Abstract

Aggressive fungal and insect attacks have reached an alarming level, threatening a variety of tree species, such as ash and oak trees, in the United Kingdom and beyond. In this context, Ground Penetrating Radar (GPR) has proven to be an effective non-invasive tool, capable of generating information about the inner structure of tree trunks in terms of existence, location, and geometry of defects. Nevertheless, it had been observed that the currently available and known GPR-related processing and data interpretation methods and tools are able to provide only limited information regarding the existence of defects and anomalies within the tree inner structure. In this study, we present a microwave tomographic approach for improved GPR data processing with the aim of detecting and characterising the geometry of decay and cavities in trees. The microwave tomographic approach is able to pinpoint explicitly the position of the measurement points on the tree surface and thus to consider the actual geometry of the sections beyond the classical (circular) ones. The robustness of the microwave tomographic approach with respect to noise and data uncertainty is tackled by exploiting a regularised scheme in the inversion process based on the Truncated Singular Value Decomposition (TSVD). A demonstration of the potential of the microwave tomography approach is provided for both simulated data and measurements collected in controlled conditions. First, the performance analysis was carried out by processing simulated data achieved by means of a Finite-Difference Time-Domain (FDTD) in three scenarios characterised by different geometric trunk shapes, internal trunk configurations and target dimensions. Finally, the method was validated on a real trunk by proving the viability of the proposed approach in identifying the position of cavities and decay in tree trunks.

Highlights

  • Swift and effective tree health monitoring and assessment is crucial for the protection of ecosystems and the maintenance of sustainable climate conditions [1]

  • We present a microwave tomographic approach for improved Ground Penetrating Radar (GPR) data processing with the aim of detecting and characterising the geometry of decay and cavities in trees

  • The robustness of the microwave tomographic approach with respect to noise and data uncertainty is tackled by exploiting a regularised scheme in the inversion process based on the Truncated Singular Value Decomposition (TSVD)

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Summary

Introduction

Swift and effective tree health monitoring and assessment is crucial for the protection of ecosystems and the maintenance of sustainable climate conditions [1]. The consequence of a spread of EIDs is dramatic, as these infections are on the rise [11] and can result in the complete extinction of certain tree species [12]. This operation consisted of replacing every single A-scan of the radargram with the difference between the single A-scan value and the average value of all the A-scans in the radargram. In order to compensate this effect, a gain variable versus the depth distance is applied to the raw data. No window functions have been applied to the time domain pre-processed data before conversion into frequency domain data

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