Acta Univ. Agric. Silvic. Mendelianae Brun. 2018, 66, 1141-1150
Published online 2018-10-29

Estimating Crop Yields at the Field Level Using Landsat and Modis Products

František Jurečka1,2, Vojtěch Lukas1,2, Petr Hlavinka2, Daniela Semerádová1,2, Zdeněk Žalud1,2, Miroslav Trnka2

1Department of Agrosystems and Bioclimatology, Mendel University in Brno, Brno, Czech Republic
2Global Change Research Institute, Academy of Sciences of the Czech Republic, v.v.i, Bělidla 986/4a, 603 00 Brno, Czech Republic

Remote sensing can be used for yield estimation prior to harvest at the field level to provide helpful information for agricultural decision making. This study was undertaken in Polkovice, located at low elevations in the Czech Republic. From 2014–2016, two datasets of satellite imagery were used: the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 datasets. Satellite data were compared with yields and other observations at the level of land blocks. Winter oilseed rape, winter wheat and spring barley yield data, representing the crops planted over the analyzed period, were used for comparison. In 2016, a more detailed analysis was conducted. We tested a relationship between remote sensing data and the spatial yield variability measured by a yield monitor from a combine harvester. Correlations varied from approximately r = 0.4 to r = 0.7 with the highest correlation (r = 0.74) between yield and the Green Normalized Difference Vegetation Index collected from a drone. Vegetation indices from both Landsat 8 and the MODIS showed a positive relationship with yields for the compared period. The highest correlation was between yield and the Enhanced Vegetation Index (r = 0.8) while the lowest was between yield and the Normalized Difference Vegetation Index from MODIS (r = 0.1).


FJ, PH and MT were supported by the project SustES – Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). This work was also conducted at Mendel University in Brno as a part of the project IGA AF MENDELU no. IP 14/2016 with the support of the Specific University Research Grant, provided by the Ministry of Education, Youth and Sports of the Czech Republic in 2016.


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