{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T04:16:32Z","timestamp":1778645792769,"version":"3.51.4"},"reference-count":76,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T00:00:00Z","timestamp":1711324800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000137730\/22\/I-NB"],"award-info":[{"award-number":["4000137730\/22\/I-NB"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["DCM 206\/07.04.2022"],"award-info":[{"award-number":["DCM 206\/07.04.2022"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["2022.77"],"award-info":[{"award-number":["2022.77"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Bulgarian Ministry of Education and Science under the National Research Programme \u201cYoung scientists and postdoctoral students-2\u201d","award":["4000137730\/22\/I-NB"],"award-info":[{"award-number":["4000137730\/22\/I-NB"]}]},{"name":"Bulgarian Ministry of Education and Science under the National Research Programme \u201cYoung scientists and postdoctoral students-2\u201d","award":["DCM 206\/07.04.2022"],"award-info":[{"award-number":["DCM 206\/07.04.2022"]}]},{"name":"Bulgarian Ministry of Education and Science under the National Research Programme \u201cYoung scientists and postdoctoral students-2\u201d","award":["2022.77"],"award-info":[{"award-number":["2022.77"]}]},{"name":"China Scholarship Council Fund","award":["4000137730\/22\/I-NB"],"award-info":[{"award-number":["4000137730\/22\/I-NB"]}]},{"name":"China Scholarship Council Fund","award":["DCM 206\/07.04.2022"],"award-info":[{"award-number":["DCM 206\/07.04.2022"]}]},{"name":"China Scholarship Council Fund","award":["2022.77"],"award-info":[{"award-number":["2022.77"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The aim of this study is to predict and map winter wheat yield in the Parvomay municipality, situated in the Upper Thracian Lowland of Bulgaria, utilizing satellite data from Sentinel-2. The main crops grown in the research area are winter wheat, rapeseed, sunflower, and maize. To distinguish winter wheat fields accurately, we evaluated classification methods such as Support Vector Machines (SVM) and Random Forest (RF). These methods were applied to satellite multispectral data acquired by the Sentinel-2 satellites during the growing season of 2020\u20132021. In accordance with their development cycles, temporal image composites were developed to identify suitable moments when each crop is most accurately distinguished from others. Ground truth data obtained from the integrated administration and control system (IACS) were used for training the classifiers and assessing the accuracy of the final maps. Winter wheat fields were masked using the crop mask created from the best-performing classification algorithm. Yields were predicted with regression models calibrated with in situ data collected in the Parvomay study area. Both SVM and RF algorithms performed well in classifying winter wheat fields, with SVM slightly outperforming RF. The produced crop maps enable the application of crop-specific yield models on a regional scale. The best predictor of yield was the green NDVI index (GNDVI) from the April monthly composite image.<\/jats:p>","DOI":"10.3390\/rs16071144","type":"journal-article","created":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T12:28:06Z","timestamp":1711369686000},"page":"1144","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Crop Type Mapping and Winter Wheat Yield Prediction Utilizing Sentinel-2: A Case Study from Upper Thracian Lowland, Bulgaria"],"prefix":"10.3390","volume":"16","author":[{"given":"Ilina","family":"Kamenova","sequence":"first","affiliation":[{"name":"Department of Remote Sensing and GIS, Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Milen","family":"Chanev","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and GIS, Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4821-8231","authenticated-orcid":false,"given":"Petar","family":"Dimitrov","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and GIS, Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6248-0148","authenticated-orcid":false,"given":"Lachezar","family":"Filchev","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and GIS, Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bogdan","family":"Bonchev","sequence":"additional","affiliation":[{"name":"Institute of Plant Genetic Resources \u201cKonstantin Malkov\u201d\u2014Agricultural Academy, 4122 Sadovo, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghan","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Flemish Institute of Technological Research, 2400 Mol, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,25]]},"reference":[{"key":"ref_1","unstructured":"FAO (2023). 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