This observational analysis finds the optimal altitude for UAV multispectral imaging improves wheat growth assessments, highlighting advantages for precision agriculture.
This study evaluated the growth stages of wheat crops in the agricultural fields of Bayantsogt Soum, Tuv aimag-province, Mongolia, using unmanned aerial vehicles (UAVs) equipped with multispectral cameras. Aerial imagery was captured at four spatial resolutions - 1.59 cm, 3.63 cm, 5.44 cm, and 11.35 cm - corresponding to flight altitudes of 30 m, 80 m, 120 m, and 250 m, respectively. Six vegetation indices (NDVI, GNDVI, LCI, NDRE, NDWI, and OSAVI) were calculated to evaluate their relationships with wheat biometric parameters. The determinant coefficient (R²) values for these indices were: LCI (0.81), OSAVI (0.79), NDRE (0.76), NDVI (0.76), NDWI (0.75), and GNDVI (0.73). Regarding spatial resolution, the corresponding R² values were 0.62 (1.59 ± 0.46 cm), 0.87 (3.63 ± 0.02 cm), 0.88 (5.44 ± 0.06 cm), and 0.68 (11.35 ± 0.04 cm) respectively. The findings indicate that the optimal flight altitude for estimating wheat growth characteristics was 120 m, providing a high correlation at a resolution of 5.44 ± 0.06 cm. By contrast, imagery captured from 250 m demonstrated relatively lower correlation. Overall, this study highlights the potential of UAV-based multispectral imaging for efficient crop monitoring and suggests an optimal operational altitude for precision agriculture applications.
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Turuu et al. (2025) studied this question.
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