Reverse-time migration for evaluating the internal structure of tree-trunks using ground-penetrating radar

Lists

Alani, Amir, Giannakis, Iraklis, Zou, Lilong ORCID: https://orcid.org/0000-0002-5109-4866, Lantini, Livia ORCID: https://orcid.org/0000-0002-0416-1077 and Tosti, Fabio ORCID: https://orcid.org/0000-0003-0291-9937 (2020) Reverse-time migration for evaluating the internal structure of tree-trunks using ground-penetrating radar. NDT & E International. ISSN 0963-8695

[thumbnail of Alani_etal_2020_NDT&E_Int_-_Reverse-time_migration_for_evaluating_the_internal_structure_of_tree-trunks_using_ground-penetrating_radar.pdf]

Preview

PDF
Alani_etal_2020_NDT&E_Int_-_Reverse-time_migration_for_evaluating_the_internal_structure_of_tree-trunks_using_ground-penetrating_radar.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Download (1MB) | Preview

Official URL: https://doi.org/10.1016/j.ndteint.2020.102294

Abstract

Modern socioeconomic factors such as global timber trade and international travelling have contributed to the rapid increase of Emerging Infectious Diseases (EIDs) of trees with devastating effects to the European forests and woodlands. To that extent, numerous non-destructive methodologies have been suggested as diagnostic tools in order to effectively monitor and maintain potential outbreaks. Ground-penetrating radar (GPR) is an appealing method for tree monitoring as it provides with a trivially deployable and efficient detection tool, suitable for large-scale forestry applications. Nonetheless, traditional GPR approaches are tuned for surface measurements and they are not compatible with the unique measurement configurations associated with forestry applications. Within that context, we present a novel-processing framework, which is capable of addressing features with irregular measurements on closed surfaces. A positioning method is described that exploits a wheel-measuring device in order to accurately associate each A-Scan with its corresponding coordinates. In addition, a processing pipeline is presented that aims at eliminating the ringing noise due to the layered nature of the trees. Lastly, a reverse-time migration is applied to the processed B-Scan in order to effectively map the reflectors present within the trunk. The suggested scheme is successfully tested in both numerical and real-field experiments, indicating the validity of the current approach.

Item Type:	Article
Identifier:	10.1016/j.ndteint.2020.102294
Keywords:	Ground penetrating radar (GPR), tree health monitoring, migration, tree, decay, emerging infectious diseases (EIDs)
Subjects:	Construction and engineering > Civil and environmental engineering Construction and engineering > Digital signal processing Construction and engineering > Electrical and electronic engineering
Related URLs:	Publisher
Depositing User:	Fabio Tosti
Date Deposited:	08 Jul 2020 16:47
Last Modified:	06 Feb 2024 16:03
URI:	https://repository.uwl.ac.uk/id/eprint/7168

Downloads

Downloads per month over past year

Actions (login required)

