A 3-D Full-Wave Model to Study the Impact of Soybean Components and Structure on L-Band Backscatter

Autor: Kaiser Niknam, Jasmeet Judge, A. Kaleo Roberts, Alejandro Monsivais-Huertero, Robert C. Moore, Kamal Sarabandi, Jiayi Wu
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13089-13107 (2024)
Druh dokumentu: article
ISSN: 1939-1404
2151-1535
DOI: 10.1109/JSTARS.2024.3426366
Popis: Microwave remote sensing offers a powerful tool for monitoring the growth of short, dense vegetation such as soybeans. As the plants mature, changes in their biomass and 3-D structure impact the electromagnetic (EM) backscatter signal. This backscatter information holds valuable insights into crop health and yield, prompting the need for a comprehensive understanding of how structural and biophysical properties of soybeans as well as soil characteristics contribute to the overall backscatter signature. In this study, a full-wave model is developed for simulating L-band backscatter from soybean fields. Leveraging the ANSYS high-frequency structure simulator (HFSS) framework, the model solves for the scattering of EM waves from realistic 3-D structural models of soybean, explicitly incorporating the interplant scattering effects. The model estimates of backscatter match well with the field observations from the SMAPVEX16-MicroWEX and SMAPVEX12, with average differences of 1–2 dB for co-pol and less than 4 dB for cross-pol. Furthermore, the model effectively replicates the temporal dynamics of crop backscatter throughout the growing season. The HFSS analysis revealed that the stems, pods, and soil are the primary contributors to HH-pol backscatter, while the branches contribute to VV-pol, and leaves impact the cross-pol signatures. In addition, a sensitivity study with a 3-D bare soil surface resulted in an average variation of 8 dB in co- and cross-pol, even when the root-mean-square height and correlation length were held constant. These capabilities underscore the model's potential to provide insights into the underlying dynamics of the backscatter for growing vegetation.
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