GIScience & Remote Sensing
Volume 61, 2024 - Issue 1
Open access
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Research Article
Global de-trending significantly improves the accuracy of XGBoost-based county-level maize and soybean yield prediction in the Midwestern United States
Yuanchao Lia State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China;b College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China;c Department of Marketing Management, China Siwei Surveying and Mapping Technology Co. Ltd, Beijing, ChinaView further author information
, Hongwei Zenga State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China;b College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaCorrespondence[email protected]
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Miao Zhanga State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaView further author information
, Bingfang Wua State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China;b College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaCorrespondence[email protected]
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Xingli Qina State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaView further author information
Article: 2349341
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Received 24 Aug 2023, Accepted 26 Apr 2024, Published online: 09 May 2024
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