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Li, Yuanchao [Author]; Zeng, Hongwei [Author]; Zhang, Miao [Author]; Wu, Bingfang [Author]; Qin, Xingli [Author]

Global de-trending significantly improves the accuracy of XGBoost-based county-level maize and soybean yield prediction in the Midwestern United States

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  • Media type: E-Article
  • Title: Global de-trending significantly improves the accuracy of XGBoost-based county-level maize and soybean yield prediction in the Midwestern United States
  • Contributor: Li, Yuanchao [Author]; Zeng, Hongwei [Author]; Zhang, Miao [Author]; Wu, Bingfang [Author]; Qin, Xingli [Author]
  • Published: 9 May 2024
  • Published in: GIScience and remote sensing ; 61(2024), 1, Artikel-ID 2349341
  • Language: English
  • DOI: 10.1080/15481603.2024.2349341
  • Identifier:
  • Origination:
  • Footnote: Literaturverzeichnis: Seite 22-25
  • Access State: Open Access