GNSS–T for ecohydrological monitoring of a european beech forest: Assessing different system and band characteristics for resolving temporal VOD dynamics

Abstract

European beech Fagus sylvatica L. is a climatically sensitive and ecologically significant tree species in Europe. While satellite products of Vegetation Optical Depth (VOD) provide valuable large-scale information on canopy water content, structure and biomass, critical for understanding forest resilience to environmental change, ground-based observations are required to resolve canopy-scale processes and to understand and improve satellite VOD retrievals. In this study, we employ a stationary GNSS Transmissometry (GNSS–T) setup in a mature European beech forest, exploiting signals from satellites of GPS, GALILEO, GLONASS and BDS, at different carrier frequencies within L-band. In particular, we focus on ranging code type impacts on VOD retrievals. Ranging codes modulate the GNSS signal, impacting the physical interaction between signal and vegetation, and determine the GNSS receiver’s capability to track these signals, which further may impact the recorded Signal-to-Noise Ratio (SNR). Yet, ranging code types largely remain an unexplored source of variability. Retrieved VOD magnitudes are broadly consistent across all combinations, except GPS L2 W, using the encrypted military code transmitted on the L2 band, indicating that differences in ranging code types can induce larger VOD discrepancies than differences between carrier frequencies and emphasize the importance of signal selection for GNSS–T VOD retrieval. VOD retrieved captures structural canopy features, diel and seasonal dynamics, and shows sensitivity to meteorological drivers. It aligns well with vegetation proxies derived from cameras, particularly during rapid phenological transitions, and exhibits moderate correlations with satellite-based vegetation indicators (AMSR2 LPRM X- and Ku-band VOD, MODIS LAI, Sentinel-1 cross-polarization ratio). Our results demonstrate the capability of GNSS–T to resolve canopy-scale hydraulic dynamics and provide insights into vegetation responses to climatic drivers, while highlighting key considerations in system design and data processing.