Détail de l'auteur
Auteur Hyung-Sup Jung |
Documents disponibles écrits par cet auteur (8)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesLandslide susceptibility mapping using Naïve Bayes and Bayesian network models in Umyeonsan, Korea / Sunmin Lee in Geocarto international, vol 35 n° 15 ([01/11/2020])
Titre : Landslide susceptibility mapping using Naïve Bayes and Bayesian network models in Umyeonsan, Korea Type de document : Article/Communication Auteurs : Sunmin Lee, Auteur ; Moung-Jin Lee, Auteur ; Hyung-Sup Jung, Auteur ; Saro Lee, Auteur Année de publication : 2020 Article en page(s) : pp 1665 - 1679 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] carte de la végétation
[Termes IGN] carte forestière
[Termes IGN] carte topographique
[Termes IGN] cartographie des risques
[Termes IGN] catastrophe naturelle
[Termes IGN] Corée du sud
[Termes IGN] effondrement de terrain
[Termes IGN] modèle stochastique
[Termes IGN] réseau bayesien
[Termes IGN] système d'information géographique
[Termes IGN] zone urbaineRésumé : (auteur) In recent years, machine learning techniques have been increasingly applied to the assessment of various natural disasters, including landslides and floods. Machine learning techniques can be used to make predictions based on the relationships among events and their influencing factors. In this study, a machine learning approaches were applied based on landslide location data in a geographic information system environment. Topographic maps were used to determine the topographical factors. Additional soil and forest parameters were examined using information obtained from soil and forest maps. A total of 17 factors affecting landslide occurrence were selected and a spatial database was constructed. Naïve Bayes and Bayesian network models were applied to predict landslides based on selected risk factors. The two models showed accuracies of 78.3 and 79.8%, respectively. The results of this study provide a useful foundation for effective strategies to prevent and manage landslides in urban areas. Numéro de notice : A2020-658 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1585482 Date de publication en ligne : 16/04/2019 En ligne : https://doi.org/10.1080/10106049.2019.1585482 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96130
in Geocarto international > vol 35 n° 15 [01/11/2020] . - pp 1665 - 1679[article]Machine learning techniques applied to geoscience information system and remote sensing / Saro Lee (2019)
Titre : Machine learning techniques applied to geoscience information system and remote sensing Type de document : Monographie Auteurs : Saro Lee, Éditeur scientifique ; Hyung-Sup Jung, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 438 p. ISBN/ISSN/EAN : ISBN 978-3-03921-215-6 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] géosciences
[Termes IGN] réseau neuronal convolutif
[Termes IGN] système d'information géographique
[Termes IGN] télédétection
[Termes IGN] traitement de données localiséesRésumé : (éditeur) As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing. Numéro de notice : 25831 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif En ligne : https://www.mdpi.com/books/pdfview/book/1533 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95158
Titre : Investigation of ionospheric effects on SAR Interferometry (InSAR): A case study of Hong Kong Type de document : Article/Communication Auteurs : Wu Zhu, Auteur ; Xiao-Li Ding, Auteur ; Hyung-Sup Jung, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 564 - 576 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] coordonnées GPS
[Termes IGN] Hong-Kong
[Termes IGN] image ALOS-PALSAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] perturbation ionosphérique
[Termes IGN] teneur totale en électronsRésumé : (auteur) Synthetic Aperture Radar Interferometry (InSAR) has demonstrated its potential for high-density spatial mapping of ground displacement associated with earthquakes, volcanoes, and other geologic processes. However, this technique may be affected by the ionosphere, which can result in the distortions of Synthetic Aperture Radar (SAR) images, phases, and polarization. Moreover, ionospheric effect has become and is becoming further significant with the increasing interest in low-frequency SAR systems, limiting the further development of InSAR technique. Although some research has been carried out, thorough analysis of ionospheric influence on true SAR imagery is still limited. Based on this background, this study performs a thorough investigation of ionospheric effect on InSAR through processing L-band ALOS-1/PALSAR-1 images and dual-frequency Global Positioning System (GPS) data over Hong Kong, where the phenomenon of ionospheric irregularities often occurs. The result shows that the small-scale ionospheric irregularities can cause the azimuth pixel shifts and phase advance errors on interferograms. Meanwhile, it is found that these two effects result in the stripe-shaped features in InSAR images. The direction of the stripe-shaped effects keep approximately constant in space for our InSAR dataset. Moreover, the GPS-derived rate of total electron content change index (ROTI), an index to reflect the level of ionospheric disturbances, may be a useful indicator for predicting the ionospheric effect for SAR images. This finding can help us evaluate the quality of SAR images when considering the ionospheric effect. Numéro de notice : A2016-591 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2016.05.004 En ligne : http://dx.doi.org/10.1016/j.asr.2016.05.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81747
