Reviewed by Lexie CornerFeb 24 2025
In a study published in the Journal of Remote Sensing, researchers from the University of Twente introduced the Community Land Active Passive Microwave Radiative Transfer Modelling platform (CLAP). This multi-frequency microwave scattering and emission model combines advanced soil surface scattering (ATS+AIEM) and vegetation scattering (TVG) models.
Wavenumber. Image Credit: Journal of Remote Sensing
Microwave remote sensing is an important tool for land monitoring, providing insights into soil moisture and vegetation health by measuring the microwave radiation emitted and the backscatter reflected from the surface.
Current models often overlook dynamic changes in vegetation and soil properties, such as structure, moisture, and temperature, as they mainly rely on empirical assumptions and zeroth-order radiative transfer theory.
This limitation results in reduced accuracy and inconsistencies across different frequencies and polarizations. To improve the reliability of remote sensing technologies, further research into the scattering and emission mechanisms of multi-frequency microwave signals is necessary.
The Community Land Active Passive Microwave Radiative Transfer Modelling platform (CLAP) addresses these issues by incorporating temperature variations, dynamic vegetation water content (VWC), and appropriate vegetation structure. CLAP also provides new insights for more accurate vegetation and soil monitoring by revealing the frequency-dependent nature of grassland optical depth and highlighting the significant impact of vegetation temperature on high-frequency signals.
A key advantage of CLAP is its ability to model soil and vegetation components in great detail. The researchers evaluated the model’s performance using long-term in situ observations from the Maqu site, which included vegetation data, temperature profiles, soil moisture, and microwave signals.
The results showed that, compared to 3.4 dB and 3.0 dB from disc parameterization, CLAP using cylinder parameterization for vegetation representation simulated grassland backscatter at X-band and C-band with RMSE values of 1.8 dB and 1.9 dB, respectively, during the summer.
The study also found that changes in vegetation water content mainly affect low-frequency signals, while vegetation temperature variations significantly impact high-frequency signal diurnal changes.
For example, variations in vegetation temperature had a stronger effect on signal changes at the C-band (correlation coefficient R of 0.34), whereas vegetation water content had a stronger effect at the S-band (R of 0.46). These results emphasize the importance of accounting for dynamic vegetation and soil characteristics in microwave signal emission and scattering, which CLAP accurately captures.
The CLAP platform represents a major advancement in microwave remote sensing. By incorporating appropriate vegetation structure, dynamic vegetation, and soil water content and temperature into the model, CLAP offers a more accurate representation of microwave signal scattering and emission processes. This innovation will significantly enhance our ability to monitor vegetation and soil conditions, providing more reliable data for ecosystem management and climate change research.
Dr. Hong Zhao, Study Lead Researcher, University of Twente
The team utilized satellite microwave observations and a substantial amount of in situ data from the Maqu site. These comprehensive datasets enabled the researchers to thoroughly assess CLAP's performance across a range of frequencies and polarizations, ensuring its accuracy and reliability.
The development of CLAP opens new possibilities for microwave remote sensing. Future satellite missions, such as CIMR and ROSE-L, could incorporate this technology to enhance the accuracy of vegetation and soil moisture monitoring.
Additionally, CLAP can be integrated into data assimilation frameworks to provide more precise inputs for land surface models. The widespread application of this technology is expected to support global sustainability efforts, with significant impacts on agricultural production, climate change research, and environmental monitoring.
Journal Reference:
Zhao, H., et al. (2025) Modelling of Multi-Frequency Microwave Backscatter and Emission of Land Surface by a Community Land Active Passive Microwave Radiative Transfer Modelling Platform (CLAP). Journal of Remote Sensing. doi.org/10.34133/remotesensing.0415.