A Data-Driven Hybrid Random Forest and IMDPA Approach for Mapping Soil Degradation in Iranian Arid Lands

A Data-Driven Hybrid Random Forest and IMDPA Approach for Mapping Soil Degradation in Iranian Arid Lands | 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 A Data-Driven Hybrid Random Forest and IMDPA Approach for Mapping Soil Degradation in Iranian Arid Lands Hassan Fathizad This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8313631/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Apr, 2026 Read the published version in Environmental Systems Research → Version 1 posted 23 You are reading this latest preprint version Abstract In dry regions of Iran, it would be important to quantify the processes involved in desertification in the management of the land. This paper illustrates a combination of hybrid framework of a Random Forest (RF) model and the Iranian Model of Desertification Potential Assessment (IMDPA) to go beyond the assessment of a single point in time and to model the spatiotemporal interactions between soil degradation and other processes in the Yazd-Ardakan plain. RF model accurately forecasted the important indicators of degradation such as EC (R 2 = 0.73), SAR (R 2 = 0.76), and the Soil Quality Index (SQI) (R 2 = 0.77) using 201 soil samples (2016) and multi-temporal Landsat (1986–2016). The variable importance analysis established that two process types (natural hydrological processes) (groundwater salinity) and (anthropogenic pressures) (proximity to mines, roads and urban areas) are the primary causes of degradation, respectively, in soil EC and SQI and heavy metals respectively. We quantitatively measured the acceleration of the process of desertification by rebuilding historical soil maps within 30 years of time. The findings indicate that there is a drastic growth (more than 60-fold, between ~ 30 ha and ~ 1800 ha) of the Very High desertification category, which is spatially clustered around the Yazd-Ardakan industrial belt. The given direct, data-based connection between human activity and the accelerating process of degradation offers an innovative, quantitative instrument of the accurate monitoring and specific management of soil resources in the vulnerable arid environments. Desertification Soil Quality Random Forest Model Uncertainty Analysis IMDPA Model Yazd-Ardakan Plain Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Published Journal Publication published 19 Apr, 2026 Read the published version in Environmental Systems Research → Version 1 posted Editorial decision: Revision requested 26 Dec, 2025 Reviews received at journal 26 Dec, 2025 Reviews received at journal 23 Dec, 2025 Reviews received at journal 22 Dec, 2025 Reviews received at journal 17 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviews received at journal 14 Dec, 2025 Reviewers agreed at journal 13 Dec, 2025 Reviewers agreed at journal 13 Dec, 2025 Reviewers agreed at journal 13 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers agreed at journal 12 Dec, 2025 Reviewers invited by journal 12 Dec, 2025 Editor assigned by journal 12 Dec, 2025 Submission checks completed at journal 11 Dec, 2025 First submitted to journal 09 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-8313631","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":560797656,"identity":"d5507b3d-5f3b-4083-bbe9-b29aad55aae1","order_by":0,"name":"Hassan 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Lands","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-systems-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ensr","sideBox":"Learn more about [Environmental Systems Research](http://environmentalsystemsresearch.springeropen.com)","snPcode":"40068","submissionUrl":"https://submission.nature.com/new-submission/40068/3","title":"Environmental Systems Research","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Desertification, Soil Quality, Random Forest Model, Uncertainty Analysis, IMDPA Model, Yazd-Ardakan Plain","lastPublishedDoi":"10.21203/rs.3.rs-8313631/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8313631/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn dry regions of Iran, it would be important to quantify the processes involved in desertification in the management of the land. This paper illustrates a combination of hybrid framework of a Random Forest (RF) model and the Iranian Model of Desertification Potential Assessment (IMDPA) to go beyond the assessment of a single point in time and to model the spatiotemporal interactions between soil degradation and other processes in the Yazd-Ardakan plain. RF model accurately forecasted the important indicators of degradation such as EC (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.73), SAR (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.76), and the Soil Quality Index (SQI) (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.77) using 201 soil samples (2016) and multi-temporal Landsat (1986\u0026ndash;2016). The variable importance analysis established that two process types (natural hydrological processes) (groundwater salinity) and (anthropogenic pressures) (proximity to mines, roads and urban areas) are the primary causes of degradation, respectively, in soil EC and SQI and heavy metals respectively. We quantitatively measured the acceleration of the process of desertification by rebuilding historical soil maps within 30 years of time. The findings indicate that there is a drastic growth (more than 60-fold, between ~\u0026thinsp;30 ha and ~\u0026thinsp;1800 ha) of the Very High desertification category, which is spatially clustered around the Yazd-Ardakan industrial belt. The given direct, data-based connection between human activity and the accelerating process of degradation offers an innovative, quantitative instrument of the accurate monitoring and specific management of soil resources in the vulnerable arid environments.\u003c/p\u003e","manuscriptTitle":"A Data-Driven Hybrid Random Forest and IMDPA Approach for Mapping Soil Degradation in Iranian Arid Lands","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 19:37:52","doi":"10.21203/rs.3.rs-8313631/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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