in Advances in space research > vol 58 n° 4 (August 2016) . - pp 564 - 576[article]
Titre : Automated bias-compensation approach for pushbroom sensor modeling using digital elevation model Type de document : Article/Communication Auteurs : Kwan-Young Oh, Auteur ; Hyung-Sup Jung, Auteur Année de publication : 2016 Article en page(s) : pp 3400 - 3409 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] compensation
[Termes IGN] image Kompsat
[Termes IGN] image SRTM
[Termes IGN] modèle numérique de terrain
[Termes IGN] modèle par fonctions rationnelles
[Termes IGN] pouvoir de résolution géométriqueRésumé : (Auteur) Bias compensation of rational polynomial coefficients (RPCs) is one of the most important preprocessing steps in high-resolution satellite image processing. It generally requires accurate ground control points (GCPs), but GCP acquisition is both time consuming and laborious. In this paper, we propose a time- and cost-efficient method for automated bias compensation of the RPC of high-resolution stereo image pairs. Two Korean Multi-purpose Satellite-2 (KOMPSAT-2) stereo image pairs acquired in Daejeon and Busan, Korea, and the Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM) with the spatial resolution of 3 arcsec (~90 m) were used for analysis. In the two study areas, 33 and 29 check points were respectively used for the performance evaluation. After bias compensation with the proposed method, the root-mean-square (RMS) errors for both of the study areas were less than 10 m, in all coordinate components, while the RMS error vectors were approximately 10 m. Although the RMS error vectors were slightly larger than the standard deviations of the residual errors of the initial ground coordinates, it would seem that they yielded acceptable values because the proposed method largely depends on the spatial resolution, the error of the SRTM DEM, the tie point selection error, and so on. Therefore, it can be concluded that the proposed method allows for the automated bias compensation of RPCs of KOMPSAT-2 images. Numéro de notice : A2016-853 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2517100 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2517100 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82990
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 6 (June 2016) . - pp 3400 - 3409[article]
Titre : Simulation of the SuperSAR multi-azimuth synthetic aperture radar imaging system for precise measurement of three-dimensional earth surface displacement Type de document : Article/Communication Auteurs : Hyung-Sup Jung, Auteur ; Zhong Lu, Auteur ; Andrew Shepherd, Auteur ; Tim Wright, Auteur Année de publication : 2015 Article en page(s) : pp 6196 - 6206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] déformation de la croute terrestre
[Termes IGN] données localisées 3D
[Termes IGN] image radar moiréeRésumé : (Auteur) The SuperSAR imaging system, a novel multi-azimuth synthetic aperture radar (SAR) system capable of detecting Earth surface deformation in three dimensions from a single satellite platform, has recently been proposed. In this paper, we investigate the feasibility of detecting precise 3-D surface displacement measurements with the SuperSAR imaging system using a point target simulation. From this simulation, we establish both a relationship between the interferometric SAR phase and the across-track displacement and a relationship between the multiple-aperture interferometry phase and the along-track displacement based on the SuperSAR imaging geometry. The theoretical uncertainties of the SuperSAR measurement are analyzed in the across- and along-track directions, and the theoretical accuracy of the 3-D displacement measurement from the SuperSAR system is also investigated according to both the decorrelation and the squint and look angles. In the case that the interferometric coherence is about 0.8 and that five effective looks are employed, the theoretical 2-D measurement precision values are about 3.67 and 6.35 mm in the across- and along-track directions, respectively, and the theoretical 3-D measurement precision values for 3-D displacement are about 4.05, 4.56, and 3.45 mm in the east, north, and up directions, respectively. The result of this study demonstrates that the SuperSAR imaging system is capable of measuring the 3-D surface displacement in all directions with subcentimeter precision. Numéro de notice : A2015-804 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2435776 Date de publication en ligne : 01/07/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2435776 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78835
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 11 (November 2015) . - pp 6196 - 6206[article]Réservation
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