UAV-Based Electromagnetic Detection of Buried Structures

UAV-Based Electromagnetic Detection of Buried Structures | 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PDF Research Article UAV-Based Electromagnetic Detection of Buried Structures Muñoz Udima This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9031325/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The detection of undocumented buried metallic structures is a relevant challenge in environmental monitoring and subsurface characterization, particularly in industrial and post-industrial areas. Recent advances in unmanned aerial vehicles (UAVs) and lightweight electromagnetic (EM) sensors have enabled non-invasive and efficient alternatives to conventional ground-based surveys. This study presents a validated UAV-based electromagnetic sensing system and a reproducible data acquisition and processing workflow for the detection of shallow buried metallic structures. A multirotor UAV equipped with an EM induction sensor was deployed over a controlled 40 × 40 m test site, acquiring apparent electrical conductivity data along a regular flight grid at low altitude. Platform-induced noise, altitude variations, and background conductivity effects were corrected through a dedicated processing chain, enabling the generation of high-resolution two-dimensional (2D) and three-dimensional (3D) conductivity anomaly models. The results reveal a coherent linear conductivity anomaly with values ranging from 9 to 15 mS/m above background levels, consistent with the presence of a shallow buried metallic pipeline at an estimated depth of approximately 1.5 m. Quantitative analysis and spatial modeling demonstrate the capability of the proposed UAV-based sensing approach to reliably detect small-scale subsurface infrastructure with minimal surface disturbance and high spatial resolution. The proposed system and workflow provide a robust sensing solution for subsurface detection, with direct applicability to environmental auditing, site characterization, and risk assessment. The methodology is scalable and compatible with complementary sensing techniques, supporting its integration into multi-sensor environmental monitoring frameworks. UAV-based sensing electromagnetic induction sensor subsurface detection buried metallic structures environmental monitoring geophysical sensing data processing workflow Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9031325","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":604614489,"identity":"0cd6a256-361f-464a-bb5c-fdac2b82dff8","order_by":0,"name":"Muñoz Udima","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYDACZgaGAzA2lMF8gIHHgCgtzDAGWwJ+LSiaIQCongePOt123ocHfuYwRPPPPn/wcEFFHYPujJxvEm8KtskzsLc/wKbF7DC7wcHebQy5M84lMxyecYaNwexG7jbJOQa3DRt4zmB1ntlhNoYDvEAtDWeYGQ7ztvGAtUjzGNxmbJDIweowkJaDf4Fa5oO1/JMAasl5BtJi3yD/HIfD2IAqgVo2gLU0GIC0sIG0JDZIMOB02GHZbRK5G88wGxzmOZbAY3bmmbEl0C/JbTw52LWcP8b88e02m9x5Zxgff+apqZMzO5788MabP7dt+9mPY3UYFEjAWYgYYcOjfhSMglEwCkYBfgAAFzNgIHzES9wAAAAASUVORK5CYII=","orcid":"","institution":"Directora del Grado Empresa y Tecnología","correspondingAuthor":true,"prefix":"","firstName":"Muñoz","middleName":"","lastName":"Udima","suffix":""}],"badges":[],"createdAt":"2026-03-04 14:23:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9031325/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9031325/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104781147,"identity":"ec2c2577-f6c0-4007-bbca-73ea23be51e0","added_by":"auto","created_at":"2026-03-17 07:54:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":406078,"visible":true,"origin":"","legend":"","description":"","filename":"UAVBasedElectromagneticDetection.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9031325/v1_covered_32b5c8c6-0ed0-4cc6-9b2a-a03f9cb76051.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"UAV-Based Electromagnetic Detection of Buried Structures","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"UAV-based sensing, electromagnetic induction sensor, subsurface detection, buried metallic structures, environmental monitoring, geophysical sensing, data processing workflow","lastPublishedDoi":"10.21203/rs.3.rs-9031325/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9031325/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe detection of undocumented buried metallic structures is a relevant challenge in environmental monitoring and subsurface characterization, particularly in industrial and post-industrial areas. Recent advances in unmanned aerial vehicles (UAVs) and lightweight electromagnetic (EM) sensors have enabled non-invasive and efficient alternatives to conventional ground-based surveys.\u003c/p\u003e \u003cp\u003eThis study presents a validated UAV-based electromagnetic sensing system and a reproducible data acquisition and processing workflow for the detection of shallow buried metallic structures. A multirotor UAV equipped with an EM induction sensor was deployed over a controlled 40 \u0026times; 40 m test site, acquiring apparent electrical conductivity data along a regular flight grid at low altitude. Platform-induced noise, altitude variations, and background conductivity effects were corrected through a dedicated processing chain, enabling the generation of high-resolution two-dimensional (2D) and three-dimensional (3D) conductivity anomaly models.\u003c/p\u003e \u003cp\u003eThe results reveal a coherent linear conductivity anomaly with values ranging from 9 to 15 mS/m above background levels, consistent with the presence of a shallow buried metallic pipeline at an estimated depth of approximately 1.5 m. Quantitative analysis and spatial modeling demonstrate the capability of the proposed UAV-based sensing approach to reliably detect small-scale subsurface infrastructure with minimal surface disturbance and high spatial resolution.\u003c/p\u003e \u003cp\u003eThe proposed system and workflow provide a robust sensing solution for subsurface detection, with direct applicability to environmental auditing, site characterization, and risk assessment. 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