{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T22:13:41Z","timestamp":1783030421549,"version":"3.54.6"},"reference-count":78,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,12]],"date-time":"2020-03-12T00:00:00Z","timestamp":1583971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund of State Key Laboratory of Remote Sensing Science","award":["OFSLRSS201914"],"award-info":[{"award-number":["OFSLRSS201914"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41901380"],"award-info":[{"award-number":["41901380"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2662018QD066, CCNU18XJ032"],"award-info":[{"award-number":["2662018QD066, CCNU18XJ032"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Sichuan Science and Technology Program","award":["2017JY0284"],"award-info":[{"award-number":["2017JY0284"]}]},{"name":"\u201cInnovation Ability Promotion\u201d Program of the Sichuan Provincial Department of Finance","award":["2017QNJJ-023"],"award-info":[{"award-number":["2017QNJJ-023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global biophysical products at decametric resolution derived from Sentinel-2 imagery have emerged as a promising dataset for fine-scale ecosystem modeling and agricultural monitoring. Evaluating uncertainties of different Sentinel-2 biophysical products over various regions and vegetation types is pivotal in the application of land surface models. In this study, we quantified the performance of Sentinel-2-derived Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and Fractional Vegetation Cover (FVC) estimates using global ground observations with consistent measurement criteria. Our results show that the accuracy of vegetation and non-vegetated classification based on Sentinel-2 surface reflectance products is greater than 95%, which indicates the vegetation identification is favorable for the practical application of biophysical estimates, as several LAI, FAPAR, and FVC retrievals were derived for non-vegetated pixels. The rate of best retrievals is similar between LAI and FAPAR estimates, both accounting for 87% of all vegetation pixels, while it is almost 100% for FVC estimates. Additionally, the Sentinel-2 FAPAR and FVC estimates agree well with ground-measurements-derived (GMD) reference maps, whereas a large discrepancy is observed for Sentinel-2 LAI estimates by comparing with both GMD effective LAI (LAIe) and actual LAI (LAI) reference maps. Furthermore, the uncertainties of Sentinel-2 LAI, FAPAR and FVC estimates are 1.09 m2\/m2, 1.14 m2\/m2, 0.13 and 0.17 through comparisons to ground LAIe, LAI, FAPAR, and FVC measurements, respectively. Given the temporal difference between Sentinel-2 observations and ground measurements, Sentinel-2 LAI estimates are more consistent with LAIe than LAI values. The robustness of evaluation results can be further improved as long as more multi-temporal ground measurements across different regions are obtained. Overall, this study provides fundamental information about the performance of Sentinel-2 LAI, FAPAR, and FVC estimates, which imbues our confidence in the broad applications of these decametric products.<\/jats:p>","DOI":"10.3390\/rs12060912","type":"journal-article","created":{"date-parts":[[2020,3,12]],"date-time":"2020-03-12T12:22:51Z","timestamp":1584015771000},"page":"912","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":70,"title":["Evaluation of Global Decametric-Resolution LAI, FAPAR and FVC Estimates Derived from Sentinel-2 Imagery"],"prefix":"10.3390","volume":"12","author":[{"given":"Qiong","family":"Hu","sequence":"first","affiliation":[{"name":"Key Laboratory for Geographical Process Analysis &amp; Simulation of Hubei Province\/School of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingya","family":"Yang","sequence":"additional","affiliation":[{"name":"Macro Agriculture Research Institute, College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2068-8610","authenticated-orcid":false,"given":"Baodong","family":"Xu","sequence":"additional","affiliation":[{"name":"Macro Agriculture Research Institute, College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China"},{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0341-1983","authenticated-orcid":false,"given":"Jianxi","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Land Science and Technology, China Agricultural University, Beijing 100083, China"},{"name":"Key Laboratory of Remote Sensing for Agri\u2013Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0079-0260","authenticated-orcid":false,"given":"Muhammad Sohail","family":"Memon","sequence":"additional","affiliation":[{"name":"Faculty of Agricultural Engineering, Sindh Agriculture University, Tandojam 70060, Pakistan"},{"name":"College of Engineering, Nanjing Agricultural University, Nanjing 210031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaofei","family":"Yin","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China"},{"name":"CREAF, 08193 Cerdanyola del Vall\u00e8s, Catalonia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4267-1841","authenticated-orcid":false,"given":"Yelu","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7221-3556","authenticated-orcid":false,"given":"Jing","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing Application, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1126\/science.275.5299.502","article-title":"Modeling the exchanges of energy, water, and carbon between continents and the atmosphere","volume":"275","author":"Sellers","year":"1997","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1038\/370049a0","article-title":"Importance of vegetation in removing polycyclic aromatic hydrocarbons from the atmosphere","volume":"370","author":"Simonich","year":"1994","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Huang, J., Zhuo, W., Li, Y., Huang, R., Sedano, F., Su, W., Dong, J., Tian, L., Huang, Y., and Zhu, D. 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