[Winter wheat growth spatial variation study based on temporal airborne high-spectrum images]

Area of Science:

• Agricultural Science
• Remote Sensing
• Environmental Science

Background:

• Precision agriculture optimizes resource use for profitability and environmental protection.
• Understanding crop spatial and temporal variations is key to effective management.
• Hyperspectral imaging offers detailed spectral information for crop monitoring.

Purpose of the Study:

• To investigate winter wheat growth spatial variance using push-broom hyperspectral imaging (PHI).
• To analyze the impact of variable-rate fertilization on crop growth and yield spatial variation.
• To evaluate the effectiveness of remote sensing for precision agriculture management.

Main Methods:

• Acquisition of three airborne PHI images during the 2002 winter wheat growing season.
• Contrast analysis between variable-rate and uniformity fertilization areas.
• Definition and analysis of six spectrum parameters sensitive to wheat growth variation.

Main Results:

• Spectral reflectance standard deviation increased in red edge and short infrared bands.
• Variable-rate fertilization initially increased parameter variation but later reduced it in filling and milking stages.
• Yield spatial variation coefficient was lower in the variable-rate area, though mean yield was also lower.

Conclusions:

• Airborne remote sensing images can accurately and timely capture crop growth spatial variance.
• Remote sensing provides powerful analytical tools for precision agriculture variable-rate management.
• Further research may optimize variable-rate strategies for improved yield outcomes.