A Novel Fuzzy Forest Health Index (FFHI) for Standardizing Stochastic Forest-Smart Mining, Case Study of 30 All-Around the World Mining-Engaged Forests

A Novel Fuzzy Forest Health Index (FFHI) for Standardizing Stochastic Forest-Smart Mining, Case Study of 30 All-Around the World Mining-Engaged Forests | 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 Novel Fuzzy Forest Health Index (FFHI) for Standardizing Stochastic Forest-Smart Mining, Case Study of 30 All-Around the World Mining-Engaged Forests Hamid Sarkheil, Emad Rostamian, Shahrokh Rahbari, Razieh Lak This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4726344/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract The pressing concerns associated with climate change underscore the critical need for environmental conservation and sustainable resource management. As technological and industrial advancements continue to drive an escalating demand for materials, the extraction of which often involves mining, the imperative to explore novel methodologies for assessing and mitigating the environmental impact of such operations becomes evident. This study proposes a novel approach utilizing fuzzy logic to calculate the Forest Health Index (FHI), introducing both a Fuzzy Constructive FHI and a Fuzzy Destructive FHI index, each ranging from 0 to 100. The disparity between these indices, ranging from − 100 to 100, elucidates the overall forest health index. The study employs the Sungun copper mine as a case study, situated within the Arasbaran environmental protected area, which necessitates the application of forest-smart mining regulations and policies. To examine the impact of mining operations on forest health, remote sensing is employed to identify potential porphyry copper mineralization areas and to visualize deforestation trends at the Sungun copper mine from 2008 to 2023. Vegetation indices are utilized to estimate the Forest Health Index (FHI) through remote sensing methodologies, incorporating a combination of expert opinions and guest numbers to assess variables influencing the FHI (Forest Health Index). Results indicate that the Forest Health Index (FFHI) for Sungun is 2.1 (interpreting as rather low constructive fuzzy forest health index). For broader case studies, maximum and minimum FFHIs (Fuzzy Forest Health Index) were observed in Merian (37.92 interpreting as rather average constructive fuzzy forest health index) and Nimba Range Mineral Province (NRMP) (-25.7 interpreting as rather low/average destructive fuzzy forest health index), respectively. The outcomes emphasize the importance of implementing forest-smart mining practices to mitigate the adverse effects of mining activities on the Arasbaran forest and promote conditions conducive to forest health. It is better to diminish high road density, forest fragmentation and total deforestation along with improve forest core, forest connectivity and secondary forestry. Fuzzy Forest Health Index Forest-Smart Mining Copper Mine Full Text Additional Declarations No competing interests reported. Supplementary Files ReplytoReviewingAECommentsSubmissionIDaeff5a0a0eb143eda543bc80eec19eec.docx Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 15 Jul, 2024 Submission checks completed at journal 12 Jul, 2024 First submitted to journal 11 Jul, 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. 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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-4726344","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":327168526,"identity":"f3507f94-a04b-4f50-91b3-d47695a63525","order_by":0,"name":"Hamid Sarkheil","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIie3RMQrCMBTG8SdvfaXrE4NeIRBQB8GzSKGOOjoUyaSL4NrjBAqd6p61FDp5ABfFig4uknRzyG9Khj/5IABB8J8QAVjEnxt5JzTU2C8BkgY9V02Ol0Ztd3NSdmPgloGYaUciq7VK8oppahMYnEogYVwJpFhEh3cCkQZi57Bz2yUPJpV3r9x9ErApJpFmkpwAer0ibYuKSiauGlmI18E9LMURZftxfFzV9TVbLN3DvpnuT3sFQRAEwQ9PejAupkWkYWEAAAAASUVORK5CYII=","orcid":"","institution":"University of Tehran","correspondingAuthor":true,"prefix":"","firstName":"Hamid","middleName":"","lastName":"Sarkheil","suffix":""},{"id":327168527,"identity":"df91e035-dec7-4d44-a07a-5ae5100d0884","order_by":1,"name":"Emad Rostamian","email":"","orcid":"","institution":"University of Tehran","correspondingAuthor":false,"prefix":"","firstName":"Emad","middleName":"","lastName":"Rostamian","suffix":""},{"id":327168531,"identity":"76c12a33-68a1-4206-a2f3-81b9a27277bd","order_by":2,"name":"Shahrokh Rahbari","email":"","orcid":"","institution":"Tarbiat Modares University (TMU)","correspondingAuthor":false,"prefix":"","firstName":"Shahrokh","middleName":"","lastName":"Rahbari","suffix":""},{"id":327168533,"identity":"5f869d25-2d3f-4773-b65f-85c9d1e399b4","order_by":3,"name":"Razieh Lak","email":"","orcid":"","institution":"Geological Survey of Iran","correspondingAuthor":false,"prefix":"","firstName":"Razieh","middleName":"","lastName":"Lak","suffix":""}],"badges":[],"createdAt":"2024-07-11 19:18:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4726344/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4726344/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62017610,"identity":"b5501472-485c-411e-b426-65f1263187ca","added_by":"auto","created_at":"2024-08-08 