{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:33:18Z","timestamp":1762507998221,"version":"build-2065373602"},"reference-count":86,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T00:00:00Z","timestamp":1579564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Research Council grant agreement (BIODESERT)","award":["647038"],"award-info":[{"award-number":["647038"]}]},{"name":"Ram\u00f3n y Cajal Programme of the Spanish Government.","award":["RYC-2015-18136"],"award-info":[{"award-number":["RYC-2015-18136"]}]},{"name":"Spanish Ministry of Science under the project","award":["TIN2017-89517-P"],"award-info":[{"award-number":["TIN2017-89517-P"]}]},{"name":"European LIFE Project ADAPTAMED","award":["LIFE14 CCA\/ES\/000612"],"award-info":[{"award-number":["LIFE14 CCA\/ES\/000612"]}]},{"name":"NASA\u2019s Work Programme on Group on Earth Observations - Biodiversity Observation Network (GEOBON)","award":["80NSSC18K0446"],"award-info":[{"award-number":["80NSSC18K0446"]}]},{"name":"ECOPOTENTIAL, funded by European Union Horizon 2020 Research and Innovation Programme","award":["641762"],"award-info":[{"award-number":["641762"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate tree cover mapping is of paramount importance in many fields, from biodiversity conservation to carbon stock estimation, ecohydrology, erosion control, or Earth system modelling. Despite this importance, there is still uncertainty about global forest cover, particularly in drylands. Recently, the Food and Agriculture Organization of the United Nations (FAO) conducted a costly global assessment of dryland forest cover through the visual interpretation of orthoimages using the Collect Earth software, involving hundreds of operators from around the world. Our study proposes a new automatic method for estimating tree cover using artificial intelligence and free orthoimages. Our results show that our tree cover classification model, based on convolutional neural networks (CNN), is 23% more accurate than the manual visual interpretation used by FAO, reaching up to 79% overall accuracy. The smallest differences between the two methods occurred in the driest regions, but disagreement increased with the percentage of tree cover. The application of CNNs could be used to improve and reduce the cost of tree cover maps from the local to the global scale, with broad implications for research and management.<\/jats:p>","DOI":"10.3390\/rs12030343","type":"journal-article","created":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T11:25:59Z","timestamp":1579605959000},"page":"343","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Tree Cover Estimation in Global Drylands from Space Using Deep Learning"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5348-7391","authenticated-orcid":false,"given":"Emilio","family":"Guirado","sequence":"first","affiliation":[{"name":"Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18071 Granada, Spain"},{"name":"Multidisciplinary Institute for Environment Studies \u201cRam\u00f3n Margalef\u201d, University of Alicante, San Vicente del Raspeig, 03690 Alicante, Spain"},{"name":"Andalusian Center for Assessment and Monitoring of Global Change (CAESCG), University of Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8988-4540","authenticated-orcid":false,"given":"Domingo","family":"Alcaraz-Segura","sequence":"additional","affiliation":[{"name":"Andalusian Center for Assessment and Monitoring of Global Change (CAESCG), University of Almer\u00eda, 04120 Almer\u00eda, Spain"},{"name":"Department of Botany, Faculty of Science, University of Granada, 18071 Granada, Spain"},{"name":"Iecolab. Inter-University Institute for Earth System Research, University of Granada, 18006 Granada, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5123-964X","authenticated-orcid":false,"given":"Javier","family":"Cabello","sequence":"additional","affiliation":[{"name":"Andalusian Center for Assessment and Monitoring of Global Change (CAESCG), University of Almer\u00eda, 04120 Almer\u00eda, Spain"},{"name":"Department of Biology and Geology, University of Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"given":"Sergio","family":"Puertas-Ru\u00edz","sequence":"additional","affiliation":[{"name":"Department of Botany, Faculty of Science, University of Granada, 18071 Granada, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7283-312X","authenticated-orcid":false,"given":"Francisco","family":"Herrera","sequence":"additional","affiliation":[{"name":"Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18071 Granada, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4093-5356","authenticated-orcid":false,"given":"Siham","family":"Tabik","sequence":"additional","affiliation":[{"name":"Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, 18071 Granada, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,21]]},"reference":[{"key":"ref_1","first-page":"564","article-title":"Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass","volume":"29","author":"Popescu","year":"2003","journal-title":"Can. 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