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Knowledge-guided consistent correlation analysis of multimode landslide monitoring data / Shuangxi Miao in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 11-12 (November - December 2017) . - pp 2255 - 2271 Titre : Knowledge-guided consistent correlation analysis of multimode landslide monitoring data Type de document : Article/Communication Auteurs : Shuangxi Miao, Auteur ; Qing Zhu, Auteur ; Bo Zhang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 2255 - 2271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] base de connaissances [Termes IGN] Chensi (Chine) [Termes IGN] corrélation [Termes IGN] données multisources [Termes IGN] effondrement de terrain [Termes IGN] regroupement de données [Termes IGN] structure géologique [Termes IGN] surveillance géologique Résumé : (Auteur) A novel method called knowledge-guided spatio-temporal consistent correlation analysis (KSTCCA) was developed to discover reliable deformation features induced by multiple factors based on multimode landslide monitoring data. Compared to conventional approaches, KSTCCA integrates both temporal and spatial correlation analysis to improve the consistency of deformation patterns and capture the spatio-temporal heterogeneities in multimode monitoring data. KSTCCA considers both the landslide deformation mechanisms and the relationships between different influential factors as knowledge. Moreover, the method extracts the morphological structures of monitoring curves based on a seven-point approach and identifies knowledge rules using the k-means clustering method. Under the guidance of prior knowledge, a spatial correlation analysis is conducted based on support vector regression, and a temporal correlation analysis of the time lag is carried out based on the morphological structure features. Finally, three kinds of typical monitoring data, including deformation, rainfall, and reservoir water level data collected in the Baishuihe landslide area, China, are used for experimental analysis to verify the validity of the proposed method. Numéro de notice : A2017-700 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1356461 En ligne : https://doi.org/10.1080/13658816.2017.1356461 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88081 [article]

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079-2017061	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-2017062	RAB	Revue	Centre de documentation	En réserve L003	Disponible