{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T01:36:10Z","timestamp":1780364170036,"version":"3.54.1"},"reference-count":107,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T00:00:00Z","timestamp":1709078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"France 2030 program","award":["DOS0178310\/00"],"award-info":[{"award-number":["DOS0178310\/00"]}]},{"name":"France 2030 program","award":["DOS0178311\/00"],"award-info":[{"award-number":["DOS0178311\/00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Cover crops play a pivotal role in mitigating climate change by bolstering carbon sequestration through biomass production and soil integration. However, current methods for quantifying cover crop biomass lack spatial precision and objectivity. Thus, our research aimed to devise a remote-sensing-based approach to estimate cover crop biomass across various species and mixtures during fallow periods in France. Leveraging Sentinel-2 optical data and machine learning algorithms, we modeled biomass across 50 fields representative of France\u2019s diverse cropping practices and climate types. Initial tests using traditional empirical relationships between vegetation indices\/spectral bands and dry biomass revealed challenges in accurately estimating biomass for mixed cover crop categories due to spectral interference from grasses and weeds, underscoring the complexity of modeling diverse agricultural conditions. To address this challenge, we compared several machine learning algorithms (Support Vector Machine, Random Forest, and eXtreme Gradient Boosting) using spectral bands and vegetation indices from the latest available image before sampling as input. Additionally, we developed an approach that incorporates dense optical time series of Sentinel-2 data, generated using a Radial Basis Function for interpolation. Our findings demonstrated that a Random Forest model trained with dense time series data during the cover crop development period yielded promising results, with an average R-squared (r2) value of 0.75 and root mean square error (RMSE) of 0.73 t\u00b7ha\u22121, surpassing results obtained from methods using single-image snapshots (r2 of 0.55). Moreover, our approach exhibited robustness in accounting for factors such as crop species diversity, varied climatic conditions, and the presence of weed vegetation\u2014essential for approximating real-world conditions. Importantly, its applicability extends beyond France, holding potential for global scalability. The availability of data for model calibration across diverse regions and timeframes could facilitate broader application.<\/jats:p>","DOI":"10.3390\/rs16050834","type":"journal-article","created":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T07:56:02Z","timestamp":1709106962000},"page":"834","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Estimating Winter Cover Crop Biomass in France Using Optical Sentinel-2 Dense Image Time Series and Machine Learning"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4435-7610","authenticated-orcid":false,"given":"Hugo","family":"do Nascimento Bendini","sequence":"first","affiliation":[{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re (CESBIO), Centre National d\u2019\u00e9tudes Spatiales (CNES)\/Centre National de la Recherche Scientifique (CNRS)\/Institut National de Recherche pour l\u2019Agriculture, l\u2019Alimentation et l\u2019Anvironnement (INRAE)\/Institut de Recherche pour le D\u00e9veloppement (IRD)\/Universit\u00e9 Toulouse III-Paul Sabatier, 18, Avenue Edouard Belin, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R\u00e9my","family":"Fieuzal","sequence":"additional","affiliation":[{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re (CESBIO), Centre National d\u2019\u00e9tudes Spatiales (CNES)\/Centre National de la Recherche Scientifique (CNRS)\/Institut National de Recherche pour l\u2019Agriculture, l\u2019Alimentation et l\u2019Anvironnement (INRAE)\/Institut de Recherche pour le D\u00e9veloppement (IRD)\/Universit\u00e9 Toulouse III-Paul Sabatier, 18, Avenue Edouard Belin, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre","family":"Carrere","sequence":"additional","affiliation":[{"name":"EarthDaily Agro, 31130 Balma, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6743-7798","authenticated-orcid":false,"given":"Harold","family":"Clenet","sequence":"additional","affiliation":[{"name":"EarthDaily Agro, 31130 Balma, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aurelie","family":"Galvani","sequence":"additional","affiliation":[{"name":"EarthDaily Agro, 31130 Balma, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aubin","family":"Allies","sequence":"additional","affiliation":[{"name":"EarthDaily Agro, 31130 Balma, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5941-752X","authenticated-orcid":false,"given":"\u00c9ric","family":"Ceschia","sequence":"additional","affiliation":[{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re (CESBIO), Centre National d\u2019\u00e9tudes Spatiales (CNES)\/Centre National de la Recherche Scientifique (CNRS)\/Institut National de Recherche pour l\u2019Agriculture, l\u2019Alimentation et l\u2019Anvironnement (INRAE)\/Institut de Recherche pour le D\u00e9veloppement (IRD)\/Universit\u00e9 Toulouse III-Paul Sabatier, 18, Avenue Edouard Belin, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.agee.2010.09.020","article-title":"Management effects on net ecosystem carbon and GHG budgets at European crop sites","volume":"139","author":"Ceschia","year":"2010","journal-title":"Agric. 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