Estimating yields, using a combination of remote sensing and a simple crop model

C.-P. Federolf; S. Reusch; G. Portz; A. Truszkowski-Graw; J. Jasper

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Estimating yields, using a combination of remote sensing and a simple crop model

于Precision agriculture '25

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C.-P. Federolf

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S. Reusch

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G. Portz

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A. Truszkowski-Graw

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J. Jasper

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类型:: 章节

Page Range:: 673–680

DOI:: https://doi.org/10.1163/9789004725232_088

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Dar Hadith al Hassania

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Grain yields and their variability impact agronomic management decisions, yet accurate yield maps of multiple seasons in a comparable format are often unavailable at farm level. While crop growth models could estimate site-specific yields, they lack sufficient high-resolution input data. This study hypothesized that combining a growth model with satellite imagery-derived vegetation information could generate yield estimations and yield maps. The model was calibrated using field average yield data from 2017–2023 across relevant global cereal growing areas. The model achieved an r² of 0.771 for training data and 0.443 for test data, demonstrating its potential for accurate yield mapping.

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Precision agriculture '25

ISBN:: 9789004725232

出版社:: Wageningen Academic

印刷出版日期:: 18 Jun 2025

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Estimating yields, using a combination of remote sensing and a simple crop model

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Precision agriculture '25

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