{"id":1719,"date":"2024-05-29T04:34:18","date_gmt":"2024-05-29T04:34:18","guid":{"rendered":"https:\/\/sarai.igme.es\/?p=1719"},"modified":"2024-05-29T04:34:42","modified_gmt":"2024-05-29T04:34:42","slug":"presentacion-del-poster-automated-classification-of-ground-deformation-processes-in-spain-a-machine-learning-approach-using-a-novel-national-insar-based-database-en-la-egu-2024","status":"publish","type":"post","link":"https:\/\/sarai.igme.es\/index.php\/presentacion-del-poster-automated-classification-of-ground-deformation-processes-in-spain-a-machine-learning-approach-using-a-novel-national-insar-based-database-en-la-egu-2024\/","title":{"rendered":"Presentaci\u00f3n del poster \u201cAutomated classification of ground deformation processes in Spain: a machine learning approach using a novel national InSAR-based database\u201d en la EGU 2024"},"content":{"rendered":"\n<figure class=\"wp-block-image aligncenter size-large\"><img decoding=\"async\" width=\"1024\" height=\"771\" src=\"https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-1024x771.jpg\" alt=\"Jhonatan Rivera junto a su p\u00f3ster en la EGU 2024\" class=\"wp-image-1720\" srcset=\"https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-1024x771.jpg 1024w, https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-300x226.jpg 300w, https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-150x113.jpg 150w, https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-768x578.jpg 768w, https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-1536x1157.jpg 1536w, https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-2048x1542.jpg 2048w, https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-500x376.jpg 500w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Jhonatan Rivera junto a su p\u00f3ster en la EGU 2024.<\/figcaption><\/figure>\n\n\n\n<p>El d\u00eda 18 de abril, Jhonatan Rivera Rivera present\u00f3 en la sesi\u00f3n NH6.1 de la EGU2024 su contribuci\u00f3n cient\u00edfica \u201cInterferometric Synthetic Aperture Radar to assess the impacts of ground deformation in local, regional and national studies\u201d, realizada en el marco del proyecto SARAI. En este trabajo, aplicamos algoritmos de Machine Learning (ML) para la clasificaci\u00f3n de procesos de deformaci\u00f3n del terreno, a partir de MOVESAR: una base de datos nacional basada en SAR, integrando covariables geol\u00f3gicas, geot\u00e9cnicas, hidrol\u00f3gicas, morfom\u00e9tricas y de cobertura y uso del suelo.<\/p>\n\n\n\n<p>La base de datos MOVESAR recopila MP\u2019s de procesados realizados por el Instituto Geol\u00f3gico y Minero de Espa\u00f1a (IGME), el Centro Tecnol\u00f3gico de Telecomunicaciones de Catalu\u00f1a (CTTC) y el European Ground Motion Service (EGM). Espacialmente MOVESAR contiene MP\u00b4s de Arcos, Huelva, Cobre las Cruces, Granada, Lorca, Murcia, Madrid, Barcelona, Valle de Tena, Asturias, Albu\u00f1uelas, Rules, Sierra Nevada, La Uni\u00f3n y Suria. Los MP\u2019s del EGMS \u00fanicamente se utilizaron para validar los algoritmos de Machine learning utilizados (random forest y catboost). Los resultados indican que las t\u00e9cnicas de filtrado de MP\u2019s ruidosos (threshold velocity filtering technique \u201cTVF\u201d), balanceo de clases (Cost Sensitive Learning \u201cCSL\u201d) y reducci\u00f3n de caracter\u00edsticas (Feature Importance \u201cFI\u201d), mejora la interpretabilidad, eficiencia y precisi\u00f3n de los modelos.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>El d\u00eda 18 de abril, Jhonatan Rivera Rivera present\u00f3 en la sesi\u00f3n NH6.1 de la EGU2024 su contribuci\u00f3n cient\u00edfica.<br \/>\nEn este trabajo, aplicamos algoritmos de Machine Learning (ML) para la clasificaci\u00f3n de procesos de deformaci\u00f3n del terreno.<\/p>\n","protected":false},"author":1,"featured_media":1720,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[15],"tags":[207,179,177,175],"class_list":["post-1719","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-noticia","tag-egu24","tag-jhonatan-rivera","tag-poster","tag-presentacion"],"featured_image_src":"https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-scaled.jpg","author_info":{"display_name":"saraiadm","author_link":"https:\/\/sarai.igme.es\/index.php\/author\/saraiadm\/"},"uagb_featured_image_src":{"full":["https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-scaled.jpg",2050,1544,false],"thumbnail":["https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-150x113.jpg",150,113,true],"medium":["https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-300x226.jpg",300,226,true],"medium_large":["https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-768x578.jpg",768,578,true],"large":["https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-1024x771.jpg",1024,771,true],"1536x1536":["https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-1536x1157.jpg",1536,1157,true],"2048x2048":["https:\/\/sarai.igme.es\/wp-content\/uploads\/EGU2024-Jhonatan_Rivera-2048x1542.jpg",2048,1542,true]},"uagb_author_info":{"display_name":"saraiadm","author_link":"https:\/\/sarai.igme.es\/index.php\/author\/saraiadm\/"},"uagb_comment_info":0,"uagb_excerpt":"El d\u00eda 18 de abril, Jhonatan Rivera Rivera present\u00f3 en la sesi\u00f3n NH6.1 de la EGU2024 su contribuci\u00f3n cient\u00edfica. En este trabajo, aplicamos algoritmos de Machine Learning (ML) para la clasificaci\u00f3n de procesos de deformaci\u00f3n del terreno.","_links":{"self":[{"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/posts\/1719","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/comments?post=1719"}],"version-history":[{"count":2,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/posts\/1719\/revisions"}],"predecessor-version":[{"id":1722,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/posts\/1719\/revisions\/1722"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/media\/1720"}],"wp:attachment":[{"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/media?parent=1719"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/categories?post=1719"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/tags?post=1719"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}