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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Bibliographic Details
Published in:IEEE journal of selected topics in applied earth observations and remote sensing 2025-01, Vol.18, p.435-445
Main Authors: Zhao, Yu-Huan, Moller, Delwyn, Meason, Dean, Moghaddam, Mahta
Format: Article
Language:English
Subjects:
Airborne radar
Algorithms
Backscatter
Calibration
Data acquisition
Dielectrics
Dry season
Error analysis
Forest Flows (FF)
Forestry
Forests
Functions (mathematics)
L-band
Moisture content
Moisture profiles
multifrequency
Polynomials
Radar
Radar data
Retrieval
Root-mean-square errors
Scattering
Sensors
Simulated annealing
Soil
Soil measurements
Soil moisture
soil moisture profile
Soil profiles
synthetic aperture radar (SAR)
Synthetic data
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Summary: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 \mathbf {m^{3}/m^{3}}, with an overall RMSE of 0.032 \mathbf {m^{3}/m^{3}}. 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.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2024.3493118