Abstract

Abstract Log moisture content (MC) has been determined based on the propagation velocity (PV) of ground penetrating radar (GPR) signals. This approach is based on measuring the travel time of the GPR signal through the log, from which its PV and the apparent log dielectric permittivity can be retrieved. Linear regression between the log dielectric permittivity and MC was established for each of the investigated wood species (quaking aspen, balsam poplar, and black spruce), log state (thawed and frozen), and direction of measurement [on the log cross-section (CS) and through the bark (TB)]. CS and TB measurements led to different results depending on the log state and wood species. Linear models with different slopes were found for thawed (slope=6.4–9.8) and frozen (slope=12–29) logs due to the difference in the dielectric properties of the frozen and unfrozen water in wood. The models for quaking aspen and balsam poplar were very similar to each other and differed from that of black spruce in terms of slopes and intercepts. Generally, the PV method leads to poorer log MC prediction accuracy than the partial least squares method presented in Part 1 of this study.

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