Performance of ground penetrating radar in root detection and its application in root diameter estimation under controlled conditions

2015 ◽  
Vol 59 (1) ◽  
pp. 145-155 ◽  
Author(s):  
Shan Wing Yeung ◽  
Wai Man Yan ◽  
Chi Hang Billy Hau
Keyword(s):  
Ground Penetrating Radar ◽  
Root Diameter ◽  
Controlled Conditions ◽  
Root Detection ◽  
Ground Penetrating

scholarly journals Advanced GPR Signal Processing Techniques for Root Detection in Urban Environments

2020 ◽  
Author(s):  
Livia Lantini ◽  
Fabio Tosti ◽  
Iraklis Giannakis ◽  
Kevin Jagadissen Munisami ◽  
Dale Mortimer ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Root Systems ◽  
Urban Environments ◽  
Street Trees ◽  
Destructive Testing ◽  
Root Detection ◽  
Charitable Trust ◽  
Ground Penetrating ◽  
Processing Techniques ◽  
Non Destructive

<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>

Modeling tree root diameter and biomass by ground-penetrating radar

2010 ◽  
Vol 54 (5) ◽  
pp. 711-719 ◽  
Author(s):  
XiHong Cui ◽  
Jin Chen ◽  
JinSong Shen ◽  
Xin Cao ◽  
XueHong Chen ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Root Diameter ◽  
Ground Penetrating

Ground-penetrating radar estimates of tree root diameter and distribution under field conditions

Trees ◽  
2018 ◽  
Vol 32 (6) ◽  
pp. 1657-1668 ◽  
Author(s):  
Keitaro Yamase ◽  
Toko Tanikawa ◽  
Masako Dannoura ◽  
Mizue Ohashi ◽  
Chikage Todo ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Root Diameter ◽  
Field Conditions ◽  
Ground Penetrating

Full three-dimensional imaging via ground penetrating radar: assessment in controlled conditions and on field for archaeological prospecting

2013 ◽  
Vol 115 (4) ◽  
pp. 1415-1422 ◽  
Author(s):  
Ilaria Catapano ◽  
Antonio Affinito ◽  
Gianluca Gennarelli ◽  
Francesco di Maio ◽  
Antonio Loperte ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Three Dimensional ◽  
Three Dimensional Imaging ◽  
Controlled Conditions ◽  
Ground Penetrating

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 ◽  
...  
Keyword(s):  
Leaf Litter ◽  
Plant Species ◽  
Ground Penetrating Radar ◽  
Root Detection ◽  
Ground Penetrating

scholarly journals Evaluation of a Ground Penetrating Radar to Map the Root Architecture of HLB-infected Citrus Trees

Agronomy ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 354 ◽  
Author(s):  
Zhang ◽  
Derival ◽  
Albrecht ◽  
Ampatzidis
Keyword(s):  
Ground Penetrating Radar ◽  
Crop Production ◽  
Field Experiments ◽  
Structural Characteristics ◽  
Root Diameter ◽  
Moisture Level ◽  
Limiting Factors ◽  
Horizontal Distance ◽  
Tree Root System ◽  
Ground Penetrating

This paper investigates the influences of several limiting factors on the performance of ground penetrating radar (GPR) in accurately detecting huanglongbing (HLB)-infected citrus roots and determining their main structural characteristics. First, single-factor experiments were conducted to evaluate GPR performance. The factors that were evaluated were (i) root diameter; (ii) root moisture level; (iii) root depth; (iv) root spacing; (v) survey angle; and, (vi) soil moisture level. Second, two multi-factor field experiments were conducted to evaluate the performance of the GPR in complex orchard environments. The GPR generated a hyperbola in the radar profile upon root detection; the diameter of the root was successfully determined according to the width of the hyperbola when the roots were larger than 6 mm in diameter. The GPR also distinguished live from dead roots, a capability that is indispensable for studying the effects of soil-borne and other diseases on the citrus tree root system. The GPR can distinguish the roots only if their horizontal distance is greater than 10 cm and their vertical distance is greater than 5 cm if two or more roots are in proximity. GPR technology can be applied to determine the efficacy of advanced crop production strategies, especially under the pressures of disease and environmental stresses.

