An Enhanced Data Processing Framework for Mapping Tree Root Systems Using Ground Penetrating Radar

Lantini, Livia ORCID: https://orcid.org/0000-0002-0416-1077, Tosti, Fabio ORCID: https://orcid.org/0000-0003-0291-9937, Giannakis, Iraklis, Zou, Lilong ORCID: https://orcid.org/0000-0002-5109-4866, Benedetto, Andrea and Alani, Amir (2020) An Enhanced Data Processing Framework for Mapping Tree Root Systems Using Ground Penetrating Radar. Remote Sensing. ISSN 2072-4292 (In Press)

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Abstract

The preservation of natural assets is nowadays an essential commitment. In this regard, root systems are endangered by fungal diseases which can undermine the health and stability of trees. Within this framework, Ground Penetrating Radar (GPR) is emerging as a reliable non-destructive method for root investigation. A coherent GPR-based root-detection framework is presented in this paper. The proposed methodology is a multi-stage data analysis system that is applied to semi-circular measurements collected around the investigated tree. In the first step, the raw data are processed by applying several standard and advanced signal processing techniques, to reduce noise-related information. In the second stage, the presence of any discontinuity element within the survey area is investigated by analysing the signal reflectivity. Then, a tracking algorithm aimed at identifying patterns compatible with tree roots is implemented. Finally, the mass density of roots is estimated by means of continuous functions, to achieve a more realistic representation of the root paths and to identify their length in a continuous and more realistic domain. The method was validated in a case study in London (UK), where the root system of a real tree was surveyed using GPR and a soil test pit was excavated for validation purposes. Results support the feasibility of the data processing framework implemented in this study.

Item Type: Article
Uncontrolled Keywords: Assessment of Tree Roots; Ground Penetrating Radar (GPR); Tree Root Mapping; Tree Root Mass Density; Multi-stage Data Processing Framework
Subjects: Construction and engineering > Civil and environmental engineering
Construction and engineering > Digital signal processing
Construction and engineering
Depositing User: Livia Lantini
Date Deposited: 17 Oct 2020 16:58
Last Modified: 17 Oct 2020 16:58
URI: http://repository.uwl.ac.uk/id/eprint/7406

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