Comparison of Vegetation Scattering Models for GNSS-R

A variety of microwave bistatic scattering methods for vegetation layers have been developed and applied to global navigation satellite system reflectometry (GNSS-R). These methods can be grouped into three categories: incoherent models based on radiative transfer (RT) theory, coherent methods based on analytical wave theory and the distorted Born approximation (DBA), and full wave simulations utilizing fast hybrid methods (FHM). Some comparisons of RT methods and FHM have been performed, e.g., in [1]. Yet, little is known about how RT and coherent methods compare. In this study, the significance of coherent vegetation scattering effects for GNSS-R is investigated using a simulated forest of truncated dielectric cylinders over a reflective surface.

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Published
2024-09-02
DOI
https://doi.org/10.1109/iceaa61917.2024.10701580
Primary Topic
Soil Moisture and Remote Sensing
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article
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article

Comparison of Vegetation Scattering Models for GNSS-R

Mahta Moghaddam, James D. Campbell
Soil Moisture and Remote Sensing
article

Comparison of Vegetation Scattering Models for GNSS-R

Mahta Moghaddam, James D. Campbell
article en

Abstract

A variety of microwave bistatic scattering methods for vegetation layers have been developed and applied to global navigation satellite system reflectometry (GNSS-R). These methods can be grouped into three categories: incoherent models based on radiative transfer (RT) theory, coherent methods based on analytical wave theory and the distorted Born approximation (DBA), and full wave simulations utilizing fast hybrid methods (FHM). Some comparisons of RT methods and FHM have been performed, e.g., in [1]. Yet, little is known about how RT and coherent methods compare. In this study, the significance of coherent vegetation scattering effects for GNSS-R is investigated using a simulated forest of truncated dielectric cylinders over a reflective surface.

University of Southern California (US)
Climate action
Openalex Percentile: Top 85%
Soil Moisture and Remote Sensing
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