Right on Time: Evaluating Accuracy and Timing of Burn-Severity Assessments to Support Post-Fire Response

Right on Time: Evaluating Accuracy and Timing of Burn-Severity Assessments to Support Post-Fire Response | 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 Right on Time: Evaluating Accuracy and Timing of Burn-Severity Assessments to Support Post-Fire Response Kyle C Rodman, Ellen Whitman, Alexander A Howe, Alexander Spannuth, and 35 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9557776/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 Effective post-fire management – including flood mitigation, revegetation, and salvage logging – depends on timely and reliable burn-severity assessments that characterize impacts to vegetation and soils. These assessments are typically derived from satellite-based change detection but can be delayed or degraded by aerosols (i.e., dust or smoke), clouds, and snow. Across 9,129 large fires (≥404 ha) in Canada and the United States from 2016–2024, we quantified sources of post-fire data obstruction and evaluated observational latency – the time to acquire the first usable scene – for four freely available, moderate-resolution datasets: Landsat, Sentinel‑1, Sentinel‑2, and the Harmonized Landsat Sentinel-2 (HLS) product. For 77 fires with field-derived burn-severity indicators, we also assessed mapping accuracy in forested ecosystems and quantified variation over time. Cloud cover was the dominant cause of data obstruction, especially in mesic and coastal regions. Sentinel‑1 exhibited the shortest observational latency (median = 4 days), followed by HLS (7 days), Sentinel‑2 (10 days), and Landsat (17 days). Composite imagery from Sentinel‑1 (89.6%) and HLS (82.8%) achieved near‑complete coverage of most fires within one month, substantially better than Sentinel‑2 (70.5%) and Landsat (56.1%). HLS, Landsat, and Sentinel‑2 produced maps of stand-replacing disturbance that exceeded 80% accuracy within one month of fire, only slightly lower than maps generated after the following growing season. Sentinel‑1 had lower initial accuracy (<70%), but outperformed other sensors in winter and improved over time. High‑frequency multispectral datasets such as HLS facilitate timely, accurate post‑fire assessments, informing critical management activities that can prevent the loss of human life and minimize economic losses following fire. Emergency Burn-Severity Assessment Initial Burn-Severity Assessment Post-Fire Remote Sensing Harmonized Landsat Sentinel-2 C-band Synthetic Aperture Radar Data Obstruction Full Text Additional Declarations No competing interests reported. Supplementary Files RodmanEtAlSI.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 13 May, 2026 Reviewers invited by journal 07 May, 2026 Editor assigned by journal 30 Apr, 2026 Submission checks completed at journal 30 Apr, 2026 First submitted to journal 28 Apr, 2026 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. 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