P-band radiometry for enhanced vegetation optical depth (VOD) and soil moisture retrieval in dense crop canopies

P-band (0.3-1 GHz) radiometry shows promise in enhancing the next generation of radiometer missions for global soil moisture and vegetation optical depth (VOD) monitoring, particularly in moderately to densely vegetated areas, which remain challenging for current L-band (1.4 GHz) missions such as Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP). However, the superiority of P-band over L-band in this regard has not been experimentally verified, and the quantitative differences remain unexplored. To address this gap, the P-band Radiometer Inferred Soil Moisture (PRISM) tower-based experiment was conducted, pioneering a comprehensive evaluation of P- (0.75 GHz) and L-band (1.4 GHz) radiometry in densely vegetated areas with vegetation water content (VWC) up to 20 kg/m(2). The results revealed that P-band VOD was consistently lower than L-band VOD, suggesting reduced vegetation attenuation and thus a higher VWC threshold for reliable soil moisture sensing at P-band. The VWC thresholds for P- and L-band were estimated at 7.7 kg/m(2) and 4.0 kg/m(2), respectively, suggesting that P-band radiation could go through the vegetation approximately twice as effectively as L-band radiation. Additionally, the Microwave Polarization Difference Index (MPDI) was identified as a strong predictor of retrieval performance because it established a good link between retrieval errors and VWC. Regarding VOD retrieval, robust logarithmic relationships (R-2 > 0.9) between VOD and VWC were established for both bands within the 0-20 kg/m(2) VWC range, challenging the previously assumed linear relationship. Moreover, P-band demonstrated greater retrieval robustness as its dual-polarized TB observations contain more independent information than those of L-band. This research establishes the foundation for a successful passive microwave mission at P-band, aiming to improve the quality of global VOD and soil moisture datasets.