{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T14:50:20Z","timestamp":1784213420655,"version":"3.55.0"},"reference-count":59,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T00:00:00Z","timestamp":1667174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the earmarked fund for China Agriculture Research System","award":["CARS-03"],"award-info":[{"award-number":["CARS-03"]}]},{"name":"the earmarked fund for China Agriculture Research System","award":["42271396"],"award-info":[{"award-number":["42271396"]}]},{"name":"the earmarked fund for China Agriculture Research System","award":["2019YFE0125300"],"award-info":[{"award-number":["2019YFE0125300"]}]},{"name":"National Natural Science Foundation of China","award":["CARS-03"],"award-info":[{"award-number":["CARS-03"]}]},{"name":"National Natural Science Foundation of China","award":["42271396"],"award-info":[{"award-number":["42271396"]}]},{"name":"National Natural Science Foundation of China","award":["2019YFE0125300"],"award-info":[{"award-number":["2019YFE0125300"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["CARS-03"],"award-info":[{"award-number":["CARS-03"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["42271396"],"award-info":[{"award-number":["42271396"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["2019YFE0125300"],"award-info":[{"award-number":["2019YFE0125300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Crop production is one of the major interactions between humans and the natural environment, in the process, carbon is translocated cyclically inside the ecosystem. Data assimilation algorithm has advantages in mechanism and robustness in yield estimation, however, the computational efficiency is still a major obstacle for widespread application. To address the issue, a novel hybrid method based on the combination of the Crop Biomass Algorithm of Wheat (CBA-Wheat) to the Simple Algorithm For Yield (SAFY) model and the transfer learning method was proposed in this paper, which enables winter wheat yield estimation with acceptable accuracy and calculation efficiency. The transfer learning techniques learn the knowledge from the SAFY model and then use the knowledge to predict wheat yield. The main results showed that: (1) The comparison using CBA-Wheat between measured AGB and predicted AGB all reveal a good correlation with R2 of 0.83 and RMSE of 1.91 t ha\u22121, respectively; (2) The performance of yield prediction was as follows: transfer learning method (R2 of 0.64, RMSE of 1.05 t ha\u22121) and data assimilation (R2 of 0.64, RMSE of 1.01 t ha\u22121). At the farm scale, the two yield estimation models are still similar in performance with RMSE of 1.33 t ha\u22121 for data assimilation and 1.13 t ha\u22121 for transfer learning; (3) The time consumption of transfer learning with complete simulation data set is significantly lower than that of the other two yield estimation tests. The number of pixels to be simulated was about 16,000, and the computational efficiency of the data assimilation algorithm and transfer learning without complete simulation datasets. The transfer learning model shows great potential in improving the efficiency of production estimation.<\/jats:p>","DOI":"10.3390\/rs14215474","type":"journal-article","created":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T06:01:28Z","timestamp":1667282488000},"page":"5474","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Transfer-Learning-Based Approach for Yield Prediction of Winter Wheat from Planet Data and SAFY Model"],"prefix":"10.3390","volume":"14","author":[{"given":"Yu","family":"Zhao","sequence":"first","affiliation":[{"name":"National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoyu","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Meng","sequence":"additional","affiliation":[{"name":"National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3312-6200","authenticated-orcid":false,"given":"Haikuan","family":"Feng","sequence":"additional","affiliation":[{"name":"National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9878-3274","authenticated-orcid":false,"given":"Zhenhai","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"},{"name":"College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingli","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Agriculture, Qingdao Hengxing University of Science and Technology, Qingdao 266100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0294-5705","authenticated-orcid":false,"given":"Xiaoyu","family":"Song","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1884-2404","authenticated-orcid":false,"given":"Yan","family":"Zhu","sequence":"additional","affiliation":[{"name":"National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guijun","family":"Yang","sequence":"additional","affiliation":[{"name":"National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China"},{"name":"Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"015001","DOI":"10.1088\/1748-9326\/aa518a","article-title":"Comparing estimates of climate change impacts from process-based and statistical crop models","volume":"12","author":"Lobell","year":"2017","journal-title":"Environ. 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