Invasive fungi diseases are considered one the biggest threats for the ash and oak forests in United Kingdom. To that extend, Ground Penetrating Radar (GPR) can provide a powerful diagnostic tool for assessing the health status of tree trunks based on their internal dielectric distribution. GPR acquisitions in tree-trunks is a unique problem that can not be approached with traditional GPR processing approaches. Typical interpretation tools like hyperbola fitting and migration should be adjusted and fine-tuned in order to be applicable for irregular measurements in a closed curve. The purpose of this paper is to provide GPR practitioners with a set of interpretation tools that can be applied in the field using commercial GPR antennas. In that context, a novel processing framework is presented that is fine-tuned for the current problem. The suggested scheme is successfully tested using both numerical and real data indicating the capabilities of GPR as a diagnostic tool for early detection of tree diseases.
Giannakis, I., Tosti, F., Lantini, L., Egyir, D., Alani, A.M. (2019). Signal processing for tree-trunk investigation using ground penetrating radar. In 10th International Workshop on Advanced Ground Penetrating Radar, Held at Near Surface Geoscience Conference and Exhibition 2019, NSG 2019.
Signal processing for tree-trunk investigation using ground penetrating radar
F. Tosti;
2019-01-01
Abstract
Invasive fungi diseases are considered one the biggest threats for the ash and oak forests in United Kingdom. To that extend, Ground Penetrating Radar (GPR) can provide a powerful diagnostic tool for assessing the health status of tree trunks based on their internal dielectric distribution. GPR acquisitions in tree-trunks is a unique problem that can not be approached with traditional GPR processing approaches. Typical interpretation tools like hyperbola fitting and migration should be adjusted and fine-tuned in order to be applicable for irregular measurements in a closed curve. The purpose of this paper is to provide GPR practitioners with a set of interpretation tools that can be applied in the field using commercial GPR antennas. In that context, a novel processing framework is presented that is fine-tuned for the current problem. The suggested scheme is successfully tested using both numerical and real data indicating the capabilities of GPR as a diagnostic tool for early detection of tree diseases.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
