{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T14:13:04Z","timestamp":1773583984515,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"International Climate Initiative (IKI)","award":["20_III_108"],"award-info":[{"award-number":["20_III_108"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Amazon forests act as a global reserve for carbon, have very high biodiversity, and provide a variety of additional ecosystem services. These forests are, however, under increasing pressure, coming mainly from deforestation, despite the fact that accurate satellite monitoring is in place that produces annual deforestation maps and timely alerts. Here, we present a proof of concept for rapid deforestation monitoring that engages the global community directly in the monitoring process via crowdsourcing while subsequently leveraging the power of deep learning. Offering no tangible incentives, we were able to sustain participation from more than 5500 active contributors from 96 different nations over a 6-month period, resulting in the crowd classification of 43,108 satellite images (representing around 390,000 km2). Training a suite of AI models with results from the crowd, we achieved an accuracy greater than 90% in detecting new and existing deforestation. These findings demonstrate the potential of a crowd\u2013AI approach to rapidly detect and validate deforestation events. Our method directly engages a large, enthusiastic, and increasingly digital global community who wish to participate in the stewardship of the global environment. Coupled with existing monitoring systems, this approach could offer an additional means of verification, increasing confidence in global deforestation monitoring.<\/jats:p>","DOI":"10.3390\/rs15215204","type":"journal-article","created":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T11:51:43Z","timestamp":1698839503000},"page":"5204","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Crowd-Driven Deep Learning Tracks Amazon Deforestation"],"prefix":"10.3390","volume":"15","author":[{"given":"Ian","family":"McCallum","sequence":"first","affiliation":[{"name":"International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria"}]},{"given":"Jon","family":"Walker","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"given":"Steffen","family":"Fritz","sequence":"additional","affiliation":[{"name":"International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria"}]},{"given":"Markus","family":"Grau","sequence":"additional","affiliation":[{"name":"SAS Institute AG, 8304 Wallisellen, Switzerland"}]},{"given":"Cassie","family":"Hannan","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"given":"I-Sah","family":"Hsieh","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"given":"Deanna","family":"Lape","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"given":"Jen","family":"Mahone","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"given":"Caroline","family":"McLester","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"given":"Steve","family":"Mellgren","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"given":"Nolan","family":"Piland","sequence":"additional","affiliation":[{"name":"SAS Campus Drive, Cary, NC 27513, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2665-7065","authenticated-orcid":false,"given":"Linda","family":"See","sequence":"additional","affiliation":[{"name":"International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria"}]},{"given":"Gerhard","family":"Svolba","sequence":"additional","affiliation":[{"name":"SAS Austria, 1020 Vienna, Austria"}]},{"given":"Murray","family":"de Villiers","sequence":"additional","affiliation":[{"name":"SAS Netherlands B.V., 1272 PC Huizen, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1111\/j.1523-1739.2005.00704.x","article-title":"Biodiversity and Conservation of Plants in Brazil","volume":"19","author":"Giulietti","year":"2005","journal-title":"Conserv. 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