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The study aims to develop a UAV-based framework for accurately retrieving canopy temperature and supporting irrigation decisions in tea plantations.

August 9, 2026SensorsOpen Access

UAV-Based Thermal Inversion for Canopy Temperature Retrieval and Precision Irrigation

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The study aims to develop a UAV-based framework for accurately retrieving canopy temperature and supporting irrigation decisions in tea plantations.
Developed a UAV-based thermal infrared framework for canopy temperature retrieval.
Utilized multi-frame image mosaicking and threshold-based canopy extraction techniques.
Calculated Crop Water Stress Index (CWSI) and estimated irrigation requirements based on a defined threshold strategy.
Achieved a maximum absolute error of less than 0.3 °C using the gray-temperature calibration model.
CWSI and estimated irrigation requirements showed a strong correlation with stomatal conductance (R2 up to 0.91).
Demonstrated a practical workflow for UAV thermal imagery acquisition to support irrigation decision-making.

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Randomized trial develops a UAV-based method for canopy temperature retrieval in tea plantations, suggesting improvements for precision irrigation.

Li et al. (2026) studied this question.

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Randomized trial develops a UAV-based method for canopy temperature retrieval in tea plantations, suggesting improvements for precision irrigation.