Analysis of spatiotemporal changes and driving factors of ecological environment quality in the Mulan River Basin based on RSEI

Analysis of spatiotemporal changes and driving factors of ecological environment quality in the Mulan River Basin based on RSEI | 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 Analysis of spatiotemporal changes and driving factors of ecological environment quality in the Mulan River Basin based on RSEI Yanyu Lin, Wenjie Fu, Fanying Luo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8252420/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract In this study, Google Earth Engine (GEE) was used to calculate the Remote Sensing Ecological Index (RSEI) to evaluate the spatiotemporal evolution characteristics of ecological environment quality in Mulan River Basin from 2000 to 2020. The direct and indirect effects of climate, urbanization and biological factors on the change of ecological environment quality were analyzed by Partial Least Squares Structural Equation Model (PLS-SEM), and the spatial clustering characteristics of RSEI in the study area were analyzed. The results showed that: (1) from 2000 to 2020, RSEI showed an upward trend, with the lowest in 2000 (0.565) and the highest in 2015 (0.682); (2) The study area is dominated by areas with rising ecological environment quality, accounting for 80.50%; (3) Climate and biological factors have a positive impact on the quality of ecological environment, while urbanization has a negative impact. The driving force intensity of urbanization factors showed an upward trend from 2005 to 2015, indicating that the intensity of human activities in the study area is increasing; (4) The results of spatial autocorrelation analysis show that the H-H region is mainly distributed in the mountains in the northwest of the study area, while the L-L region is concentrated in the urban areas in the East, and the agglomeration intensity has been increasing since 2005. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences RSEI Ecological environment quality PLS-SEM driving factors Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 04 Feb, 2026 Reviewers invited by journal 02 Feb, 2026 Editor assigned by journal 04 Dec, 2025 Submission checks completed at journal 04 Dec, 2025 First submitted to journal 01 Dec, 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. 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-8252420","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":584465684,"identity":"8a8e65a9-8201-472c-b198-7422f6f78972","order_by":0,"name":"Yanyu Lin","email":"","orcid":"","institution":"Putian University","correspondingAuthor":false,"prefix":"","firstName":"Yanyu","middleName":"","lastName":"Lin","suffix":""},{"id":584465685,"identity":"6396fcc8-10fc-48c0-a5f1-d5eda9e5c8f8","order_by":1,"name":"Wenjie Fu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApUlEQVRIiWNgGAWjYBAC9gaGxAcQZgKRWngOMCQbQFSToIVNgkQtEgnPqgt/HGbgZ88xYPi5gzgtabdnJBxmkOx5Y8DYe4YILfbSQC08QC0GN3IMmBnbiLEFqKUYpMWeJC3MYFskiNYi/yBZekZaOo/EmWcFB3uJ0sJzJvFzgY21HH978sYHP4nRAtSUwAwiQcwDRGkAJpkDzESqHAWjYBSMgpEKAOyQMQX+kyP1AAAAAElFTkSuQmCC","orcid":"","institution":"Putian University","correspondingAuthor":true,"prefix":"","firstName":"Wenjie","middleName":"","lastName":"Fu","suffix":""},{"id":584465686,"identity":"19c08b25-1bb7-463c-82e1-ce57618627f1","order_by":2,"name":"Fanying Luo","email":"","orcid":"","institution":"Putian University","correspondingAuthor":false,"prefix":"","firstName":"Fanying","middleName":"","lastName":"Luo","suffix":""}],"badges":[],"createdAt":"2025-12-01 16:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8252420/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8252420/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101880853,"identity":"0b3cb1ad-d22c-456b-9a28-15ff7fb95e07","added_by":"auto","created_at":"2026-02-04 15:07:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1349927,"visible":true,"origin":"","legend":"","description":"","filename":"AnalysisofspatiotemporalchangesanddrivingfactorsofecologicalenvironmentqualityintheMulanRiverBasinbasedonRSEI.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8252420/v1_covered_feffb7ee-bb24-4cd3-a32e-dc6533dbd2a4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of spatiotemporal changes and driving factors of ecological environment quality in the Mulan River Basin based on RSEI","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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"RSEI, Ecological environment quality, PLS-SEM, driving factors","lastPublishedDoi":"10.21203/rs.3.rs-8252420/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8252420/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, Google Earth Engine (GEE) was used to calculate the Remote Sensing Ecological Index (RSEI) to evaluate the spatiotemporal evolution characteristics of ecological environment quality in Mulan River Basin from 2000 to 2020. 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