{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T17:48:45Z","timestamp":1780595325973,"version":"3.54.1"},"reference-count":87,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,2,21]],"date-time":"2019-02-21T00:00:00Z","timestamp":1550707200000},"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>The spatial quantification of green leaf area index (LAIgreen), the total green photosynthetically active leaf area per ground area, is a crucial biophysical variable for agroecosystem monitoring. The Sentinel-2 mission is with (1) a temporal resolution lower than a week, (2) a spatial resolution of up to 10 m, and (3) narrow bands in the red and red-edge region, a highly promising mission for agricultural monitoring. The aim of this work is to define an easy implementable LAIgreen index for the Sentinel-2 mission. Two large and independent multi-crop datasets of in situ collected LAIgreen measurements were used. Commonly used LAIgreen indices applied on the Sentinel-2 10 m \u00d7 10 m pixel resulted in a validation R2 lower than 0.6. By calculating all Sentinel-2 band combinations to identify high correlation and physical basis with LAIgreen, the new Sentinel-2 LAIgreen Index (SeLI) was defined. SeLI is a normalized index that uses the 705 nm and 865 nm centered bands, exploiting the red-edge region for low-saturating absorption sensitivity to photosynthetic vegetation. A R2 of 0.708 (root mean squared error (RMSE) = 0.67) and a R2 of 0.732 (RMSE = 0.69) were obtained with a linear fitting for the calibration and validation datasets, respectively, outperforming established indices. Sentinel-2 LAIgreen maps are presented.<\/jats:p>","DOI":"10.3390\/s19040904","type":"journal-article","created":{"date-parts":[[2019,2,22]],"date-time":"2019-02-22T03:49:44Z","timestamp":1550807384000},"page":"904","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":121,"title":["Multi-Crop Green LAI Estimation with a New Simple Sentinel-2 LAI Index (SeLI)"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0782-8455","authenticated-orcid":false,"given":"Nieves","family":"Pasqualotto","sequence":"first","affiliation":[{"name":"Image Processing Laboratory (IPL), University of Valencia, 46980 Valencia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jes\u00fas","family":"Delegido","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), University of Valencia, 46980 Valencia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5699-0352","authenticated-orcid":false,"given":"Shari","family":"Van Wittenberghe","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), University of Valencia, 46980 Valencia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michele","family":"Rinaldi","sequence":"additional","affiliation":[{"name":"Council for Agricultural Research and Economics\u2014Research Centre for Cereal and Industrial Crops, S.S. 673 km 25, 200, 71122 Foggia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9","family":"Moreno","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), University of Valencia, 46980 Valencia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/0034-4257(92)90132-4","article-title":"Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies","volume":"39","author":"Daughtry","year":"1992","journal-title":"Remote Sens. 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