Advancing Ecosystem Monitoring with Global High-Resolution Maps of Vegetation Biophysical Properties

Advancing Ecosystem Monitoring with Global High-Resolution Maps of Vegetation Biophysical Properties | 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 Advancing Ecosystem Monitoring with Global High-Resolution Maps of Vegetation Biophysical Properties Felix Specker, Anna K. Schweiger, Jean-Baptiste Féret, Luke A. Brown, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6343364/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Human activities are rapidly transforming ecosystems worldwide, underscoring the urgent need for scalable approaches to monitor vegetation condition and recovery at scale. Public satellite missions such as Sentinel-2 have great potential for monitoring key vegetation biophysical properties because of their high spatial and temporal resolution. Radiative transfer models provide a physically based link between reflectance and vegetation structure and function, and radiative transfer-based inversion methods are well established for retrieving biophysical variables. However, existing operational products are either coarse in resolution, geographically restricted, or available only through on-demand processing workflows that require technical expertise. As a result, access to high-resolution, analysis-ready vegetation biophysical information remains limited, constraining large-scale ecosystem monitoring and restoration assessment. Here, we introduce S2BIOPHYS, the first global operational product providing precomputed, annual maps at high resolution (20 m) for three key vegetation biophysical properties: effective leaf area index (LAIe), fraction of absorbed photosynthetically active radiation (FAPAR) and fractional vegetation cover (FCOVER). To generate these products, we systematically extend radiative transfer-based inversion approaches by coupling simulation-driven model training with empirically constrained parameter optimization using an extensive in-situ reference dataset. Annual composites for 2019-2025 are derived from peak growing-season Sentinel-2 observations and include per-pixel mean values, calibrated uncertainty estimates and observation counts. Validation against more than 11,000 ground reference measurements, evaluated using spatially independent cross-validation, demonstrates strong performance relative to existing retrieval approaches. The resulting ~20 TB global dataset, together with an accompanying Python package enabling sub-annual retrievals, supports downstream applications in biodiversity assessment, ecosystem restoration monitoring, and global reporting frameworks. Conservation Biology Environmental Policy Forestry Ecosystem Monitoring Biophysical Vegetation Properties Biodiversity Restoration LAI FAPAR FCOVER PROSAIL Sentinel-2 Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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-6343364","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":436674847,"identity":"5c6c934f-647e-4018-9677-36bee6db6877","order_by":0,"name":"Felix Specker","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIie2QsQrCMBBArwSSJeiaTv5CXXTsrzQIHV1cFEQShLr4AQ7iN3RyNRLopLvQRRGcFScnrRbUxcRRMA+Ou4N7HHcADscPQgQSqixxEV2ASll9hirvXVk9kl2Bp+Il3yhESk1h0K6SjO97Mx1iQIetUaFLsZyA7vjjWNfXc80TwM3ApISMC3UExdMNSXw5zyMMFDPjltpOqAgGfLEho4uc5qFdYd59C+Ipw5knRV58wKZQXtwS6A5bxS1fZFeeINwwK0TrM+0WHxtl9ZPox2GVDA9GpSSA6NUg+/yDyDrhcDgc/8sNR1lF8beduXsAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-9398-9975","institution":"Institute of Integrative Biology, Department of Environmental Systems Science, ETH Zurich, Switzerland","correspondingAuthor":true,"prefix":"","firstName":"Felix","middleName":"","lastName":"Specker","suffix":""},{"id":436674848,"identity":"88d787df-dd69-4783-a324-9cf0c0afdb34","order_by":1,"name":"Anna K. 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