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An improved computerized ionospheric tomography model fusing 3-D multisource ionospheric data enabled quantifying the evolution of magnetic storm / Jian Kong in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 5 (May 2021) . - pp 3725 - 3736 Titre : An improved computerized ionospheric tomography model fusing 3-D multisource ionospheric data enabled quantifying the evolution of magnetic storm Type de document : Article/Communication Auteurs : Jian Kong, Auteur ; Lulu Shan, Auteur ; Chen Zhou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3725 - 3736 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] données GNSS [Termes IGN] erreur absolue [Termes IGN] filtre de Kalman [Termes IGN] fusion de données multisource [Termes IGN] modèle ionosphérique [Termes IGN] modèle stochastique [Termes IGN] perturbation ionosphérique [Termes IGN] tempête magnétique [Termes IGN] teneur totale en électrons [Termes IGN] tomographie Résumé : (auteur) Global Navigation Satellite System (GNSS) ionospheric tomography is a typical ill-posed problem. Joint inversion with external observation data is one of the effective ways to mitigate the problem. In this article, by fusing 3-D multisource ionospheric data, and improving the stochastic model, an improved GNSS tomographic algorithm MFCIT [computerized ionospheric tomography (CIT) using mapping function] is presented. The accuracy of the algorithm is validated by selected data under different geomagnetic and solar conditions acquired in Europe. The results show that the estimated, statistically significant uncertainty for each of the layers is about 0.50–3.0TECU, with the largest absolute error within 6.0TECU. The advantage of the MFCIT is that it is based on the Kalman filter, which enables efficient near real-time 3-D monitoring of ionosphere. The temporal resolution can reach ~1 min level. Here, we apply the ionospheric tomography inversion to the magnetic storm on January 7, 2015, in the European region, and quantified the evolution of the storm. The results show that the difference of the core region between the MFCIT and CODE GIM is less than 1TECU. More importantly, during the initial phase of the storm, when the ionospheric disturbance is not evident in the single layer CODE GIM model, the MFCIT shows obvious positive disturbances in the upper ionosphere, although there is no disturbance in the F2 layer. The MFCIT further tracks the evolution of the magnetic storm that the ionospheric disturbance expands from the upper to the lower ionosphere layers, and at UT12:00, the disturbance continues to spread to the F2 layer. Numéro de notice : A2021-396 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3022949 Date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3022949 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97686 [article]

A topology-preserving polygon rasterization algorithm / Chen Zhou in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 6 (November 2018) . - pp 495 - 509 Titre : A topology-preserving polygon rasterization algorithm Type de document : Article/Communication Auteurs : Chen Zhou, Auteur ; Dingmou Li, Auteur ; Ningchuan Xiao, Auteur ; Zhenjie Chen, Auteur ; Xiang Li, Auteur ; Manchun Li, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 509 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données vectorielles [Termes IGN] polygone [Termes IGN] rastérisation [Termes IGN] relation topologique [Termes IGN] traitement de données localisées Résumé : (Auteur) Conventional algorithms for polygon rasterization are typically designed to maintain non-topological characteristics. Consequently, topological relationships, such as the adjacency between polygons, may also be lost or altered, creating topological errors. This paper proposes a topology-preserving polygon rasterization algorithm to avoid topological errors. Four types of topological error may occur during polygon rasterization. The algorithm starts from an initial polygon rasterization and uses a set of preserving strategies to increase topological accuracy. The count of the four types of error measures the topological errors of the conversion. Topological accuracy is summarized as 1 minus the ratio of actual topological errors to the total number of possible error cases. When applied to a land-use dataset with a data volume of 128 MB, 127,836 polygons, and extending 1352 km2, the algorithm achieves a topological accuracy of more than 99% when raster cell size is 30 m or smaller (100% for 5 and 10 m). The effects of cell size, polygon shape, and number of iterations on topological accuracy are also examined. Numéro de notice : A2018-473 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1401488 Date de publication en ligne : 21/11/2017 En ligne : https://doi.org/10.1080/15230406.2017.1401488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91256 [article]

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A parallel scheme for large-scale polygon rasterization on CUDA-enabled GPUs / Chen Zhou in Transactions in GIS, vol 21 n° 3 (June 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 3 (June 2017) . - pp 608 – 631 Titre : A parallel scheme for large-scale polygon rasterization on CUDA-enabled GPUs Type de document : Article/Communication Auteurs : Chen Zhou, Auteur ; Zhenjie Chen, Auteur ; Yuzhe Pian, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 608 – 631 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données massives [Termes IGN] maillage [Termes IGN] polygone [Termes IGN] processeur [Termes IGN] processeur graphique [Termes IGN] rastérisation [Termes IGN] temps [Termes IGN] traitement parallèle Résumé : (Auteur) This research develops a parallel scheme to adopt multiple graphics processing units (GPUs) to accelerate large-scale polygon rasterization. Three new parallel strategies are proposed. First, a decomposition strategy considering the calculation complexity of polygons and limited GPU memory is developed to achieve balanced workloads among multiple GPUs. Second, a parallel CPU/GPU scheduling strategy is proposed to conceal the data read/write times. The CPU is engaged with data reads/writes while the GPU rasterizes the polygons in parallel. This strategy can save considerable time spent in reading and writing, further improving the parallel efficiency. Third, a strategy for utilizing the GPU's internal memory and cache is proposed to reduce the time required to access the data. The parallel boundary algebra filling (BAF) algorithm is implemented using the programming models of compute unified device architecture (CUDA), message passing interface (MPI), and open multi-processing (OpenMP). Experimental results confirm that the implemented parallel algorithm delivers apparent acceleration when a massive dataset is addressed (50.32 GB with approximately 1.3 × 108 polygons), reducing conversion time from 25.43 to 0.69 h, and obtaining a speedup ratio of 36.91. The proposed parallel strategies outperform the conventional method and can be effectively extended to a CPU-based environment. Numéro de notice : A2017-626 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12213 En ligne : http://dx.doi.org/10.1111/tgis.12213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86941 [article]