Remote sensing backscattering model for sea ice: Theoretical modelling and analysis

Remote sensing has been used in Antarctic studies as an earth observation technique to study the polar region. A remote sensing forward model is an important tool in polar research to study and understand scattering mechanisms and sensitivity of physical parameters of snow and sea ice. In this paper, a reliable theoretical model to study sea ice is developed. The theoretical model in a prior work was improved by including multiple-surface scattering, based on an existing integral equation model and additional second-order surface-volume scattering. This model is applied to a desalinated ice layer above thick saline ice and analyzed using different frequencies, bottom surface roughness and sea-ice layer thickness. Improvement in calculation of the backscattering coefficient of the sea-ice layer is investigated for both co-polarized and cross-polarized returns. The effect on each scattering mechanism is also investigated, to understand in more detail the effect of surface multiple scattering and second-order surface-volume scattering. Comparisons are also made with field measurement results, to validate the theoretical model. Results show improvement in the total backscattering coefficient for cross-polarized return in the studied range, suggesting that multiple-surface scattering and surface-volume scattering up to second order are important scattering mechanisms in the sea-ice layer and should not be ignored in polar research

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

Microwave remote sensing offers a powerful tool for monitoring the growth of short, dense vegetation like soybean. 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 and pods 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 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

衛星搭載型多偏波SARを用いた土壌水分分布評価手法の開発とALOS/PALSARへの適用

学位の種別: 論文博士審査委員会委員 : （主査）東京大学教授 小池 俊雄, 東京大学教授 田島 芳満, 東京大学教授 西村 拓, 東京大学准教授 平林 由希子, 東京大学准教授 沖 一雄, 東京大学准教授 竹内 渉University of Tokyo(東京大学