{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:41:20Z","timestamp":1760146880048,"version":"build-2065373602"},"reference-count":162,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,14]],"date-time":"2024-12-14T00:00:00Z","timestamp":1734134400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Programa Operativo de Coopera\u00e7\u00e3o Transfronteiri\u00e7o Espanha-Portugal (POCTEP), project CILIFO\u2014Centro Ib\u00e9rico para la Investigaci\u00f3n y Lucha contra Incendios Forestales","award":["0753_CILIFO_5_E"],"award-info":[{"award-number":["0753_CILIFO_5_E"]}]},{"name":"FCT (Foundation for Science and Technology) under the Project with MED (Mediterranean Institute for Agriculture, Environment and Development)","award":["0753_CILIFO_5_E"],"award-info":[{"award-number":["0753_CILIFO_5_E"]}]},{"name":"CHANGE (Global Change and Sustainability Institute)","award":["0753_CILIFO_5_E"],"award-info":[{"award-number":["0753_CILIFO_5_E"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Land"],"abstract":"<jats:p>Land use and land cover (LULC) studies, particularly those focused on mapping forest species using Sentinel-2 (S2A) data, face challenges in delineating and identifying areas of heterogeneous forest components with spectral similarity at the canopy level. In this context, the main objective of this study was to compare and analyze the feasibility of two classification algorithms, K-Nearest Neighbor (KNN) and Random Forest (RF), with S2A data for mapping forest cover in the southern regions of Portugal, using tools with a free, open-source, accessible, and easy-to-use interface. Sentinel-2A data from summer 2019 provided 26 independent variables at 10 m spatial resolution for the analysis. Nine object-based LULC categories were distinguished, including five forest species (Quercus suber, Quercus rotundifolia, Eucalyptus spp., Pinus pinaster, and Pinus pinea), and four non-forest classes. Orfeo ToolBox (OTB) proved to be a reliable and powerful tool for the classification process. The best results were achieved using the RF algorithm in all regions, where it reached the highest accuracy values in Alentejo Central region (OA = 92.16% and K = 0.91). The use of open-source tools has enabled high-resolution mapping of forest species in the Mediterranean, democratizing access to research and monitoring.<\/jats:p>","DOI":"10.3390\/land13122184","type":"journal-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T06:48:39Z","timestamp":1734331719000},"page":"2184","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Mapping of Forest Species Using Sentinel-2A Images in the Alentejo and Algarve Regions, Portugal"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5909-7068","authenticated-orcid":false,"given":"Crismeire","family":"Isbaex","sequence":"first","affiliation":[{"name":"MED\u2014Mediterranean Institute for Agriculture, Environment and Development & CHANGE\u2014Global Change and Sustainability Institute, Institute for Advanced Research and Training, University of \u00c9vora, P.O. Box 94, 7002-544 \u00c9vora, Portugal"}]},{"given":"Ana Margarida","family":"Coelho","sequence":"additional","affiliation":[{"name":"ICT\u2014Institute of Earth Sciences, Institute for Advanced Research and Training, Col\u00e9gio Luis Ant\u00f3nio Verney, Rua Rom\u00e3o Ramalho, University of \u00c9vora, 59, 7002-554 \u00c9vora, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0128-9187","authenticated-orcid":false,"given":"Ana Cristina","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"MED\u2014Mediterranean Institute for Agriculture, Environment and Development & CHANGE\u2014Global Change and Sustainability Institute, Institute for Advanced Research and Training, Rural Engineering Department, School of Science and Technology, University of \u00c9vora, P.O. Box 94, 7002-544 \u00c9vora, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0060-0682","authenticated-orcid":false,"given":"Ad\u00e9lia M. O.","family":"Sousa","sequence":"additional","affiliation":[{"name":"MED\u2014Mediterranean Institute for Agriculture, Environment and Development & CHANGE\u2014Global Change and Sustainability Institute, Institute for Advanced Research and Training, Remote Sensing Laboratory\u2014EaRSLab, Rural Engineering Department, School of Science and Technology, University of \u00c9vora, P.O. Box 94, 7002-544 \u00c9vora, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chatziantoniou, A., Psomiadis, E., and Petropoulos, G.P. (2017). Co-Orbital Sentinel 1 and 2 for LULC Mapping with Emphasis on Wetlands in a Mediterranean Setting Based on Machine Learning. 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