Tomographs are increasingly used in advanced tree assessment. Their accuracy depends on accurately measured sensor positions (Rust 2017). For complex cross-sections, using the standard method based on electronic callipers, recording sensor positions is time consuming and, in rare cases, can even fail. Faster and easy to use methods could improve the quality of tomograms because users are more likely to record sensor positions accurately.
This study tested several alternative methods to measure sensor positions and compared them to results from electronic callipers. These are structure from motion, an infrared depth sensor, and pattern recognition. All methods proved to be highly accurate with results deviating less than 2% between methods.
Rust, S., 2017. Accuracy and reproducibility of acoustic tomography significantly increase with precision of sensor position. Journal of Forest and Landscape Research, 2 (1), 1–6.
Rust, S., 2020. Comparison of methods to measure sensor positions for tomography. Arboricultural Journal, 1–7.