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Images from medium-resolution optical satellites combined with extensive field data have allowed researchers to assess patterns of windthrow tree-mortality and to monitor forest recovery over decades of succession in different regions. Although satellites with high spatial-resolution have become available in the last decade, they have not yet been employed for the quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November 2015. Remote sensing estimates of windthrow tree-mortality were produced from Spectral Mixture Analysis and evaluated with forest inventory data (i.e., ground true) by using Generalized Linear Models. Field measured windthrow tree-mortality (3 transects and 30 subplots) crossing the entire disturbance gradient was 26.9 \u00b1 11.1% (mean \u00b1 95% CI). Although the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3%, p &lt; 0.001), Landsat 8 had the most accurate results and efficiently captured field-observed variations in windthrow tree-mortality across the entire gradient of disturbance (Sentinel 2 and WorldView 2 produced the second and third best results, respectively). As expected, mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of model fits showed the opposite pattern. We suggest that this reflects the influence of a relatively minor disturbance, such as defoliation and crown damage, and the fast growth of natural regeneration, which were not measured in the field nor can be captured by coarser resolution imagery. Our results validate the reliability of Landsat imagery for assessing plot-to-landscape patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Satellites with high spatial resolution can improve estimates of windthrow severity by allowing the quantification of crown damage and mortality of lower canopy and understory trees. However, this requires the validation of remote sensing metrics using field data at compatible scales.<\/jats:p>","DOI":"10.3390\/rs15164027","type":"journal-article","created":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T10:40:31Z","timestamp":1692009631000},"page":"4027","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8718-840X","authenticated-orcid":false,"given":"Luciano","family":"Emmert","sequence":"first","affiliation":[{"name":"Forest Management Laboratory, National Institute of Amazon Research, Manaus 69060-062, AM, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4691-2692","authenticated-orcid":false,"given":"Robinson Isaac","family":"Negr\u00f3n-Ju\u00e1rez","sequence":"additional","affiliation":[{"name":"Climate Sciences Department, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey Quintin","family":"Chambers","sequence":"additional","affiliation":[{"name":"Climate Sciences Department, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joaquim dos","family":"Santos","sequence":"additional","affiliation":[{"name":"Forest Management Laboratory, National Institute of Amazon Research, Manaus 69060-062, AM, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adriano Jos\u00e9 Nogueira","family":"Lima","sequence":"additional","affiliation":[{"name":"Forest Management Laboratory, National Institute of Amazon Research, Manaus 69060-062, AM, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan","family":"Trumbore","sequence":"additional","affiliation":[{"name":"Biogeochemical Processes Department, Max Planck Institute for Biochemistry, 07745 Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1216-2982","authenticated-orcid":false,"given":"Daniel Magnabosco","family":"Marra","sequence":"additional","affiliation":[{"name":"Biogeochemical Processes Department, Max Planck Institute for Biochemistry, 07745 Jena, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Marra, D.M., Chambers, J.Q., Higuchi, N., Trumbore, S.E., Ribeiro, G.H.P.M., Dos Santos, J., Negr\u00f3n-Ju\u00e1rez, R.I., Reu, B., and Wirth, C. 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