{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T17:36:06Z","timestamp":1771608966568,"version":"3.50.1"},"reference-count":106,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,10]],"date-time":"2022-09-10T00:00:00Z","timestamp":1662768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000781","name":"European Research Council (ERC)","doi-asserted-by":"publisher","award":["755617"],"award-info":[{"award-number":["755617"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ram\u00f3n y Cajal Contract (Spanish Ministry of Science, Innovation and Universities)","award":["755617"],"award-info":[{"award-number":["755617"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant development along the crop\u2019s phenological cycle, which is particularly relevant for irrigated agricultural areas. The high spatial and temporal resolution of the Sentinel-2 (S2) multispectral instrument leverages the possibility to estimate leaf area index (LAI), canopy chlorophyll content (CCC), and vegetation water content (VWC) from space. Therefore, our study presents a hybrid retrieval workflow combining a physically-based strategy with a machine learning regression algorithm, i.e., Gaussian processes regression, and an active learning technique to estimate LAI, CCC and VWC of irrigated winter wheat. The established hybrid models of the three traits were validated against in-situ data of a wheat campaign in the Bonaerense valley, South of the Buenos Aires Province, Argentina, in the year 2020. We obtained good to highly accurate validation results with LAI: R2 = 0.92, RMSE = 0.43 m2 m\u22122, CCC: R2 = 0.80, RMSE = 0.27 g m\u22122 and VWC: R2 = 0.75, RMSE = 416 g m\u22122. The retrieval models were also applied to a series of S2 images, producing time series along the seasonal cycle, which reflected the effects of fertilizer and irrigation on crop growth. The associated uncertainties along with the obtained maps underlined the robustness of the hybrid retrieval workflow. We conclude that processing S2 imagery with optimised hybrid models allows accurate space-based crop traits mapping over large irrigated areas and thus can support agricultural management decisions.<\/jats:p>","DOI":"10.3390\/rs14184531","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T04:05:41Z","timestamp":1663041941000},"page":"4531","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2268-2674","authenticated-orcid":false,"given":"Gabriel","family":"Caballero","sequence":"first","affiliation":[{"name":"Agri-Environmental Engineering, Technological University of Uruguay (UTEC), Av. Italia 6201, Montevideo 11500, Uruguay"},{"name":"Image Processing Laboratory (IPL), University of Valencia, C\/Catedr\u00e1tico Jos\u00e9 Beltr\u00e1n 2, 46980 Paterna, Spain"}]},{"given":"Alejandro","family":"Pezzola","sequence":"additional","affiliation":[{"name":"Remote Sensing and SIG Laboratory, Hilario Ascasubi Agricultural Experimental Station, National Institute of Agricultural Technology (INTA), Hilario Ascasubi 8142, Argentina"}]},{"given":"Cristina","family":"Winschel","sequence":"additional","affiliation":[{"name":"Remote Sensing and SIG Laboratory, Hilario Ascasubi Agricultural Experimental Station, National Institute of Agricultural Technology (INTA), Hilario Ascasubi 8142, Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6718-3679","authenticated-orcid":false,"given":"Alejandra","family":"Casella","sequence":"additional","affiliation":[{"name":"Permanent Observatory of Agro-Ecosystems, Climate and Water Institute-National Agricultural Research Centre (ICyA-CNIA), National Institute of Agricultural Technology (INTA), Nicol\u00e1s Repetto s\/n, Hurlingham 1686, Argentina"}]},{"given":"Paolo","family":"Sanchez Angonova","sequence":"additional","affiliation":[{"name":"Remote Sensing and SIG Laboratory, Hilario Ascasubi Agricultural Experimental Station, National Institute of Agricultural Technology (INTA), Hilario Ascasubi 8142, Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3188-1448","authenticated-orcid":false,"given":"Juan Pablo","family":"Rivera-Caicedo","sequence":"additional","affiliation":[{"name":"Secretary of Research and Graduate Studies, CONACYT-UAN, Tepic 63155, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0784-7717","authenticated-orcid":false,"given":"Katja","family":"Berger","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), University of Valencia, C\/Catedr\u00e1tico Jos\u00e9 Beltr\u00e1n 2, 46980 Paterna, Spain"},{"name":"Mantle Labs GmbH, Gr\u00fcnentorgasse 19\/4, 1090 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6313-2081","authenticated-orcid":false,"given":"Jochem","family":"Verrelst","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), University of Valencia, C\/Catedr\u00e1tico Jos\u00e9 Beltr\u00e1n 2, 46980 Paterna, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2819-6979","authenticated-orcid":false,"given":"Jesus","family":"Delegido","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), University of Valencia, C\/Catedr\u00e1tico Jos\u00e9 Beltr\u00e1n 2, 46980 Paterna, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s12571-013-0263-y","article-title":"Crops that feed the world 10. 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