond
[Termes IGN] classification floue
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection de changement
[Termes IGN] échantillonnage
[Termes IGN] filtre de déchatoiement
[Termes IGN] image radar moirée
[Termes IGN] ondelette
[Termes IGN] regroupement de données
[Termes IGN] superpixelRésumé : (auteur) Small area change detection using synthetic aperture radar (SAR) imagery is a highly challenging task, due to speckle noise and imbalance between classes (changed and unchanged). In this paper, a robust unsupervised approach is proposed for small area change detection using deep learning techniques. First, a multi-scale superpixel reconstruction method is developed to generate a difference image (DI), which can suppress the speckle noise effectively and enhance edges by exploiting local, spatially homogeneous information. Second, a two-stage centre-constrained fuzzy c-means clustering algorithm is proposed to divide the pixels of the DI into changed, unchanged and intermediate classes with a parallel clustering strategy. Image patches belonging to the first two classes are then constructed as pseudo-label training samples, and image patches of the intermediate class are treated as testing samples. Finally, a convolutional wavelet neural network (CWNN) is designed and trained to classify testing samples into changed or unchanged classes, coupled with a deep convolutional generative adversarial network (DCGAN) to increase the number of changed class within the pseudo-label training samples. Numerical experiments on four real SAR datasets demonstrate the validity and robustness of the proposed approach, achieving up to 99.61% accuracy for small area change detection. Numéro de notice : A2021-103 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.004 Date de publication en ligne : 17/01/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96879
in ISPRS Journal of photogrammetry and remote sensing > vol 173 (March 2021) . - pp 79 - 94[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021031 SL Revue Centre de documentation Revues en salle Disponible 081-2021033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach / Bisong Hu in International journal of geographical information science IJGIS, vol 35 n° 3 (March 2021)
[article]
Titre : Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach Type de document : Article/Communication Auteurs : Bisong Hu, Auteur ; Pan Ning, Auteur ; Yi Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 466 - 489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] carte sanitaire
[Termes IGN] Chine
[Termes IGN] entropie maximale
[Termes IGN] filtre de Kalman
[Termes IGN] géostatistique
[Termes IGN] modèle dynamique
[Termes IGN] régressionRésumé : (auteur) In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotemporal mapping purposes, is proposed in a spatiotemporal disease mapping context. The proposed BME-Kalman synthesis allows BME to use information from both parametric regression modeling and KF estimation leading to enhanced knowledge bases. The BME-Kalman synthetic approach is used to study the space-time incidence mapping of the hand, foot and mouth disease (HFMD) in Shandong province (China) during the period May 1st, 2008 to March 19th, 2009. The results showed that the BME-Kalman approach exhibited very good regressive and predictive accuracies, maintained a very good performance even during low-incidence and extremely low-incidence periods, offered an improved description of hierarchical disease characteristics compared to traditional mapping techniques, and provided a clear explanation of the spatial stratified incidence heterogeneity at unsampled locations. The BME-Kalman approach is versatile and flexible so that it can be modified and adjusted according to the needs of the application. Numéro de notice : A2021-165 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1795177 Date de publication en ligne : 22/07/2021 En ligne : https://doi.org/10.1080/13658816.2020.1795177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97098
in International journal of geographical information science IJGIS > vol 35 n° 3 (March 2021) . - pp 466 - 489[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2021031 SL Revue Centre de documentation Revues en salle Disponible The Realization and evaluation of PPP ambiguity resolution with INS aiding in marine survey / Zhenqiang Du in Marine geodesy, vol 44 n° 2 (March 2021)
[article]
Titre : The Realization and evaluation of PPP ambiguity resolution with INS aiding in marine survey Type de document : Article/Communication Auteurs : Zhenqiang Du, Auteur ; Hongzhou Chai, Auteur ; Guorui Xiao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 136 - 156 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] ambiguïté entière
[Termes IGN] filtre de Kalman
[Termes IGN] fractional cycle bias
[Termes IGN] milieu marin
[Termes IGN] positionnement inertiel
[Termes IGN] positionnement ponctuel précis
[Termes IGN] précision du positionnement
[Termes IGN] qualité des données
[Termes IGN] récepteur GNSS
[Termes IGN] résolution d'ambiguïté
[Termes IGN] trajet multipleRésumé : (auteur) The tightly coupled global navigation satellite system (GNSS) precise point positioning (PPP) and inertial navigation system (INS) can provide high-precision position, velocity and attitude information. The coupled system utilizes single receiver, which is particularly suitable for the environment without reference station, such as marine survey. In the former works, the integer ambiguity resolution of PPP/INS in terrestrial environment is researched. However, the GNSS observation is severely affected by the multipath effect in marine environment. In addition, the sideslip caused by wind and sea wave also impact float ambiguity estimation, consequently introducing difficulty for PPP ambiguity fixing. Therefore, the PPP/INS tightly coupled model with fixed ambiguity is proposed for marine survey. The correction model of INS gyroscope bias in closed-loop is deduced in detail. The influence of ship motion noise and multipath in marine environment is reduced by introducing the robust factor to the Kalman filter. The feasibility of the method is verified in a real marine experiment, with a detail evaluation of the data quality and positioning accuracy. The results show that the accuracy of PPP/INS can reach centimeter level after fixing the ambiguity in marine environment. Furthermore, the precise INS-predicted position can significantly shorten the re-fixed time of PPP/INS, which proves the efficiency of the proposed approach. Numéro de notice : A2021-267 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/01490419.2020.1852986 Date de publication en ligne : 07/12/2020 En ligne : https://doi.org/10.1080/01490419.2020.1852986 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97321
