Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand
A subsurface soil moisture retrieval algorithm, using a pathfinder simultaneously acquired P- and L-band radar data over forested areas, is proposed in this article. It employs a generalized radar backscattering model for forests and a second-order polynomial function for soil moisture profile. The...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10746561/ |
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| author | Yu-Huan Zhao Delwyn Moller Dean Meason Mahta Moghaddam |
| author_facet | Yu-Huan Zhao Delwyn Moller Dean Meason Mahta Moghaddam |
| author_sort | Yu-Huan Zhao |
| collection | DOAJ |
| description | A subsurface soil moisture retrieval algorithm, using a pathfinder simultaneously acquired P- and L-band radar data over forested areas, is proposed in this article. It employs a generalized radar backscattering model for forests and a second-order polynomial function for soil moisture profile. The inversion uses a hybrid simulated annealing method. The proposed multifrequency retrieval algorithm has been evaluated using synthetic data and showed good performance. Furthermore, the proposed algorithm was applied to actual radar data from the forest flows airborne campaign in Te Hiku, New Zealand, in April 2022. The multifrequency inversion results revealed that the root mean squared error between the retrieved and measured soil moisture profiles ranged from 0.019 to 0.048 <inline-formula><tex-math notation="LaTeX">$\mathbf {m^{3}/m^{3}}$</tex-math></inline-formula>, with an overall RMSE of 0.032 <inline-formula><tex-math notation="LaTeX">$\mathbf {m^{3}/m^{3}}$</tex-math></inline-formula>. In addition, comparing multifrequency and single P-band retrievals indicated a reduction in RMSE with the multifrequency approach, particularly noted during the Te Hiku dry season. |
| format | Article |
| id | doaj-art-4daa89aa8d4e41b5affff0357c9852b8 |
| institution | OA Journals |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-4daa89aa8d4e41b5affff0357c9852b82025-08-20T02:06:50ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-011843544510.1109/JSTARS.2024.349311810746561Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New ZealandYu-Huan Zhao0https://orcid.org/0000-0003-4190-624XDelwyn Moller1https://orcid.org/0000-0003-4207-1539Dean Meason2https://orcid.org/0000-0002-7592-0827Mahta Moghaddam3https://orcid.org/0000-0001-5304-2616Microwave Systems, Sensors, and Imaging Laboratory, Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USAUniversity of Auckland, Auckland, New ZealandScion, Rotorua, New ZealandMicrowave Systems, Sensors, and Imaging Laboratory, Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USAA subsurface soil moisture retrieval algorithm, using a pathfinder simultaneously acquired P- and L-band radar data over forested areas, is proposed in this article. It employs a generalized radar backscattering model for forests and a second-order polynomial function for soil moisture profile. The inversion uses a hybrid simulated annealing method. The proposed multifrequency retrieval algorithm has been evaluated using synthetic data and showed good performance. Furthermore, the proposed algorithm was applied to actual radar data from the forest flows airborne campaign in Te Hiku, New Zealand, in April 2022. The multifrequency inversion results revealed that the root mean squared error between the retrieved and measured soil moisture profiles ranged from 0.019 to 0.048 <inline-formula><tex-math notation="LaTeX">$\mathbf {m^{3}/m^{3}}$</tex-math></inline-formula>, with an overall RMSE of 0.032 <inline-formula><tex-math notation="LaTeX">$\mathbf {m^{3}/m^{3}}$</tex-math></inline-formula>. In addition, comparing multifrequency and single P-band retrievals indicated a reduction in RMSE with the multifrequency approach, particularly noted during the Te Hiku dry season.https://ieeexplore.ieee.org/document/10746561/Forest Flows (FF)multifrequencysoil moisture profilesynthetic aperture radar (SAR) |
| spellingShingle | Yu-Huan Zhao Delwyn Moller Dean Meason Mahta Moghaddam Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Forest Flows (FF) multifrequency soil moisture profile synthetic aperture radar (SAR) |
| title | Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand |
| title_full | Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand |
| title_fullStr | Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand |
| title_full_unstemmed | Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand |
| title_short | Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand |
| title_sort | multifrequency subsurface soil moisture retrieval for forest flows a case study in te hiku new zealand |
| topic | Forest Flows (FF) multifrequency soil moisture profile synthetic aperture radar (SAR) |
| url | https://ieeexplore.ieee.org/document/10746561/ |
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