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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #418898
Research Project: From Field to Watershed: Enhancing Water Quality and Management in Agroecosystems through Remote Sensing, Ground Measurements, and Integrative Modeling

Location: Hydrology and Remote Sensing Laboratory

Title: Full-wave simulations of forest at L-band with fast hybrid multiple scattering theory method and comparison with GNSS signals

Author
item JEONG, J - University Of Michigan
item TSANG, L - University Of Michigan
item KURUM, M - University Of Georgia
item GHOSH, A - University Of Georgia
item COLLIANDER, A - Jet Propulsion Laboratory
item YUEH, S - Jet Propulsion Laboratory
item MCDONALD, K - City University Of New York
item STEINER, N - City University Of New York
item Cosh, Michael

Submitted to: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/16/2025
Publication Date: 1/25/2025
Citation: Jeong, J., Tsang, L., Kurum, M., Ghosh, A., Colliander, A., Yueh, S., Mcdonald, K., Steiner, N., Cosh, M.H. 2025. Full-wave simulations of forest at L-band with fast hybrid multiple scattering theory method and comparison with GNSS signals. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18:5395-5405. https://doi.org/10.1109/JSTARS.2025.3533313.
DOI: https://doi.org/10.1109/JSTARS.2025.3533313

Interpretive Summary: Estimating large scale vegetation canopy biomass is useful for carbon, energy, and water cycle modeling. Canopy biomass is often correlated with water content, which can be estimated using L-band microwave radiometry. Using field data collected during a field campaign in Massachusetts and New York, a portable L-band system was used between a forested canopy to characterize the water content and therefore biomass. This work is useful for sensor developers as well as landscape scientists who need large scale parameterization of vegetation.

Technical Abstract: Full-wave simulations at L-band using the Fast Hybrid Method (FHM) have been applied to the Harvard forest in Massachusetts using the Soil Moisture Active Passive Validation Experiment 2022 (SMAPVEX 22) dataset. Due to the limitations of commercial full-wave electromagnetic solvers, the FHM is our choice considering its efficient and fast solutions. During SMAPVEX 22, scientists collected a dataset of tree sizes, tree positions (derived from Light Detection and Ranging (LiDAR) measurement), and microwave signals utilizing Global Navigation Satellite System (GNSS) Transmissometery (GNSS-T) approach. The 3D geometric forest model provides 300 trees with heights up to 19 meters by processing the dataset. We import the forest model into the FHM and analyze microwave propagation at MA401. The FHM analysis shows that the transmissivity ranges from 0.627 to 0.674 for the vertically polarized incident wave source and from 0.593 to 0.665 for the horizontally polarized incident wave source. To validate the FHM, comparison is made with the GNSS signals. The comparison results of microwaves are in good agreement, demonstrating the physical results such shadowing effects under the trees and higher electric amplitudes at some points in forests compared to that of the open area. We also analyze the effects of tapered trees in this study.