Umeå University's logo

Introduction: Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) has recently emerged as a low-cost, continuous, and high-resolution technique for monitoring crop growth. However, conventional GNSS-R approaches that rely on signal-to-noise ratio (SNR) observables are limited by data availability, particularly from legacy receivers, and the effectiveness of observable combination methods in this context has not yet been established.

Methods: This study presents the first successful attempt to retrieve wheat height using ground-based GNSS-R with code pseudorange and dual-frequency carrier phase observables. Six observable combination schemes from GPS and BDS were evaluated through a field experiment at the Fengqiu Agro-ecology Experimental Station in China. A GDD-parameterized Logistic growth model was employed as a continuous reference. A multi-system, multi-satellite fusion strategy was developed, incorporating principal frequency power weighting within each system and residual reciprocal weighting across systems.

Results: The observable combination method effectively captured wheat growth dynamics. The best-performing combinations—GPS C5I+L5I+L2P and BDS C2I+L2I+L6I—achieved correlation coefficients (R) of 0.935 and 0.957, and RMSE values of 0.081 m and 0.086 m, respectively. Dual-system fusion further enhanced retrieval accuracy, reducing RMSE by 22.6% compared with the best single-system combination and by 34.6% relative to an SNR-based method.

Discussion: These findings demonstrate the feasibility and superiority of pseudorange and dual-frequency carrier phase combinations for SNR-independent GNSS-R crop monitoring. The proposed strategy offers a robust, scalable, and accessible tool for precision agriculture and continuous crop growth tracking, particularly in contexts where SNR data are unavailable or unreliable.