A novel approach for estimating root orientation by surface fitting of the hyperbola signature

Abstract

In this study, we introduce a novel approach to determine root orientation from Ground Penetrating Radar (GPR) data, employing a dual-fitting strategy involving hyperbola fitting and polynomial regression surface fitting. The initial hyperbola fitting serves to capture essential parameters, while the subsequent polynomial regression surface fitting seeks to unveil nuanced relationships between root orientation angles and hyperbola characteristics. This dual-fitting framework represents a significant advancement in root analysis methodologies, offering a more refined and comprehensive understanding of root orientation derived from GPR data.