09:01:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2403585,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4726344/v1_covered_4030e38d-c513-4aa4-a1b4-bd0ddb0541b6.pdf"},{"id":62016978,"identity":"ec25b7a1-db0c-4a37-a59e-768d6a2e7080","added_by":"auto","created_at":"2024-08-08 08:53:02","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":779709,"visible":true,"origin":"","legend":"","description":"","filename":"ReplytoReviewingAECommentsSubmissionIDaeff5a0a0eb143eda543bc80eec19eec.docx","url":"https://assets-eu.researchsquare.com/files/rs-4726344/v1/d20e954a6244d8caccb11fc4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Novel Fuzzy Forest Health Index (FFHI) for Standardizing Stochastic Forest-Smart Mining, Case Study of 30 All-Around the World Mining-Engaged Forests","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":"stochastic-environmental-research-and-risk-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"serr","sideBox":"Learn more about [Stochastic Environmental Research and Risk Assessment](https://www.springer.com/journal/477)","snPcode":"477","submissionUrl":"https://submission.nature.com/new-submission/477/3","title":"Stochastic Environmental Research and Risk Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Fuzzy Forest Health Index, Forest-Smart Mining, Copper Mine","lastPublishedDoi":"10.21203/rs.3.rs-4726344/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4726344/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe pressing concerns associated with climate change underscore the critical need for environmental conservation and sustainable resource management. As technological and industrial advancements continue to drive an escalating demand for materials, the extraction of which often involves mining, the imperative to explore novel methodologies for assessing and mitigating the environmental impact of such operations becomes evident. This study proposes a novel approach utilizing fuzzy logic to calculate the Forest Health Index (FHI), introducing both a Fuzzy Constructive FHI and a Fuzzy Destructive FHI index, each ranging from 0 to 100. The disparity between these indices, ranging from \u0026minus;\u0026thinsp;100 to 100, elucidates the overall forest health index. The study employs the Sungun copper mine as a case study, situated within the Arasbaran environmental protected area, which necessitates the application of forest-smart mining regulations and policies. To examine the impact of mining operations on forest health, remote sensing is employed to identify potential porphyry copper mineralization areas and to visualize deforestation trends at the Sungun copper mine from 2008 to 2023. Vegetation indices are utilized to estimate the Forest Health Index (FHI) through remote sensing methodologies, incorporating a combination of expert opinions and guest numbers to assess variables influencing the FHI (Forest Health Index). Results indicate that the Forest Health Index (FFHI) for Sungun is 2.1 (interpreting as rather low constructive fuzzy forest health index). For broader case studies, maximum and minimum FFHIs (Fuzzy Forest Health Index) were observed in Merian (37.92 interpreting as rather average constructive fuzzy forest health index) and Nimba Range Mineral Province (NRMP) (-25.7 interpreting as rather low/average destructive fuzzy forest health index), respectively. The outcomes emphasize the importance of implementing forest-smart mining practices to mitigate the adverse effects of mining activities on the Arasbaran forest and promote conditions conducive to forest health. It is better to diminish high road density, forest fragmentation and total deforestation along with improve forest core, forest connectivity and secondary forestry.\u003c/p\u003e","manuscriptTitle":"A Novel Fuzzy Forest Health Index (FFHI) for Standardizing Stochastic Forest-Smart Mining, Case Study of 30 All-Around the World Mining-Engaged Forests","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-08 08:52:57","doi":"10.21203/rs.3.rs-4726344/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-07-15T13:38:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-12T14:59:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Stochastic Environmental Research and Risk Assessment","date":"2024-07-11T19:17:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"stochastic-environmental-research-and-risk-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"serr","sideBox":"Learn more about [Stochastic Environmental Research and Risk Assessment](https://www.springer.com/journal/477)","snPcode":"477","submissionUrl":"https://submission.nature.com/new-submission/477/3","title":"Stochastic Environmental Research and Risk Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"68049cca-2032-4dad-8817-7db4257ccca3","owner":[],"postedDate":"August 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-08-08T08:52:57+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-08 08:52:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4726344","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4726344","identity":"rs-4726344","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}