Winter wheat yield index insurance design based on multi-source remote sensing and meteorological observation data

Winter wheat yield index insurance design based on multi-source remote sensing and meteorological observation data | 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 Winter wheat yield index insurance design based on multi-source remote sensing and meteorological observation data ZiYi Xue, Wang Tong, Wang Dong, Chen Yan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4044809/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract This study utilizes Sentinel-2 satellite data, remote sensing time series data MOD13Q2, and daily meteorological data from the meteorological station in Weinan City, Shaanxi Province. The aim is to accurately extract winter wheat planting areas and construct a remote sensing index system that is highly correlated with winter wheat yield. The index system covers wheat in Weinan City and includes meteorological data throughout the growing period. A multi-source fusion data prediction model for winter wheat yield is established using multiple linear regression methods to explore the relationship between multi-source data and winter wheat yield. Additionally, a comprehensive model is designed to calculate the claim thresholds and actuarial pure rates for index insurance products with an accuracy of 10 meters. The output prediction error rate of the final model is within 11%, indicating that this product can effectively reduce the basis risk of index insurance, improve the spatial accuracy of rate determination, and provide valuable insights for future index product research. remote sensing data multi-source fusion insurance product design winter wheat. Full Text Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Reject, do not transfer 23 Jun, 2024 Reviewers invited by journal 07 Apr, 2024 Editor assigned by journal 14 Mar, 2024 First submitted to journal 08 Mar, 2024 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-4044809","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":288503587,"identity":"957818c6-0213-4239-afdb-47b3528c6008","order_by":0,"name":"ZiYi Xue","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACNmbG5sc/DP7L8csfPkCcFj525jZjhgJmY8kZbAnEaZHjZ2+QZvjAnLjhBo8B0Q5rMC4wYGNsuN3z8cYbBjs53QYitDyeYcDDzDjn7GbLOQzJxmYHiNBiwGMgwcbMkLtNmofhQOI2YrRI8BgY8LAx5DwjXos0j0GCBI9EDhvRWtoMZxgcMJDgOWZsOceACL/I9x9//ODDnwP1+483P7zxpsJOjqAWFCBBbNQgayFVxygYBaNgFIwIAAAOmjv2qouBfQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0000-1741-0928","institution":"Northwest A\u0026F University","correspondingAuthor":true,"prefix":"","firstName":"ZiYi","middleName":"","lastName":"Xue","suffix":""},{"id":288503588,"identity":"8e8ff435-32c7-4b5f-a86c-8de6732c961d","order_by":1,"name":"Wang Tong","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"prefix":"","firstName":"Wang","middleName":"","lastName":"Tong","suffix":""},{"id":288503589,"identity":"5cf0a4d2-68f6-43e2-9c1a-8a380c1c86bb","order_by":2,"name":"Wang Dong","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"prefix":"","firstName":"Wang","middleName":"","lastName":"Dong","suffix":""},{"id":288503590,"identity":"f5119cd7-f296-4831-a449-dc2426b6dda0","order_by":3,"name":"Chen Yan","email":"","orcid":"","institution":"Northwest A\u0026F University","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2024-03-08 13:35:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4044809/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4044809/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54482487,"identity":"a5cd6d1b-759b-4e4f-b3f9-ba04503b85c5","added_by":"auto","created_at":"2024-04-11 08:30:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1336424,"visible":true,"origin":"","legend":"","description":"","filename":"XueZiyi.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4044809/v1_covered_de77ce08-d94f-406d-aa05-5ab34ff4155b.pdf"}],"financialInterests":"","formattedTitle":"Winter wheat yield index insurance design based on multi-source remote sensing and meteorological observation data","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"terrestrial-atmospheric-and-oceanic-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taoj","sideBox":"Learn more about [Terrestrial, Atmospheric and Oceanic Sciences](https://link.springer.com/journal/44195)","snPcode":"44195","submissionUrl":"https://submission.springernature.com/new-submission/44195/3","title":"Terrestrial, Atmospheric and Oceanic Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"remote sensing data, multi-source fusion, insurance product design, winter wheat.","lastPublishedDoi":"10.21203/rs.3.rs-4044809/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4044809/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study utilizes Sentinel-2 satellite data, remote sensing time series data MOD13Q2, and daily meteorological data from the meteorological station in Weinan City, Shaanxi Province. 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