Health assessment of trees using GPR-derived root density maps

Lantini, Livia, Tosti, Fabio, Giannakis, Iraklis, Zou, Lilong, Egyir, Daniel, Mortimer, Dale and Alani, Amir (2020) Health assessment of trees using GPR-derived root density maps. In: IEEE Radar Conference 2020; 21-25 Sep 2020, Florence, Italy.


In this paper, a coherent framework for estimating the density and the distribution of roots using ground penetrating radar is presented. The proposed methodology is a multi-stage data processing scheme that is applied in semi-circular measurements collected concentrically around the investigated tree. The adopted processing methodology consists of three distinct and sequential steps. In the first step, the raw B-scans are subject to time-zero correction, zero-offset removal, time-varying gain and the singular value decomposition (SVD) filter. The SVD filter is used in order to effectively eliminate multiples and ringing noise from the B-Scans and increase the overall signal-to-clutter ratio. The second step consists of a tracking algorithm that aims at identifying patterns that resemble tree roots. In the last step, a continuous function is fitted to each root in order to effectively interpolate between points and subsequently estimate the density of the roots. This paper concludes with a case study on an urban tree at the Gunnersbury Park, London, United Kingdom. The top soil around the tree was excavated to 40 cm below the surface approximately in order to expose the tree root architecture. Then the exposed tree root system was used to compare the survey results for validity purposes and ultimately support the viability of the proposed data processing methods adopted in this investigation.

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