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A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development

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Bibliographic Details
Published in:International Journal of Disaster Risk Science
Format: Online Article RSS Article
Published: 2026
Subjects:
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container_title International Journal of Disaster Risk Science
description
discipline_display Social Sciences
discipline_facet Social Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:47129
institution FRELIP
journal_source_facet International Journal of Disaster Risk Science
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development
— — — — — Management
Sociology
Social Sciences
sub_discipline_display Sociology
sub_discipline_facet Sociology
subject_display — — — — — Management
Sociology
Social Sciences
— — — — — Management
Sociology
Social Sciences
subject_facet — — — — — Management
Sociology
Social Sciences
title A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development
title_auth A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development
title_full A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development
title_fullStr A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development
title_full_unstemmed A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development
title_short A GeoAI-Driven and Decision-Oriented Methodology for Multi-Hazard Early Warning System Development
title_sort a geoai-driven and decision-oriented methodology for multi-hazard early warning system development
topic — — — — — Management
Sociology
Social Sciences
url https://link.springer.com/article/10.1007/s13753-026-00715-z