<abstract xmlns="http://www.w3.org/1999/xhtml">

The active biomass of cultivated plants and average yield decreases as a result of biotic and abiotic stress effect. The extent of the reduction can be quantified on the basis of remotely sensed data. The aim of this research is to evaluate the suitability of Landsat 8 data for a wheat yield estimation. We processed Landsat 8 recordings for the period 2013–2019 and generated NDVI data. Time series NDVI data were calibrated and validated with observed wheat yield averages. The agricultural plots around Karcag, Hungary, were our research area. The relation between Landsat NDVI data and yield was strongest and highest in the total biomass period (<italic>R</italic>2 = 0.53–0.54) and the estimation error based on RMSE is between 0.48–0.7 t.ha−1.
</abstract>

The active biomass of cultivated plants and average yield decreases as a result of biotic and abiotic stress effect. The extent of the reduction can be quantified on the basis of remotely sensed data. The aim of this research is to evaluate the suitability of Landsat 8 data for a wheat yield estimation. We processed Landsat 8 recordings for the period 2013–2019 and generated NDVI data. Time series NDVI data were calibrated and validated with observed wheat yield averages. The agricultural plots around Karcag, Hungary, were our research area. The relation between Landsat NDVI data and yield was strongest and highest in the total biomass period (R2 = 0.53–0.54) and the estimation error based on RMSE is between 0.48–0.7 t.ha−1.

Assessment of a Yield Prediction Method Based on Time Series Landsat 8 Data

Acta Horticulturae et Regiotecturae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Assessment of a Yield Prediction Method Based on Time Series Landsat 8 Data"}

The active biomass of cultivated plants and average yield decreases as a result of biotic and abiotic stress effect. The extent of the reduction can be...

Assessment of a Yield Prediction Method Based on Time Series Landsat 8 Data

Online veröffentlicht: 21. Mai 2021

Seitenbereich: 12 - 15

DOI: https://doi.org/10.2478/ahr-2021-0003

Schlüsselwörter
Landsat 8, crop, yield prediction

© 2021 Andrea Szabó et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Assessment of a Yield Prediction Method Based on Time Series Landsat 8 Data

Online veröffentlicht: 21. Mai 2021

Seitenbereich: 12 - 15

DOI: https://doi.org/10.2478/ahr-2021-0003

SchlüsselwörterLandsat 8, crop, yield prediction

© 2021 Andrea Szabó et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Landsat 8, crop, yield prediction