López-Hernández et al. (2026) Sentinel-2 and Unmanned Aerial Vehicle (UAV) Imagery for Irrigation Scheduling in Fodder Maize: A Comparative Remote Sensing Approach

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Identification

• Journal: Plants
• Year: 2026
• Date: 2026-07-24
• Authors: Nuria Aide López-Hernández, Víctor Manuel Rodríguez-Moreno, Ricardo Israel Ramírez Gottfried, Ramón Trucíos-Caciano, Marco A. Inzunza-Ibarra, Aldo Rafael Martínez Sifuentes
• DOI: 10.3390/plants15152265

Research Groups

Not specified

Short Summary

This study compared satellite- and UAV-derived NDVI models for estimating crop coefficients (Kc) in forage maize to optimize irrigation scheduling. It found that while UAV models had higher calibration accuracy, satellite-based scheduling provided the best balance between water efficiency, forage yield, and nutritional quality.

Objective

• To compare the accuracy of satellite- and UAV-derived NDVI models for estimating crop coefficients (Kc) and evaluate their operational performance for irrigation scheduling in two forage maize hybrids.

Study Configuration

• Spatial Scale: Field level (two forage maize hybrids: N83N5 and Matador)
• Temporal Scale: Two growing seasons (2023 for model development and 2024 for field validation)

Methodology and Data

• Models used: Kc–NDVI models
• Data sources: Satellite imagery, UAV imagery, and field-based irrigation strategies (Conventional, Satellite-based, and UAV-based)

Main Results

• Model Accuracy: The UAV-derived NDVI model exhibited higher calibration accuracy ($R^2 = 0.9414$) than the satellite-derived model ($R^2 = 0.8278$).
• Water Use: UAV-based irrigation scheduling (ID3) reduced water application by 23–30% compared to other methods, but this led to reductions in crop growth, forage yield, and nutritional quality.
• Yield and Quality: Satellite-based irrigation scheduling (ID2) produced the highest forage yield (reaching 59.8 t ha⁻¹ for hybrid N83N5) and improved nutritional quality by increasing dry matter and starch concentrations while reducing fiber fractions.
• Operational Insight: A stronger statistical relationship between Kc and NDVI (as seen in UAV data) does not necessarily translate to superior irrigation scheduling performance.

Contributions

The research highlights the trade-offs between spatial resolution and operational scalability in precision irrigation. It demonstrates that satellite-based models can be more effective than high-resolution UAV models for maintaining a balance between water productivity and crop quality in forage maize production.

Funding

Not specified

Citation

@article{LópezHernández2026Sentinel2,
  author = {López-Hernández, Nuria Aide and Rodríguez-Moreno, Víctor Manuel and Gottfried, Ricardo Israel Ramírez and Trucíos-Caciano, Ramón and Inzunza-Ibarra, Marco A. and Sifuentes, Aldo Rafael Martínez},
  title = {Sentinel-2 and Unmanned Aerial Vehicle (UAV) Imagery for Irrigation Scheduling in Fodder Maize: A Comparative Remote Sensing Approach},
  journal = {Plants},
  year = {2026},
  doi = {10.3390/plants15152265},
  url = {https://doi.org/10.3390/plants15152265}
}