View Item

References

[1] A. Broome, D. Ray, R. Mitchell and R. Harmer, ”Responding to ash dieback (Hymenoscyphus fraxineus) in the UK: woodland composition and replacement tree species,” Forestry, An International Journal of Forest Research, vol. 92, pp. 108–119, 2019.
[2] A. Santini, L. Ghelardini, C. De Pace, [...] and J. Stenlid, ”Biogeographical patterns and determinants of invasion by forest pathogens in Europe,” New Phytologist, vol. 197, pp. 238-250, 2012.
[3] A. M. Ellison, M. S. Bank, B. D. Clinton, [...] and J. R. Webster, ”Loss of foundation species: consequences for the structure and dynamics of forested ecosystem,” The Ecological Society of America, vol. 3, pp. 479-486, 2005.
[4] S. A. Anagnostakis, ”Chestnut blight: the classical problem of an introduced pathogen,” Mycologia, vol. 79, pp. 23-37, 1987.
[5] Q. Guo, M. Rejmanek and J. Wen, ”Geographical, socioeconomic and ecological determinants of exotic plant naturalization in the United States: insights and updates from improved data,” NeoBiota, vol. 12, pp. 41-55, 2012.
[6] J. J. Stocks, R. J. A. Buggs and S. J. Lee, ”A first assessment of Fraxinus excelsion (common ash) susceptibility to Hymenoscyphus fraxineus (ash dieback) throughout the British Isles,” Nature, Scientific Reports, vol. 7, 2017.
[7] R. Worrell, “An Assessment of the Potential Impacts of Ash Dieback in Scotland,” Available online: https: //bit.ly/2ZkYhNc (accessed on 30 August 2019)
[8] N. Brown, “Epidemiology of Acute Oak Decline in Great Britain,” Available online: https://spiral.imperial.ac. uk/handle/10044/1/30827 (accessed on 30 August 2019).
[9] S. Denman, N. Brown, S. Kirk, M. Jeger and J. Webber, ”A description of the symptoms of Acute Oak Decline in Britain and a comparative review on causes of similar disorders on oak in Europe,” Forestry, vol. 87, pp. 535-551, 2014.
[10] A. M. Ellison, M. S. Bank, B. D. Clinton, [...] and J. R. Webster, ”Loss of foundation species: consequences for the structure and dynamics of forested ecosystem,” The Ecological Society of America, vol. 3, pp. 479-486, 2005.
[11] W. C. Shortle and K. R. Dudzik, Wood Decay in Living and Dead Trees: A Pictorial Overview, U.S. FOREST SERVICE, 2012.
[12] P.M.W.Xu and R.Wimmer,”Application of a drill resistance technique for density profile measurement in wood composite panels,” Forest Prod. J., vol. 45, pp. 90-93, 1995.
[13] W. Moore, ”The combined use of the RESISTOGRAPH and the Shigometer for the accurate mapping and diagnosis of the internal condition of wood support orangs of trees,” Arboricultural J., vol. 23, pp. 273–287, 1999.
[14] V.Bucur. Nondestructive Characterization and Imaging of Wood. Berlin, Germany: Springer, 2003.
[15] Lantini, L., Holleworth, R., Egyir, D., Giannakis, I., Tosti, F., and Alani, A.M. (2018). Use of Ground Penetrating Radar for Assessing Interconnections between Root Systems of Different Matured Tree Species. In: Proc of the IEEE International Conference on Metrology for Archaeology and Cultural Heritage (MetroArchaeo 2018), Cassino, Italy, October 22-24, 2018.
[16] A. Guyot, K.T. Ostergaard, M. Lenkopane, J. Fanand, D.A. Lockington, ”Using electrical resistivity tomography to differentiate sapwood from heartwood: application to conifers,” Tree Physiology, vol. 33, pp. 187– 194, 2013.
[17] C. J. Lin and T. H. Yang, ”Detection of acoustic velocity and electrical resistance tomographies for evaluation of peripheral-inner wood demarcation in urban royal palms,” Urban Forestry and Urban Greening, vol. 14, pp. 583-589, 2015.
[18] I. Giannakis, G. Tosti, L. Lantini and A. Alani, ”Health monitoring of tree-trunks using ground penetrating radar,” IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 10, pp. 8317-8326, 2019.
[19] J. Jezova, L. Mertens and S. Lambot, ”Ground-penetrating radar for observing tree trunks and other cylindrical objects,” Construction and Building Materials, vol. 123, pp. 214–225, 2016.
[20] J. Jezova, J. Harou and S. Lambot, ”Reflection waveforms occurring in bistatic radar testing of columns and tree trunks,” Construction and Building Materials, vol. 174, pp. 388-400, 2018.
[21] X. Xiao, J. Wen, Z. Xiao and W. Li, ”Detecting and measuring internal anomalies in tree trunks using radar data for layer identification,” Journal of Sensors, vol. 2018, pp. 1-11, 2018.
[22] G. Leucci, N. Masini, R. Persico and F. Soldovieri, “GPR and sonic tomography for structural restoration: The case of the cathedral of Tricarico,” J. Geophys. Eng. vol. 8, pp. S76–S92, 2011.
[23] M. Pastorino, Microwave Imaging, John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2010.
[24] A. M. Alani, F. Soldovieri, I. Catapano, I. Giannakis, G. Gennarelli, L. Lantini, G. Ludeno and F. Tosti, “The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks,” Remote Sensing, 2019.
[25] D. J. Daniels, Ground Penetrating Radar, 2nd ed. London, U.K.: Institution of 563 Engineering and Technology, 2004.
[26] J. Schofield, D. Daniels and P. Hammerton, ”A Multiple Migration and Stacking Algorithm Designed for Land Mine Detection,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 11, pp. 6983-6988, 2014.
[27] M. A. Gonzlez-Huici, I. Catapano and F. Soldovieri, ”A Comparative Study of GPR Reconstruction Approaches for Landmine Detection,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 12, pp. 4869-4878, 2014
[28] X. Feng, M. Sato, C. Liu and Y. Zhang, ”Profiling the Rough Surface by Migration,” IEEE Geoscience and Remote Sensing Letters, vol. 6, no.2, pp. 258-262, April 2009
[29] I. Giannakis, F. Tosti, L. Lantini, D. Egyir and A. M. Alani, “Signal Processing For Tree-Trunk Investigation Using Ground Penetrating Radar,” in Proc. Of 10th Workshop on Advanced Ground Penetrating Radar, Netherlands, 2019.
[30] C. J. Leuschen and R. G. Plumb, ”A matched-filter-based reverse-time migration algorithm for ground-penetrating radar data,” IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 5, pp. 929-936, 2001.
[31] R. J. Sharpe and R. W. Thorne, “Numerical method for extracting an arc length parameterization from parametric curves,” Comput.-Aided Des., vol. 14, no. 2, pp. 79–81, 1982.
[32] B. Guenter and R. Parent, “Computing the arc length of parametric curves,” IEEE Comput. Graph. Appl., vol. 10, no. 3, pp. 72–78, 1990.
[33] I. Giannakis, A. Giannopoulos, and C. Warren, “Realistic FDTD GPR antenna models 588 optimized using a novel linear/nonlinear full- waveform inversion,” IEEE Trans. Geosci. Remote Sens., vol. 57, no. 3, pp. 1768-1778, Mar. 2019.
[34] A. Taflove and S. C. Hagness, Computational Electrodynamics: The Finite-Difference Time-Domain Method, 2nd ed. Norwood, MA, USA: Artech House, 2000.
[35] C. Warren, A. Giannopoulos, and I. Giannakis, “gprMax: Open source software to simulate electromagnetic wave propagation for ground penetrating radar,” Comput. Phys. Commun., vol. 209, pp. 163–170, Dec. 2016.
[36] C. Warren et al., “A CUDA-based GPU engine for gprMax: Open source FDTD electromagnetic simulation software,” Comput. Phys. Commun., vol. 237, pp. 208-218, Apr. 2019. 598
[37] S. M, Nixon and A. S. Aguado. Feature Extraction and Image Processing for Computer Vision. Academic Press, 2008.
[38] D. F. Kelley, T. J. Destan, and R. J. Luebbers, “Debye function expansions of complex permittivity using a hybrid particle swarm-least squares optimization approach,” IEEE Trans. 602 Antennas Propag., vol. 55, no. 7, pp. 1999–2005, 2007.

Tools

CORE (COnnecting REpositories)

The University of West London

Reverse-time migration for evaluating the internal structure of tree-trunks using ground-penetrating radar

Abstract

Downloads

Actions (login required)

Menu