# Monitoring Within-Field Variability of Corn Yield using Sentinel-2 and Machine Learning Techniques
## 3 Results
### Vegetation Indices  
Each year presented a different pattern of yield spatial distribution due to different soil characteristics, variable rate nitrogen application by the farmer, and other weather conditions. In general, the yield maps showed a high yield at the north-western zone of the field compared with the south-eastern zone in 2016 and 2017 (Figure 2). In 2018, yield improved in the south-eastern zone while yield decreased in the north-western zone compared to previous seasons. Nine vegetation indices (NDVI, NDRE1, NDRE2, GNDVI, GARVI, EVI, WDRVI, mWDRVI, and GCVI) derived from each Sentinel-2 image calculated with three different NIR bands (8, 8A, and 9) were correlated with the actual yield map of each year. In general, correlations based on bands 8 and 8A were higher than those based on band 9. Band 8 and 8A correlations had the same trend for all seasons and at all crop ages with slight differences. Band 9 has a spatial resolution of 60 m which provided only 57 pixels for the whole study field compared to band 8A and 8, which have a spatial resolution of 20 and 10 m and provided 516 and 2067 pixels, respectively. The higher spatial resolution could describe the field variability more accurately and improve the correlation results. Therefore, VIs based on band 8 were considered for further analysis. The correlation between vegetation indices and corn grain yield (Figure 3) were low at the vegetative growth stages and early reproductive development stages (first 80 days of crop age) for 2017 and 2018 seasons. This correlation increased during the grain filling stage R3 (90 to 110 days) and reached its peak at the physiological maturity stage R4-R6 (105 to 135 days). This trend could be realized from the three seasons correlations (R\({}^{2}\) value), as shown in Figure 3. In 2016, the coefficient of determination (R\({}^{2}\) value) started from less than 0.2 at a crop age of 80 days (R3) and reached the highest R\({}^{2}\) value of 0.48 at 137 days (R6) from GNDVI. In 2017, a clearer trend was observed due to the higher number of available images, starting from an R\({}^{2}\) value of less than 0.2 at a crop age of 70 days (R2) and more than 0.35 for five different images from a crop age of 110 to 135 days (R4-R6). The highest R\({}^{2}\) value was for GNDVI compared to the other investigated indices at all stages, which reached a peak of 0.42 at the R6 stage at a crop age of 135 days. In 2018, R\({}^{2}\) values were not stable due to fog and blur in the images that affected the image quality but followed the same trend as previous seasons. The R\({}^{2}\) values started from less than 0.1 at a crop age between 60 and 100 days (R1-R4), then improved to reach the peak of 0.37 from GARVI and 0.36 from GNDVI at a crop age of 130 days (R6). All correlations between VIs and corn grain yield for all satellite image dates are available in the Supplementary files. GARVI provided the highest correlations in 2018 slightly higher than GNDVI. GARVI is more resistant to atmospheric effects, as described by [PERSON] et al. (2018), which explain GARVI's trend for this season in particular. Moreover, the correlation decreased dramatically at a crop age of 140 days  
Figure 3: Coefficient of determination (R\({}^{2}\) value) between vegetation indices and actual yield at different crop ages for the three seasons. The three columns represent different NIR bands used. for the 2017 and 2018 seasons with a R\({}^{2}\) value of less than 0.25, while it decreased to 0.4 for 2016. After 140 days, the crop enters the stage of full maturity and leaves turns from green to brown, thus decreasing the coefficient of determination R\({}^{2}\) value. The highest R\({}^{2}\) value was observed from GNDVI at crop ages of 127, 135, and 130 days for 2016, 2017, and 2018, respectively.