Separating Water-Level Variations and Phenological Changes in Rice Paddies: Integrating SAR with Ground-Based GNSS-IR Observations.
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| Title: | Separating Water-Level Variations and Phenological Changes in Rice Paddies: Integrating SAR with Ground-Based GNSS-IR Observations. |
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| Authors: | Kobayashi, Daiki1 (AUTHOR) dk.kobayashi@ntt.com, Suzuki, Ryusuke2 (AUTHOR), Noborio, Kosuke3 (AUTHOR) |
| Source: | Remote Sensing. Apr2026, Vol. 18 Issue 7, p1055. 21p. |
| Subjects: | Paddy fields, Water levels, Vegetation dynamics, Phenology, Global Positioning System, Synthetic aperture radar |
| Abstract: | Highlights: What are the main findings? L-band co-polarized SAR (VV, HH) corresponds to the GNSS-IR LSP peak associated with water level variations in paddy fields. The L-band SAR cross-polarized ratio (VH/VV) corresponds to the GNSS-IR LSP normalized spectral integral, capturing rice phenological dynamics. What are the implications of the main findings? GNSS-IR provides complementary vertical structural information that supports the physical interpretation of SAR scattering mechanisms. Integrating SAR and GNSS-IR enables physically consistent and high-temporal-resolution monitoring of water and vegetation dynamics. Paddy field water management and rice phenology strongly affect crop productivity and environmental processes, requiring continuous and quantitative monitoring. This study combined satellite synthetic aperture radar (SAR) observations and ground-based Global Navigation Satellite System (GNSS) interferometric reflectometry (GNSS-IR) over a paddy field to analyze their sensitivities to water-level variations and phenological dynamics. Sentinel-1 (C-band) and ALOS-2/PALSAR-2 (L-band) SAR time series were compared with continuous GNSS-IR observations acquired using geodetic-grade instrumentation. For GNSS-IR, Lomb–Scargle periodogram (LSP) analysis of SNR data was applied to derive two indicators: (i) the dominant spectral peak (fwater) frequency associated with the effective reflecting surface, and (ii) a normalized spectral integral (GNSS Phenology Indicator, GPI) representing vegetation-induced scattering and attenuation effects. The temporal evolution of LSP spectra exhibited systematic changes with rice phenological progression, including peak broadening and the emergence of multiple peaks as vegetation developed. For water level variations, L-band SAR co-polarized backscatter (VV and HH) and the GNSS-IR spectral peak exhibited comparable relationships with in situ water level, whereas C-band SAR showed weaker sensitivity. For phenological dynamics, GPI showed temporal behavior similar to that of the SAR polarization ratio (VH/VV), with clear responses around key growth stages, such as heading and harvest. These results suggest that SAR polarization-based indicators and GNSS-IR spectral characteristics can be interpreted within a consistent electromagnetic framework: co-polarized L-band SAR responses correspond to the water-surface-related GNSS-IR peak, whereas cross-polarized indicators correspond to GPI. This study demonstrated the potential of GNSS-IR as complementary information for physically interpreting SAR scattering mechanisms, highlighting a pathway toward more integrated microwave-based monitoring of land surface processes. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? L-band co-polarized SAR (VV, HH) corresponds to the GNSS-IR LSP peak associated with water level variations in paddy fields. The L-band SAR cross-polarized ratio (VH/VV) corresponds to the GNSS-IR LSP normalized spectral integral, capturing rice phenological dynamics. What are the implications of the main findings? GNSS-IR provides complementary vertical structural information that supports the physical interpretation of SAR scattering mechanisms. Integrating SAR and GNSS-IR enables physically consistent and high-temporal-resolution monitoring of water and vegetation dynamics. Paddy field water management and rice phenology strongly affect crop productivity and environmental processes, requiring continuous and quantitative monitoring. This study combined satellite synthetic aperture radar (SAR) observations and ground-based Global Navigation Satellite System (GNSS) interferometric reflectometry (GNSS-IR) over a paddy field to analyze their sensitivities to water-level variations and phenological dynamics. Sentinel-1 (C-band) and ALOS-2/PALSAR-2 (L-band) SAR time series were compared with continuous GNSS-IR observations acquired using geodetic-grade instrumentation. For GNSS-IR, Lomb–Scargle periodogram (LSP) analysis of SNR data was applied to derive two indicators: (i) the dominant spectral peak (fwater) frequency associated with the effective reflecting surface, and (ii) a normalized spectral integral (GNSS Phenology Indicator, GPI) representing vegetation-induced scattering and attenuation effects. The temporal evolution of LSP spectra exhibited systematic changes with rice phenological progression, including peak broadening and the emergence of multiple peaks as vegetation developed. For water level variations, L-band SAR co-polarized backscatter (VV and HH) and the GNSS-IR spectral peak exhibited comparable relationships with in situ water level, whereas C-band SAR showed weaker sensitivity. For phenological dynamics, GPI showed temporal behavior similar to that of the SAR polarization ratio (VH/VV), with clear responses around key growth stages, such as heading and harvest. These results suggest that SAR polarization-based indicators and GNSS-IR spectral characteristics can be interpreted within a consistent electromagnetic framework: co-polarized L-band SAR responses correspond to the water-surface-related GNSS-IR peak, whereas cross-polarized indicators correspond to GPI. This study demonstrated the potential of GNSS-IR as complementary information for physically interpreting SAR scattering mechanisms, highlighting a pathway toward more integrated microwave-based monitoring of land surface processes. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18071055 |
