{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T05:50:39Z","timestamp":1785822639509,"version":"3.56.0"},"reference-count":47,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T00:00:00Z","timestamp":1718668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Remote sensing products are typically assessed using a single accuracy estimate for the entire map, despite significant variations in accuracy across different map areas or classes. Estimating per-pixel uncertainty is a major challenge for enhancing the usability and potential of remote sensing products. This paper introduces the dataDriven open access tool, a novel statistical design-based approach that specifically addresses this issue by estimating per-pixel uncertainty through a bootstrap resampling procedure. Leveraging Sentinel-2 remote sensing data as auxiliary information, the capabilities of the Google Earth Engine cloud computing platform, and the R programming language, dataDriven can be applied in any world region and variables of interest. In this study, the dataDriven tool was tested in the Rincine forest estate study area\u2014eastern Tuscany, Italy\u2014focusing on volume density as the variable of interest. The average volume density was 0.042, corresponding to 420 m3 per hectare. The estimated pixel errors ranged between 93 m3 and 979 m3 per hectare and were 285 m3 per hectare on average. The ability to produce error estimates for each pixel in the map is a novel aspect in the context of the current advances in remote sensing and forest monitoring and assessment. It constitutes a significant support in forest management applications and also a powerful communication tool since it informs users about areas where map estimates are unreliable, at the same time highlighting the areas where the information provided via the map is more trustworthy. In light of this, the dataDriven tool aims to support researchers and practitioners in the spatially exhaustive use of remote sensing-derived products and map validation.<\/jats:p>","DOI":"10.3390\/s24123947","type":"journal-article","created":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T08:06:06Z","timestamp":1718784366000},"page":"3947","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Per-Pixel Forest Attribute Mapping and Error Estimation: The Google Earth Engine and R dataDriven Tool"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6991-0289","authenticated-orcid":false,"given":"Saverio","family":"Francini","sequence":"first","affiliation":[{"name":"Department of Agriculture, Food, Environment and Forestry, University of Firenze, 50145 Firenze, Italy"},{"name":"NBFC, National Biodiversity Future Center, 90133 Palermo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agnese","family":"Marcelli","sequence":"additional","affiliation":[{"name":"Department for Innovation in Biological, Agro-Food, and Forest System, Tuscia University, 01100 Viterbo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0669-5726","authenticated-orcid":false,"given":"Gherardo","family":"Chirici","sequence":"additional","affiliation":[{"name":"Department of Agriculture, Food, Environment and Forestry, University of Firenze, 50145 Firenze, Italy"},{"name":"Fondazione per il Futuro delle Citt\u00e0, 50127 Firenze, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8038-9217","authenticated-orcid":false,"given":"Rosa Maria","family":"Di Biase","sequence":"additional","affiliation":[{"name":"NBFC, National Biodiversity Future Center, 90133 Palermo, Italy"},{"name":"Department of Economics and Statistics, University of Siena, 53100 Siena, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Fattorini","sequence":"additional","affiliation":[{"name":"Department of Economics and Statistics, University of Siena, 53100 Siena, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8105-0792","authenticated-orcid":false,"given":"Piermaria","family":"Corona","sequence":"additional","affiliation":[{"name":"CREA Research Centre for Forestry and Wood, 52100 Arezzo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1007\/s13280-016-0772-y","article-title":"When Is a Forest a Forest? 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