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Sentinel-2 and Unmanned Aerial Vehicle (UAV) Imagery for Irrigation Scheduling in Fodder Maize: A Comparative Remote
Nuria Aide López Hernández1, Victor Manuel Rodríguez Moreno2, Ricardo Israel Ramírez Gottfried3
1National Center for Disciplinary Research in the Relationship Water, Soil, Plant, and Atmosphere, National Institute of Agricultural and Livestock Forestry Research, Km. 6.5 Margen Derecha Canal de Sacramento, Gomez Palacio 35079, Mexico.
Plants (Basel, Switzerland)
|August 13, 2026
Summary
Satellite and UAV imagery offer insights into crop water needs for maize. Satellite-based irrigation scheduling balanced water use, yield, and quality, outperforming UAV-based methods despite lower NDVI model accuracy.
Area of Science:
- Agricultural Science
- Remote Sensing
- Agronomy
Background:
- Optimizing irrigation is crucial for forage maize production and water resource management.
- Accurate crop coefficients (Kc) are essential for effective irrigation scheduling.
- Normalized Difference Vegetation Index (NDVI) derived from remote sensing offers a promising approach for Kc estimation.
Purpose of the Study:
- To compare satellite- and UAV-derived NDVI models for estimating Kc in forage maize.
- To evaluate the operational performance of these models for irrigation scheduling.
- To assess the impact of different irrigation strategies on forage yield and quality.
Main Methods:
- Developed and validated Kc-NDVI models using satellite and UAV data during the 2023 and 2024 growing seasons.
- Implemented three irrigation strategies: conventional (ID1), satellite-based (ID2), and UAV-based (ID3).
- Assessed crop growth, forage yield, water productivity, and nutritional quality under each strategy.
Main Results:
- Both satellite and UAV NDVI models showed strong Kc relationships, with UAV models exhibiting higher calibration accuracy (R2 = 0.9414) than satellite models (R2 = 0.8278).
- UAV-based irrigation reduced water use by 23-30% but decreased crop growth, yield, and nutritional quality.
- Satellite-based irrigation scheduling maximized forage yield (59.8 t ha-1) and improved nutritional quality while maintaining water use efficiency.
Conclusions:
- While UAVs offer higher spatial detail, satellite-based irrigation scheduling provided a superior balance of water use, forage yield, and nutritional quality in this study.
- A stronger Kc-NDVI relationship does not automatically guarantee better irrigation scheduling outcomes.
- Satellite and UAV remote sensing can be complementary tools for precision irrigation, with careful consideration of trade-offs in resolution and scalability.
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