Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm Article Swipe
Minghe Zhang
,
Xuan Feng
,
Maksim Bano
,
Cai Liu
,
Qian Liu
,
Xiaogang Wang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/vzj2.20379
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/vzj2.20379
Soil water content (SWC) estimation is important for many areas including hydrology, agriculture, soil science, and environmental science. Ground penetrating radar (GPR) is a promising geophysical method for SWC estimation. However, at present, most of the studies are based on partial information of GPR, like travel time or amplitude information, to invert the SWC. Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. The proposed scheme includes a petrophysical relationship to link the SWC with the relative dielectric permittivity, 1D GPR forward modeling, and a GWO optimization algorithm. First, numerical modeling was carried out, and the proposed scheme was applied to both noise‐free and noisy data to verify its applicability. Then, the proposed method was applied to data collected from a field experimental site. These results, derived from both synthetic and real datasets, show that the proposed inversion scheme resulted in a good match between the observed and calculated GPR data. In the numerical modeling, it was observed that the SWC could be inverted accurately, even when noise was present in the data. These demonstrate that the GWO method can be applied for the quantitative interpretation of GPR data. The proposed scheme shows potential for SWC estimation by using GPR full waveform data.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/vzj2.20379
- OA Status
- gold
- Cited By
- 6
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402530847
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4402530847Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/vzj2.20379Digital Object Identifier
- Title
-
Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-12Full publication date if available
- Authors
-
Minghe Zhang, Xuan Feng, Maksim Bano, Cai Liu, Qian Liu, Xiaogang WangList of authors in order
- Landing page
-
https://doi.org/10.1002/vzj2.20379Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1002/vzj2.20379Direct OA link when available
- Concepts
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Ground-penetrating radar, Inversion (geology), Waveform, Radar, Algorithm, Remote sensing, Estimation theory, Computer science, Soil science, Geology, Seismology, Tectonics, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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59Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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