{"id":1724,"date":"2024-05-29T04:58:26","date_gmt":"2024-05-29T04:58:26","guid":{"rendered":"https:\/\/sarai.igme.es\/?p=1724"},"modified":"2024-05-29T04:58:27","modified_gmt":"2024-05-29T04:58:27","slug":"presentation-of-the-poster-automated-classification-of-ground-deformation-processes-in-spain-a-machine-learning-approach-using-a-novel-national-insar-based-database-at-egu-2024","status":"publish","type":"post","link":"https:\/\/sarai.igme.es\/index.php\/presentation-of-the-poster-automated-classification-of-ground-deformation-processes-in-spain-a-machine-learning-approach-using-a-novel-national-insar-based-database-at-egu-2024\/","title":{"rendered":"Presentation of the poster \u201cAutomated classification of ground deformation processes in Spain: a machine learning approach using a novel national InSAR-based database\u201d at 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 with his poster at EGU 2024.\" class=\"wp-image-1723\" 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 with his poster at EGU 2024.<\/figcaption><\/figure>\n\n\n\n<p>On April 18th, Jhonatan Rivera Rivera presented in the NH6.1 session of EGU2024 his scientific contribution \u201cInterferometric Synthetic Aperture Radar to assess the impacts of ground deformation in local, regional and national studies\u201d, which results are part of the SARAI project. In this work, we applied Machine Learning (ML) algorithms to classify ground deformation process, using MOVESAR: &nbsp;a national database based on SAR, integrating geological, geotechnical, hydrological, morphometric, and land cover covariates.<\/p>\n\n\n\n<p>The MOVESAR database compiles MP\u2019s from processed data carried out by the Instituto Geol\u00f3gico y Minero de Espa\u00f1a (IGME), the Centro Tecnol\u00f3gico de Telecomunicaciones de Catalu\u00f1a (CTTC), and the European Ground Motion Service (EGMS). Spatially, MOVESAR contains MPs from Arcos, Huelva, Cobre las Cruces, Granada, Lorca, Murcia, Madrid, Barcelona, Valle de Tena, Asturias, Albu\u00f1uelas, Rules, Sierra Nevada, La Uni\u00f3n, and Suria. The MPs from EGMS were only used to validate the machine learning algorithms employed (random forest and catboost). The results indicate that noise filtering techniques for MPs (threshold velocity filtering technique &#8220;TVF&#8221;), class balancing (Cost Sensitive Learning &#8220;CSL&#8221;), and feature reduction (Feature Importance &#8220;FI&#8221;) enhance the interpretability, efficiency, and accuracy of the models.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>On April 18th, Jhonatan Rivera Rivera presented in the NH6.1 session of EGU2024 his scientific contribution.<br \/>\nMachine Learning (ML) algorithms were applied to classify ground deformation process using MOVESAR.<\/p>\n","protected":false},"author":1,"featured_media":1723,"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 center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[19],"tags":[212],"class_list":["post-1724","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-presentation"],"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":"On April 18th, Jhonatan Rivera Rivera presented in the NH6.1 session of EGU2024 his scientific contribution. Machine Learning (ML) algorithms were applied to classify ground deformation process using MOVESAR.","_links":{"self":[{"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/posts\/1724","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=1724"}],"version-history":[{"count":1,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/posts\/1724\/revisions"}],"predecessor-version":[{"id":1725,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/posts\/1724\/revisions\/1725"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/media\/1723"}],"wp:attachment":[{"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/media?parent=1724"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/categories?post=1724"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sarai.igme.es\/index.php\/wp-json\/wp\/v2\/tags?post=1724"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}