STTORM-CD: Low-Demand and High-Impact Disaster Monitoring Onboard Satellites Using Change Detection

STTORM-CD: Low-Demand and High-Impact Disaster Monitoring Onboard Satellites Using Change Detection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article STTORM-CD: Low-Demand and High-Impact Disaster Monitoring Onboard Satellites Using Change Detection Jonáš Herec, Jan Sedmidubský, Rado Pitoňák This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6334392/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Satellite imagery can play a crucial role in disaster management. However, without extensive costs, critical images may take hours or even days to reach end-users. This article explores change detection methods for real-time disaster identification onboard satellites as an alternative method to decrease reaction time. We introduce STTORM-CD, a framework that combines a Variational Autoencoder (VAE) with a triplet loss, customized for change detection. The triplet loss enhances the accuracy of the approach while maintaining the computational and storage efficiency of VAE, making it particularly suitable for deployment on resource-constrained onboard hardware. We also introduce a new dataset -- STTORM-CD-Floods, annotated using a custom strategy tailored for change detection. Combining them resulted in significant performance improvements, as our method outperforms existing solutions in flood detection by significant margins, while the ability to detect other types of disasters was not significantly affected. Additionally, we highlight the potential of machine learning-free approaches and introduce new evaluation metrics to address testing challenges. These advancements bring us significantly closer to deploying a universal and accurate real-time disaster detection system in operational settings. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Natural hazards Physical sciences/Engineering/Aerospace engineering Physical sciences/Mathematics and computing/Computer science Physical sciences/Mathematics and computing/Scientific data Physical sciences/Mathematics and computing/Software Full Text Additional Declarations Competing interest reported. J.S. declares no competing interests. J.H. is employed by Zaitra s.r.o., a private company focused on onboard data processing, of which R.P. is a co-founder. This article presents advancements in research and future research directions, rather than a finished product, so the potential gains from this publication are indirect and similar to those of any other researchers, such as enhancing personal or company reputation. While this publication could potentially help secure funding to continue the proposed research directions, this funding has already been secured recently (TA ČR -- TQ16000010). However, it is possible that it could assist in securing additional funding in the future. Supplementary Files SupplementaryInformation.pdf Cite Share Download PDF Status: Published Journal Publication published 04 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 30 Jul, 2025 Reviews received at journal 25 Jul, 2025 Reviewers agreed at journal 11 Jun, 2025 Reviews received at journal 20 May, 2025 Reviewers agreed at journal 12 May, 2025 Reviewers invited by journal 27 Apr, 2025 Editor assigned by journal 26 Apr, 2025 Editor invited by journal 01 Apr, 2025 Submission checks completed at journal 29 Mar, 2025 First submitted to journal 29 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6334392","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":449119601,"identity":"e17ddd54-7f3f-4aa0-a126-7a95d7727758","order_by":0,"name":"Jonáš Herec","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIie2QsQrCMBCGrwhxCXQ9UewrpBRawZepCE4OjgqiFcEu1TmP0xLoVJwVHHRxctBF4iK2RRCX1NEh35BcyP9xuQBoNH+IEZRbXNZHAPwcf1FqLFewUnlTZkgRx8psLVwnNwmHthcuzxM57cy8MDbiq+ph0bbfpHB2Wlnq7jBFbGU+JFyl8CFrAogexyHZMYL5MD4IqlachwQx59aFjPxnrpjHSsVFCsJHpASSVa5gVZcoc7uUCZvTgdNYbLDB8RQoZ7HDyNnLsbCwLk43eZ+ZaPbFVfVjdlCs7LtzoBAALOWtRqPRaApe6K5JiLzl314AAAAASUVORK5CYII=","orcid":"","institution":"Masaryk University","correspondingAuthor":true,"prefix":"","firstName":"Jonáš","middleName":"","lastName":"Herec","suffix":""},{"id":449119602,"identity":"89d4a5c8-36d2-4b5a-b0b8-fb7703fc4b88","order_by":1,"name":"Jan Sedmidubský","email":"","orcid":"","institution":"Masaryk University","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Sedmidubský","suffix":""},{"id":449119603,"identity":"5ac537bc-150a-4054-8bdd-617d8b9d25e9","order_by":2,"name":"Rado Pitoňák","email":"","orcid":"","institution":"Zaitra s.r.o.","correspondingAuthor":false,"prefix":"","firstName":"Rado","middleName":"","lastName":"Pitoňák","suffix":""}],"badges":[],"createdAt":"2025-03-29 13:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6334392/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6334392/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-32598-3","type":"published","date":"2026-02-04T15:59:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":102235699,"identity":"313f6c6b-56c5-44cc-be4a-b31bbba46d92","added_by":"auto","created_at":"2026-02-09 16:17:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1894998,"visible":true,"origin":"","legend":"","description":"","filename":"SubmissionArchive.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6334392/v1_covered_17ee0889-a9d7-4687-b73e-f021254db8d1.pdf"},{"id":82051862,"identity":"b191bc49-3f7a-4b7d-a43b-42de3d5e88aa","added_by":"auto","created_at":"2025-05-06 10:05:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":9745643,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6334392/v1/3b79a00ee398623658e1cd16.pdf"}],"financialInterests":"Competing interest reported. 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