scholarly journals Application and Algorithm of Ground-Penetrating Radar for Plant Root Detection: A Review

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2836
Author(s):  
Hao Liang ◽  
Linyin Xing ◽  
Jianhui Lin
Keyword(s):  
Machine Learning ◽  
Ground Penetrating Radar ◽  
Plant Root ◽  
Plant Roots ◽  
Time Machine ◽  
Close Attention ◽  
Detection Algorithms ◽  
Detection Technology ◽  
Root Detection ◽  
Ground Penetrating

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.

scholarly journals A Novel Method of Hyperbola Recognition in Ground Penetrating Radar (GPR) B-Scan Image for Tree Roots Detection

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1019
Author(s):  
Xiaowei Zhang ◽  
Fangxiu Xue ◽  
Zepeng Wang ◽  
Jian Wen ◽  
Cheng Guan ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Synthetic Data ◽  
Position Estimation ◽  
Tree Roots ◽  
Symmetry Test ◽  
Root Detection ◽  
Testing Technology ◽  
Root Position ◽  
Novel Method ◽  
Ground Penetrating

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.

scholarly journals Ground-penetrating Radar to Detect and Quantify Residual Root Fragments Following Peach Orchard Clearing

2005 ◽  
Vol 15 (3) ◽  
pp. 600-607 ◽  
Author(s):  
K.D. Cox ◽  
H. Scherm ◽  
N. Serman
Keyword(s):  
Ground Penetrating Radar ◽  
High Amplitude ◽  
Root Diameter ◽  
Root Disease ◽  
Burial Depth ◽  
Pixel Intensity ◽  
Land Clearing ◽  
Armillaria Root Disease ◽  
Ground Penetrating ◽  
Peach Orchard

Consecutive replanting of peach (Prunus persica) trees on the same orchard site can result in various replant problems and diseases, including armillaria root disease (Armillaria spp.), which develops upon contact between the roots of newly planted trees and infested residual root pieces in the soil. There is little information regarding the quantity of roots remaining in stone fruit orchards following tree removal and land clearing. We investigated the utility of ground-penetrating radar (GPR) to characterize reflector signals from peach root fragments in a controlled burial experiment and to quantify the amount of residual roots remaining after typical commercial orchard clearing. In the former experiment, roots ranging from 2.5 to 8.2 cm in diameter and buried at depths of 11 to 114 cm produced characteristic parabolic reflector signals in radar profiles. Image analysis of high-amplitude reflector area indicated significant linear relationships between signal strength (mean pixel intensity) and root diameter (r = -0.517; P = 0.0097; n = 24) or the combined effects of root diameter and burial depth, expressed though a depth × diameter term (r = -0.630; P = 0.0010; n = 24). In a peach orchard in which trees and roots had been removed following typical commercial practice (i.e., trees were pushed over, burned, and tree rows subsoiled), a GPR survey of six 4 × 8-m plots revealed that the majority of reflector signals indicative of root fragments were located in the upper 30 to 40 cm of soil. Based on ground-truth excavation of selected sites within plots, reflectors showing a strong parabolic curvature in the radar profiles corresponded to residual root fragments with 100% accuracy, whereas those displaying a high amplitude area represented roots in 86.1% of the cases. By contrast, reflectors with both poor curvature and low amplitude yielded roots for less than 10% of the excavated sites, whereas randomly selected sites lacking reflector signals were devoid of any roots or other subsurface objects. A high level of variability in the number of residual roots was inferred from the radar profiles of the six plots, indicating an aggregated distribution of root fragments throughout the field. The data further indicated that at least one residual root fragment would be present per cubic meter of soil, and that many of these fragments have diameters corresponding to good to excellent inoculum potential for armillaria root disease. Further GPR surveys involving different levels of land clearing, combined with long-term monitoring of armillaria root disease incidence in replanted trees, will be necessary to ascertain the disease threat posed by the levels of residual root biomass observed in this study.

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