Potential of hyperspectral satellite biophysical variables in a crop model assimilation scenario

R. Fazioli; F. Carucci; L. Marrone; S. Pignatti; S. Mirazei; F. Rossi; S. Lo Presti; D. Kovács; R. Casa

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Potential of hyperspectral satellite biophysical variables in a crop model assimilation scenario

In: Precision agriculture '25

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R. Fazioli

R. Fazioli

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F. Carucci

F. Carucci

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L. Marrone

L. Marrone

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S. Pignatti

S. Pignatti

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S. Mirazei

S. Mirazei

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F. Rossi

F. Rossi

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S. Lo Presti

S. Lo Presti

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D. Kovács

D. Kovács

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R. Casa

R. Casa
rcasa@unitus.it

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Type:: Chapter

Pages:: 768–774

DOI:: https://doi.org/10.1163/9789004725232_101

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Dar Hadith al Hassania

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This study evaluated the use of remotely sensed biophysical variables for estimation of wheat yield and grain nitrogen, in the DSSAT model. In a synthetic data experiment, seasonal patterns of LAI, biomass and canopy nitrogen were generated by model simulation, across various scenarios. Calibration of the DSSAT model with the assimilated biomass and canopy N significantly enhanced the grain yield and N estimation accuracy of the model. Validation with real data from Sentinel-2 generally confirmed these results, albeit with reduced accuracy. This work indicates that the use of hyperspectral satellite data allowed better estimation of biomass and canopy N, improving yield estimation from data assimilation with the DSSAT model.

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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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Potential of hyperspectral satellite biophysical variables in a crop model assimilation scenario

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Precision agriculture '25

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