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Landslide susceptibility mapping using Naïve Bayes and Bayesian network models in Umyeonsan, Korea / Sunmin Lee in Geocarto international, vol 35 n° 15 ([01/11/2020])  

Public [article]  inGeocarto international > vol 35 n° 15 [01/11/2020] . - pp 1665 - 1679 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 urbaine Résumé : (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 [article]

Application of fuzzy combination operators to flood vulnerability assessments in Seoul, Korea / Moung-Jin Lee in Geocarto international, vol 30 n° 9 - 10 (October - November 2015)  

Public [article]  inGeocarto international > vol 30 n° 9 - 10 (October - November 2015) . - pp 1052 - 1075 Titre : Application of fuzzy combination operators to flood vulnerability assessments in Seoul, Korea Type de document : Article/Communication Auteurs : Moung-Jin Lee, Auteur ; Jung Eun Kang, Auteur ; Geunhan Kim, Auteur Année de publication : 2015 Article en page(s) : pp 1052 - 1075 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] changement climatique [Termes IGN] classification floue [Termes IGN] évaluation des données [Termes IGN] inondation [Termes IGN] Séoul [Termes IGN] système d'information géographique [Termes IGN] zone inondable Résumé : (Auteur) The goal of this study was to apply, verify and compare fuzzy models with various fuzzy combination operators to analyze the vulnerability to flooding in Seoul, Korea, and to create flood vulnerability maps. We employed the IPCC concept of vulnerability, which comprises exposure to climate, sensitivity and the adaptive capacity, to identify factors that influence flooding. Eleven factors were compiled in a spatial database using geographical information system. The relative weight of each factor was converted into a fuzzy membership value, which was integrated to obtain a flood vulnerability index using five fuzzy combination operators (fuzzy AND, fuzzy OR, fuzzy algebraic sum, fuzzy algebraic product and fuzzy gamma). Overall, the fuzzy models were quite effective tools for flood vulnerability assessment. Of the five fuzzy combination operators, the fuzzy AND operator obtained the highest prediction accuracy of 88.68%. This study achieved better flood vulnerability assessments by employing and comparing fuzzy combination operators. Numéro de notice : A2015-629 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1027290 Date de publication en ligne : 01/04/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2015.1027290 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78112 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2015051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Spatial and temporal change in landslide hazard by future climate change scenarios using probabilistic-based frequency ratio model / Moung-Jin Lee in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

Public [article]  inGeocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 639-662 Titre : Spatial and temporal change in landslide hazard by future climate change scenarios using probabilistic-based frequency ratio model Type de document : Article/Communication Auteurs : Moung-Jin Lee, Auteur ; Song Won-Kyong, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 639-662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] base de données localisées [Termes IGN] cartographie des risques [Termes IGN] changement climatique [Termes IGN] Corée du sud [Termes IGN] effondrement de terrain [Termes IGN] risque naturel [Termes IGN] simulation Résumé : (auteur) The aims of this study were to apply, verify and compare a frequency ratio model for landslide hazards, considering future climate change and using a geographic information system in Inje, Korea. Data for the future climate change scenario (A1B), topography, soil, forest, land cover and geology were collected, processed and compiled in a spatial database. The probability of landslides in the study area in target years in the future was then calculated assuming that landslides are triggered by a daily rainfall threshold. Landslide hazard maps were developed for the two study areas, and the frequency ratio for one area was applied to the other area as a cross-check of methodological validity. Verification results for the target years in the future were 82.32–84.69%. The study results, showing landslide hazards in future years, can be used to help develop landslide management plans. Numéro de notice : A2014-420 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.826739 En ligne : https://doi.org/10.1080/10106049.2013.826739 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73957 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2014031	RAB	Revue	Centre de documentation	En réserve L003	Disponible