Recovery of tree trunk properties by extraction of Ground Penetrating Radar (GPR) attributes from 3-D GPR data

Saeed Parnow

School of Computing and Engineering

Supervisor:

Professor Fabio Tosti

School of Computing and Engineering

Dr Livia Lantini

School of Computing and Engineering

A full understanding of a tree’s health and structural soundness is essential for effective tree management, particularly when it comes to internal conditions. A promising non-destructive technique for assessing the underlying architecture of tree trunks is ground penetrating radar (GPR). Conventional GPR maps generated using a standard offset antenna array can be rapid, but they often suffer from non-uniqueness and confusion in their visual interpretation. However, when utilizing other GPR antenna arrays that can provide information such as velocity, permittivity, and electrical conductivity in the medium, the process of gathering and analysing the data becomes time-consuming. The period of study plays a vital role in performing tree assessment surveys, especially in large areas. This research presents an innovative method to improve tree management methods by extracting a local frequency attribute from conventional GPR to accurately evaluate the interior states of trees. We adopt a seismic approach to extract key features from GPR data, utilising advanced signal processing techniques. Subsequently, this characteristic is examined to deduce any internal structure, such as deterioration, cavities, and internal empty spaces within the trunks of trees. The proposed method aims to provide arborists and forestry specialists with relevant information regarding tree health, enabling them to carry out proactive management strategies and prompt treatments. The experimental results validate the effectiveness of the proposed method in enhancing the accuracy and productivity of tree assessment, consequently providing a significant boost to sustainable urban forestry and ecosystem conservation programmes.