Impact of Data Processing and Antenna Frequency on Spatial Structure Modelling of GPR Data

Area of Science:

• Geophysics
• Soil Science
• Agricultural Technology

Background:

• High-resolution geophysical techniques, like ground-penetrating radar (GPR), offer non-invasive soil water content assessment in agriculture.
• Complexity in GPR data processing currently limits its widespread adoption.

Purpose of the Study:

• To quantitatively analyze GPR data processing impacts on radar signals.
• To identify efficient and error-effective GPR data processing methods for subsurface feature detection.
• To evaluate GPR response across different operating frequencies using statistical and geostatistical methods.

Main Methods:

• Collected GPR data using 250, 600, and 1600 MHz antennas in a gravelly Italian soil.
• Applied six GPR data processing sequences of increasing complexity.
• Utilized statistical and geostatistical techniques for quantitative analysis.

Main Results:

• GPR data structure was independent of processing complexity at a fixed frequency.
• Increased processing complexity effectively reduced noise in GPR data.
• The optimal processing procedure was selected based on error-effectiveness.

Conclusions:

• GPR data processing optimization is crucial for accurate subsurface analysis in agriculture.
• Antenna frequency selection is critical and depends on the spatial scale of soil/subsoil processes.
• Simplified, efficient GPR processing can improve non-invasive soil water monitoring.