{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T17:24:32Z","timestamp":1781717072322,"version":"3.54.5"},"reference-count":101,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,5,4]],"date-time":"2023-05-04T00:00:00Z","timestamp":1683158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the POLYPHEME project through the TOSCA program of the Centre national d\u2019\u00e9tudes spatiales (CNES)","award":["200769\/id5917"],"award-info":[{"award-number":["200769\/id5917"]}]},{"name":"the POLYPHEME project through the TOSCA program of the Centre national d\u2019\u00e9tudes spatiales (CNES)","award":["862695"],"award-info":[{"award-number":["862695"]}]},{"name":"the framework of the STEROPES project of the EJP-SOIL Horizon H2020","award":["200769\/id5917"],"award-info":[{"award-number":["200769\/id5917"]}]},{"name":"the framework of the STEROPES project of the EJP-SOIL Horizon H2020","award":["862695"],"award-info":[{"award-number":["862695"]}]},{"name":"the MELICERTES project (ANR-22-PEAE-0010) of the French National Research Agency under the France2030 program","award":["200769\/id5917"],"award-info":[{"award-number":["200769\/id5917"]}]},{"name":"the MELICERTES project (ANR-22-PEAE-0010) of the French National Research Agency under the France2030 program","award":["862695"],"award-info":[{"award-number":["862695"]}]},{"name":"the national PEPR \u201cagro\u00e9cologie et num\u00e9rique\u201d program","award":["200769\/id5917"],"award-info":[{"award-number":["200769\/id5917"]}]},{"name":"the national PEPR \u201cagro\u00e9cologie et num\u00e9rique\u201d program","award":["862695"],"award-info":[{"award-number":["862695"]}]},{"name":"INRAE (Institut national de recherche pour l\u2019agriculture, l\u2019alimentation et l\u2019environnement)","award":["200769\/id5917"],"award-info":[{"award-number":["200769\/id5917"]}]},{"name":"INRAE (Institut national de recherche pour l\u2019agriculture, l\u2019alimentation et l\u2019environnement)","award":["862695"],"award-info":[{"award-number":["862695"]}]},{"name":"ADEME (Agence de la transition \u00e9cologique)","award":["200769\/id5917"],"award-info":[{"award-number":["200769\/id5917"]}]},{"name":"ADEME (Agence de la transition \u00e9cologique)","award":["862695"],"award-info":[{"award-number":["862695"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite-based soil organic carbon content (SOC) mapping over wide regions is generally hampered by the low soil sampling density and the diversity of soil sampling periods. Some unfavorable topsoil conditions, such as high moisture, rugosity, the presence of crop residues, the limited amplitude of SOC values and the limited area of bare soil when a single image is used, are also among the influencing factors. To generate a reliable SOC map, this study addresses the use of Sentinel-2 (S2) temporal mosaics of bare soil (S2Bsoil) over 6 years jointly with soil moisture products (SMPs) derived from Sentinel 1 and 2 images, SOC measurement data and other environmental covariates derived from digital elevation models, lithology maps and airborne gamma-ray data. In this study, we explore (i) the dates and periods that are preferable to construct temporal mosaics of bare soils while accounting for soil moisture and soil management; (ii) which set of covariates is more relevant to explain the SOC variability. From four sets of covariates, the best contributing set was selected, and the median SOC content along with uncertainty at 90% prediction intervals were mapped at a 25-m resolution from quantile regression forest models. The accuracy of predictions was assessed by 10-fold cross-validation, repeated five times. The models using all the covariates had the best model performance. Airborne gamma-ray thorium, slope and S2 bands (e.g., bands 6, 7, 8, 8a) and indices (e.g., calcareous sedimentary rocks, \u201ccalcl\u201d) from the \u201clate winter\u2013spring\u201d time series were the most important covariates in this model. Our results also indicated the important role of neighboring topographic distances and oblique geographic coordinates between remote sensing data and parent material. These data contributed not only to optimizing SOC mapping performance but also provided information related to long-range gradients of SOC spatial variability, which makes sense from a pedological point of view.<\/jats:p>","DOI":"10.3390\/rs15092410","type":"journal-article","created":{"date-parts":[[2023,5,5]],"date-time":"2023-05-05T02:08:42Z","timestamp":1683252522000},"page":"2410","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Sentinel-2 and Sentinel-1 Bare Soil Temporal Mosaics of 6-year Periods for Soil Organic Carbon Content Mapping in Central France"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4327-906X","authenticated-orcid":false,"given":"Diego","family":"Urbina-Salazar","sequence":"first","affiliation":[{"name":"University of Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, 91120 Palaiseau, France"},{"name":"INRAE, Info&Sols, 45075 Orl\u00e9ans, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4703-3702","authenticated-orcid":false,"given":"Emmanuelle","family":"Vaudour","sequence":"additional","affiliation":[{"name":"University of Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, 91120 Palaiseau, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3170-4014","authenticated-orcid":false,"given":"Anne C.","family":"Richer-de-Forges","sequence":"additional","affiliation":[{"name":"INRAE, Info&Sols, 45075 Orl\u00e9ans, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1245-0482","authenticated-orcid":false,"given":"Songchao","family":"Chen","sequence":"additional","affiliation":[{"name":"ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China"},{"name":"Institute of Agriculture Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4922-4323","authenticated-orcid":false,"given":"Guillaume","family":"Martelet","sequence":"additional","affiliation":[{"name":"BRGM, 3 av. Claude Guillemin, BP36009, CEDEX 2, 45060 Orl\u00e9ans, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9461-4120","authenticated-orcid":false,"given":"Nicolas","family":"Baghdadi","sequence":"additional","affiliation":[{"name":"UMR TETIS, INRAE, University of Montpellier, UMR TETIS, 500 rue Fran\u00e7ois Breton, CEDEX 5, 34093 Montpellier, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6878-6498","authenticated-orcid":false,"given":"Dominique","family":"Arrouays","sequence":"additional","affiliation":[{"name":"INRAE, Info&Sols, 45075 Orl\u00e9ans, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007GB002952","article-title":"Farming the planet: 1. 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