Internal decays in trees can rapidly escalate into a full decomposition of the inner structural layer, i.e., the ``heartwood'' layer, due to the action of aggressive diseases and fungal infections. This process leads to the formation of big cavities and hollows, which remain surrounded by the sapwood layer only. Estimating the thickness of the sapwood layer with a high degree of accuracy is therefore crucial for correct assessment of the structural integrity of hollow trees, as well as an extremely challenging task. In this context, ground-penetrating radar (GPR) has proven effective in providing details of the internal structure of trees. Nevertheless, the existing GPR processing methods still offer limited information on their internal configuration. This study investigates the effectiveness of GPR enhanced by a microwave tomography inversion approach in the assessment of hollow trees. To this aim, a living hollow tree was investigated by performing a set of pseudocircular scans along the bark perimeter with a hand-held common-offset GPR system. The tree was then felled, and sections were cut for testing purposes. A dedicated data processing framework was developed and tested through numerical simulations of hollow tree sections. The internal structure of the real trunk was therefore reconstructed via a tomographic imaging approach and the outcomes were quantitatively analyzed by way of comparison with the real sections' main geometric features. The tomographic approach has proven very accurate in locating the sapwood-cavity interface and in the evaluation of the sapwood layer thickness, with a centimeter prediction accuracy.
|Number of pages||14|
|Journal||IEEE Transactions on Geoscience and Remote Sensing|
|Early online date||20 Oct 2021|
|Publication status||E-pub ahead of print - 20 Oct 2021|
- Ground-penetrating radar (GPR)
- hollow trees
- Microwave imaging
- Microwave measurement
- Microwave theory and techniques
- microwave tomography
- nondestructive testing (NDT)
- sapwood layer thickness
- tree health monitoring.