Trunk Health Condition Inspection Using Integrated 3-D Photogrammetry and Holographic Radar Tomography

Forests are vital components of the ecosystem of the Earth, regulating climate, conserving soil and water, and fostering biodiversity. Sustainable forest management offers crucial long-term benefits, but challenges such as disease threaten tree health. Disease-infected trees in both forests and urban areas pose risks to safety, property, and culture, leading to economic losses. Traditional inspection methods, such as resistance drilling, are invasive and laborious, while nondestructive techniques such as ground penetrating radar (GPR), offer promising alternatives. Although GPR shows potential, complexities such as tree structure and electromagnetic properties hinder accurate disease detection. In order to address these challenges, a new approach integrates structure-from-motion (SfM) photogrammetry with GPR measurement, and a novel holographic radar tomography processing approach has been proposed in this article. These methodologies accurately reconstruct tree trunks in 3-D, enabling precise GPR positioning and the obtaining of trunk permittivity. An arc-shaped Kirchhoff migration algorithm, moreover, helps mitigate irregular trunk shapes, enhancing data accuracy. The proposed framework demonstrates efficacy in real-tree measurement, offering high-precision disease monitoring. This innovation not only aids in preserving biodiversity but also enhances ecosystem services by promoting sustainable forest management. Effective disease monitoring ensures timely intervention, safeguarding valuable old trees and ecosystems while minimizing economic and cultural losses.