A calibration concept for satellite-based monitoring of the nitrogen nutrition index

P. Gregor; F. Argento; A. Walter; F. Liebisch

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A calibration concept for satellite-based monitoring of the nitrogen nutrition index

In: Precision agriculture '25

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P. Gregor

P. Gregor

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F. Argento

F. Argento

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A. Walter

A. Walter

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F. Liebisch

F. Liebisch
frank.liebisch@agroscope.admin.ch

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Type:: Chapter

Pages:: 760–767

DOI:: https://doi.org/10.1163/9789004725232_100

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Dar Hadith al Hassania

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Satellites offer a fast, robust, and cost-effective method for estimating crop nitrogen status but require high costs for model development and field infrastructure. This study demonstrates how satellite-based nitrogen estimation can be calibrated using ground-based technologies and small-scale experiments with inexpensive infrastructure and open satellite data. Machine learning models were trained on field spectrometer data to estimate crop nitrogen concentration (N_c) and dry matter. These models, when applied to Sentinel-2 data, successfully predicted the nitrogen nutrition index (NNI), explaining up to 57% of crop yield variance. The study shows that such models enable largescale, cost-efficient nitrogen management with broader calibration and validation.

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Precision agriculture '25

E-Book ISBN:: 9789004725232

Publisher:: Wageningen Academic

Print Publication Date:: 18 Jun 2025

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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A calibration concept for satellite-based monitoring of the nitrogen nutrition index

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Precision agriculture '25

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