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

Author:

Lantini LiviaORCID,Tosti FabioORCID,Giannakis Iraklis,Zou LilongORCID,Benedetto Andrea,Alani Amir M.

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 in order 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 in order 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.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Advancements in Using Deep Learning Methods for GPR Detection of Tree Roots;2023 12th International Workshop on Advanced Ground Penetrating Radar (IWAGPR);2023-07-05

2. Internal decay inspection of tree trunks using 3D point cloud and reverse time migration of ground penetrating radar data;NDT & E International;2023-07

3. An Investigation into Bark Detachment Disease in Tree Trunks Using Different GPR Antennas and Frequency Systems;2023 International Conference on Mechatronics, Control and Robotics (ICMCR);2023-02-18

4. A Depth-Adaptive Filtering Method for Effective GPR Tree Roots Detection in Tropical Area;IEEE Transactions on Instrumentation and Measurement;2023

5. Slice-Relation-Clustering Framework via Horizontal Angle Information for 3-D Tree Roots Reconstruction;IEEE Transactions on Geoscience and Remote Sensing;2023

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