in Marine geodesy > vol 44 n° 2 (March 2021) . - pp 136 - 156[article]A feature-preserving point cloud denoising algorithm for LiDAR-derived DEM construction / Chuanfa Chen in Survey review, Vol 53 n° 377 (February 2021)
[article]
Titre : A feature-preserving point cloud denoising algorithm for LiDAR-derived DEM construction Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur ; Yuan Gao, Auteur ; Yanyan Li, Auteur Année de publication : 2021 Article en page(s) : pp146 - 157 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de filtrage
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] filtrage du bruit
[Termes IGN] interpolation
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de pointsRésumé : (auteur) To attenuate positional errors of LiDAR-derived datasets for constructing digital elevation models (DEMs), a feature-preserving point denoising algorithm (F-PDA) is developed in this paper. F-PDA includes three main steps: surface normal estimation, normal filtering and point position update. Numerical tests with two simulated surfaces indicate that F-PDA is always more accurate than kriging and natural neighbour. Furthermore, F-PDA has a high effectiveness of preserving feature lines. Real-world examples of interpolating LiDAR samples demonstrate that F-PDA can best retain both prominent and subtle terrain features, while faithfully removing errors in mountainous and flat regions. Moreover, it outperforms some well-known interpolation methods. Numéro de notice : A2021-235 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1704562u Date de publication en ligne : 23/12/2019 En ligne : https://doi.org/10.1080/00396265.2019.1704562u Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97242
in Survey review > Vol 53 n° 377 (February 2021) . - pp146 - 157[article]A highly adaptable method for GNSS cycle slip detection and repair based on Kalman filter / Xianwen Yu in Survey review, Vol 53 n° 377 (February 2021)
[article]
Titre : A highly adaptable method for GNSS cycle slip detection and repair based on Kalman filter Type de document : Article/Communication Auteurs : Xianwen Yu, Auteur ; Siqi Xia, Auteur Année de publication : 2021 Article en page(s) : pp 169 - 182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] compensation Lambda
[Termes IGN] détection
[Termes IGN] double différence
[Termes IGN] filtre de Kalman
[Termes IGN] glissement de cycle
[Termes IGN] phase
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) The cycle slip detection and repair are crucial steps in the preprocessing of GNSS carrier phase observation. Currently, however, there are few cycle slip detection and repair methods that can meet the data processing needs for diverse situations. To solve this problem, a highly adaptable cycle slip detection and repair method is proposed. First, a cycle slip detection equation is established using the pseudo-range and carrier double-differenced (DD) observations; the state equation is developed based on the satellite-ground distance. Then, a Kalman filter estimation model is established by joining the two equations. Subsequently, the cycle slip can be detected and repaired. Finally, the state parameters are refined in accordance with the conditional distribution. According to the results of the example, all the simulated cycle slips are detected and repaired by the method proposed. It shows that the method can meet the data processing needs for multiple situations. Numéro de notice : A2021-195 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1756107 Date de publication en ligne : 29/04/2020 En ligne : https://doi.org/10.1080/00396265.2020.1756107 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97133
in Survey review > Vol 53 n° 377 (February 2021) . - pp 169 - 182[article]Uncertainties and errors in algorithms for elevation gradients / Dong Shi in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)PermalinkPermalinkApplication of baseline constraint Kalman filter to BeiDou precise point positioning / Xiaoguo Guan in Survey review, vol 53 n°376 (January 2021)PermalinkPermalinkBenefits from a multi-receiver architecture for GNSS RTK positioning and attitude determination / Xiao Hu (2021)PermalinkPermalinkPermalinkLearning-based representations and methods for 3D shape analysis, manipulation and reconstruction / Marie-Julie Rakotosaona (2021)PermalinkPermalinkSuivi de la déforestation à partir de données Sentinel-1 en contexte tropical / Lucile Auzeméry (2021)PermalinkPermalinkDu drone LiDAR à un nuage de points précis et exact : une chaîne de traitement LiDAR adaptée et quasi automatique / Maxime Lafleur in XYZ, n° 165 (décembre 2020)PermalinkIntegrated 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)PermalinkStereophotogrammetry for 2-D building deformation monitoring using Kalman Filter / J.O. Odumosu in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)PermalinkAcquisition of weak GPS signals using wavelet-based de-noising methods / Mohaddeseh Sharie in Survey review, vol 52 n° 375 (November 2020)PermalinkInteger-estimable GLONASS FDMA model as applied to Kalman-filter-based short- to long-baseline RTK positioning / Pengyu Hou in GPS solutions, Vol 24 n° 4 (October 2020)PermalinkA 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)PermalinkMapping 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)PermalinkGipsyX/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)PermalinkPerformance of BDS triple-frequency positioning based on the modified TCAR method / Yijun Tian in Survey review, vol 52 n° 374 (August 2020)Permalink