Simulation of Active and Passive Satellite Observations and Estimation of Vegetation Optical Depth Across Different Frequencies Based on a Theoretical Scattering Model in the Tibetan Grassland

Overview & Synopsis

Multifrequency active and passive microwave remote sensing can deliver complementary insights for surface observations. In this study, we aim to simultaneously reproduce these observations and analyze their covariations, as well as to explore the impacts of frequency and observation mode on vegetation optical depth (VOD) estimation using the Tor Vergata (TVG) model. First, model calibration is implemented to simultaneously reproduce passive L-and C-band and active C-band observations, as well as their covariations in the Tibetan grassland. The calibrated TVG model is then employed for calculating multifrequency VOD values, intercomparing satellite retrievals across different frequencies and observations modes, and exploring active and passive covariations and the consistency of active and passive VODs across frequencies. Results demonstrate that the calibrated TVG model effectively reproduces the aforementioned passive and active observations, as well as the negative linear relationship identified in active and passive covariations. Most current satellite-based VOD products have difficulty in simultaneously capturing both frequency-and polarization dependent signals. In addition, the existing active VOD product exhibits an inconsistent seasonal variation compared with our estimates derived from the TVG model. Numerical simulations from the optimized model demonstrate the identified negative linear relationship consistently holds for L/L-and S/S-band active and passive covariations but may break down for the C/C-band combination. It is further confirmed that active and passive VODs exhibit consistency at the same frequency. These findings provide novel insights into integrating multifrequency microwave remote