Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163111
Title: Tree roots reconstruction framework for accurate positioning in heterogeneous soil
Authors: Luo, Wenhao
Lee, Yee Hui
Sun, Hai-Han
Ow, Lai Fern
Mohamed Lokman Mohd Yusof
Yucel, Abdulkadir C.
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Luo, W., Lee, Y. H., Sun, H., Ow, L. F., Mohamed Lokman Mohd Yusof & Yucel, A. C. (2022). Tree roots reconstruction framework for accurate positioning in heterogeneous soil. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 1912-1925. https://dx.doi.org/10.1109/JSTARS.2022.3151869
Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Abstract: Ground-penetrating radar has recently found wide application in the underground imaging of tree roots. However, ignoring the random and complex nature of the heterogeneous soil and assuming the soil's relative permittivity constant throughout the survey region may yield an inaccurate tree root positioning. Meanwhile, the incompatible relative soil permittivity results in low image quality of the roots reconstruction. Furthermore, the soil's spatial heterogeneity introduces unwanted environmental clutter in the mapping of the tree root. A data processing framework is proposed to address these issues for retrieving the tree roots in heterogeneous soil environments. The proposed framework combines four techniques to be applied consecutively: First, a hyperbola extraction method based on a column-connection clustering algorithm is used to extract individual hyperbolae in B-scans, eliminate mutual influence in the process, and suppress noise. Second, an improved Hough transform technique is adopted to estimate the equivalent permittivity of each root's surrounding soil environment for each extracted hyperbola. Third, individual root restoration is done by transferring each hyperbola to a spot using its corresponding soil equivalent permittivity. Finally, individually restored features are combined in the final image. The images obtained via the proposed framework show a well reconstructed two-dimensional tree roots scenario. The applicability and the effectiveness of the proposed framework have been demonstrated through numerical simulations and field measurements.
URI: https://hdl.handle.net/10356/163111
ISSN: 1939-1404
DOI: 10.1109/JSTARS.2022.3151869
Rights: © 2022 The authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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