An analysis of stratification in the estimation of landscape metrics at national level

An analysis of stratification in the estimation of landscape metrics at national level | 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 An analysis of stratification in the estimation of landscape metrics at national level Habib Ramezani, Göran Ståhl This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7051434/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 Monitoring landscapes at national level is essential for understanding environmental changes. However, collecting wall-to-wall data on a large scale is very expensive and time-consuming. Sampling methods are often used to address this challenge. This study investigates how stratified sampling can improve the efficiency of national landscape monitoring. Using data from Sweden’s National Inventory of Landscapes (NILS), three stratification schemes were assessed in conjunction with two sampling densities (2.5% and 5%) and two allocation methods (Neyman and optimal allocations). Simulations were used to estimate three landscape metrics—Shannon’s diversity index, forest edge length, and number of forest patches. Larger sample sizes and optimal allocation led to better estimates. We discovered that some metrics, like forest edge length and the number of forest patches, were strongly related to the forest area. This means that simple indicators like forest cover can be used in post-stratification schemes. This can offer more flexibility, especially in landscapes that change over time. In conclusion, these findings can help governments and organizations design better monitoring programs that are both scientifically robust and cost-effective. landscape pattern environmental monitoring sampling methods Figures Figure 1 Figure 2 Figure 3 Figure 4 Full Text Additional Declarations No competing interests reported. Table 1 and 2 are available in the Supplementary Files section. Supplementary Files Tabels.docx 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. 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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-7051434","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":490463637,"identity":"5e30be31-01f0-42b2-bb84-52991a2984e1","order_by":0,"name":"Habib 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3","display":"","copyAsset":false,"role":"figure","size":110728,"visible":true,"origin":"","legend":"\u003cp\u003eRelative difference between the reference and estimated values (mean of replications) for three landscape metrics, evaluated under three stratification schemes, three allocation methods, and two sample sizes.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7051434/v1/f20124b5d9adcc09f4840ce8.png"},{"id":87540852,"identity":"ea5745a4-c360-438f-b8c8-f879e36407dd","added_by":"auto","created_at":"2025-07-25 03:34:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":94230,"visible":true,"origin":"","legend":"\u003cp\u003eThecorrelations among three metrics and their relationships with forest 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