Leaf litter thickness, but not plant species, can affect root detection by ground penetrating radar

2016 ◽  
Vol 408 (1-2) ◽  
pp. 271-283 ◽  
Author(s):  
Toko Tanikawa ◽  
Hidetoshi Ikeno ◽  
Masako Dannoura ◽  
Keitarou Yamase ◽  
Kenji Aono ◽  
...  
2020 ◽  
Author(s):  
Livia Lantini ◽  
Fabio Tosti ◽  
Iraklis Giannakis ◽  
Kevin Jagadissen Munisami ◽  
Dale Mortimer ◽  
...  

<p>Street trees are widely recognised to be an essential asset for the urban environment, as they bring several environmental, social and economic benefits [1]. However, the conflicting coexistence of tree root systems with the built environment, and especially with road infrastructures, is often cause of extensive damage, such as the uplifting and cracking of sidewalks and curbs, which could seriously compromise the safety of pedestrians, cyclists and drivers.</p><p>In this context, Ground Penetrating Radar (GPR) has long been proven to be an effective non-destructive testing (NDT) method for the evaluation and monitoring of road pavements. The effectiveness of this tool lies not only in its ease of use and cost-effectiveness, but also in the proven reliability of the results provided. Besides, recent studies have explored the capability of GPR in detecting and mapping tree roots [2]. Algorithms for the reconstruction of the tree root systems have been developed, and the spatial variations of root mass density have been also investigated [3].</p><p>The aim of this study is, therefore, to investigate the GPR potential in mapping the architecture of root systems in street trees. In particular, this research aims to improve upon the existing methods for detection of roots, focusing on the identification of the road pavement layers. In this way, different advanced signal processing techniques can be applied at specific sections, in order to remove reflections from the pavement layers without affecting root detection. This allows, therefore, to reduce false alarms when investigating trees with root systems developing underneath road pavements.</p><p>In this regard, data from trees of different species have been acquired and processed, using different antenna systems and survey methodologies, in an effort to investigate the impact of these parameters on the GPR overall performance.</p><p> </p><p><strong>Acknowledgements</strong></p><p>The authors would like to express their sincere thanks and gratitude to the following trusts, charities, organisations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook Trust, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation, and The Wyfold Charitable Trust. This paper is dedicated to the memory of our colleague and friend Jonathan West, one of the original supporters of this research project.</p><p> </p><p><strong>References</strong></p><p>[1] J. Mullaney, T. Lucke, S. J. Trueman, 2015. “A review of benefits and challenges in growing street trees in paved urban environments,” Landscape and Urban Planning, 134, 157-166.</p><p>[2] A. M. Alani, L. Lantini, 2019. “Recent advances in tree root mapping and assessment using non-destructive testing methods: a focus on ground penetrating radar,” Surveys in Geophysics, 1-42.</p><p>[3] L. Lantini, F. Tosti, Giannakis, I., Egyir, D., A. Benedetto, A. M. Alani, 2019. “A Novel Processing Framework for Tree Root Mapping and Density Estimation using Ground Penetrating Radar,” In 10th International Workshop on Advanced Ground Penetrating Radar, EAGE.</p>


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2836
Author(s):  
Hao Liang ◽  
Linyin Xing ◽  
Jianhui Lin

Attention to the natural environment is equivalent to observing the space in which we live. Plant roots, which are important organs of plants, require our close attention. The method of detecting root system without damaging plants has gradually become mainstream. At the same time, machine learning has been achieving good results in recent years; it has helped develop many tools to help us detect the underground environment of plants. Therefore, this article will introduce some existing content related to root detection technology and machine detection algorithms for root detection, proving that machine learning root detection technology has good recognition capabilities.


Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1019
Author(s):  
Xiaowei Zhang ◽  
Fangxiu Xue ◽  
Zepeng Wang ◽  
Jian Wen ◽  
Cheng Guan ◽  
...  

Ground penetrating radar (GPR), as a newly nondestructive testing technology (NDT), has been adopted to explore the spatial position and the structure of the tree roots. Due to the complexity of soil distribution and the randomness of the root position in the natural environment, it is difficult to locate the root in the GPR B-Scan image. In this study, a novel method for root detection in the B-scan image by considering both multidirectional features and symmetry of hyperbola was proposed. Firstly, a mixed dataset B-Scan images were employed to train Faster RCNN (Regions with CNN features) to obtain the potential hyperbola region. Then, the peak area and its connected region were filtered from the four directional gradient graphs in the proposed region. The symmetry test was applied to segment the intersecting hyperbolas. Finally, two rounds of coordinate transformation and line detection based on Hough transform were employed for the hyperbola recognition and root radius and position estimation. To validate the effectiveness of this approach for tree root detection, a mixed dataset was made, including synthetic data from gprMax as well as field data collected from 35 ancient tree roots and fresh grapevine controlled experiments. From the results of hyperbola recognition as well as the estimation for the radius and position of the root, our method shows a significant effect in root detection.


2012 ◽  
Vol 362 (1-2) ◽  
pp. 1-23 ◽  
Author(s):  
Li Guo ◽  
Jin Chen ◽  
Xihong Cui ◽  
Bihang Fan ◽  
Henry Lin

Author(s):  
M. S. Sudakova ◽  
M. L. Vladov ◽  
M. R. Sadurtdinov

Within the ground penetrating radar bandwidth the medium is considered to be an ideal dielectric, which is not always true. Electromagnetic waves reflection coefficient conductivity dependence showed a significant role of the difference in conductivity in reflection strength. It was confirmed by physical modeling. Conductivity of geological media should be taken into account when solving direct and inverse problems, survey design planning, etc. Ground penetrating radar can be used to solve the problem of mapping of halocline or determine water contamination.


2017 ◽  
Vol 3 (1) ◽  
pp. 73-83
Author(s):  
Rahmayati Alindra ◽  
Heroe Wijanto ◽  
Koredianto Usman

Ground Penetrating Radar (GPR) adalah salah satu jenis radar yang digunakan untuk menyelidiki kondisi di bawah permukaan tanah tanpa harus menggali dan merusak tanah. Sistem GPR terdiri atas pengirim (transmitter), yaitu antena yang terhubung ke generator sinyal dan bagian penerima (receiver), yaitu antena yang terhubung ke LNA dan ADC yang kemudian terhubung ke unit pengolahan data hasil survey serta display sebagai tampilan output-nya dan post  processing untuk alat bantu mendapatkan informasi mengenai suatu objek. GPR bekerja dengan cara memancarkan gelombang elektromagnetik ke dalam tanah dan menerima sinyal yang dipantulkan oleh objek-objek di bawah permukaan tanah. Sinyal yang diterima kemudian diolah pada bagian signal processing dengan tujuan untuk menghasilkan gambaran kondisi di bawah permukaan tanah yang dapat dengan mudah dibaca dan diinterpretasikan oleh user. Signal processing sendiri terdiri dari beberapa tahap yaitu A-Scan yang meliputi perbaikan sinyal dan pendektesian objek satu dimensi, B-Scan untuk pemrosesan data dua dimensi  dan C-Scan untuk pemrosesan data tiga dimensi. Metode yang digunakan pada pemrosesan B-Scan salah satunya adalah dengan  teknik pemrosesan citra. Dengan pemrosesan citra, data survey B-scan diolah untuk didapatkan informasi mengenai objek. Pada penelitian ini, diterapkan teori gradien garis pada pemrosesan citra B-scan untuk menentukan bentuk dua dimensi dari objek bawah tanah yaitu persegi, segitiga atau lingkaran. 


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