Determination of log moisture content using ground penetrating radar (GPR). Part 1. Partial least squares (PLS) method

Hans, Guillaume; Redman, David; Leblon, Brigitte; Nader, Joseph; Rocque, Armand La

doi:10.1515/hf-2014-0286

Cited by 9 publications

(2 citation statements)

References 36 publications

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“…The log samples and the data sets are identical with those described in Part 1 ( Hans et al 2015 ). The two-way travel time t t (ns) of the GPR signal through the log can be computed as the diff erence between the arrival times of the direct and refl ected waves of the GPR traces.…”

Section: Methodsmentioning

confidence: 99%

Determination of log moisture content using ground penetrating radar (GPR). Part 2. Propagation velocity (PV) method

Hans

Redman²,

Leblon

et al. 2015

Holzforschung

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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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Section: Methodsmentioning

confidence: 99%

Determination of log moisture content using ground penetrating radar (GPR). Part 2. Propagation velocity (PV) method

Hans

Redman²,

Leblon

et al. 2015

Holzforschung

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“…In this case, data from all four drying stages were used (model group 1). Models were also created to estimate log diameter and bark thickness from GPR signals (model group 3) since previous studies suggested that log diameter is highly correlated to GPR signals [23].…”

Section: Response Variables Covariate Variables and Time Window Selec...mentioning

confidence: 99%

Using Ground Penetrating Radar (GPR) to Predict Log Moisture Content of Commercially Important Canadian Softwoods

Duchesne,

Tong,

Hans

2023

Forests

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The non-destructive testing of wood fibre properties is crucial for informing forest management decisions and achieving optimal resource utilization. Moisture content (MC) is an important indicator of wood freshness and may reveal the presence of wood degradation. However, efficient methods are still needed to better monitor this property along the forest–wood value chain. The objective of the study was to develop prediction models to evaluate log MC based on the propagation of ground penetrating radar (GPR) signals. A total of 165 trees representing four species (black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca (Moench) Voss), red spruce (Picea rubens Sarg.), and balsam fir (Abies balsamea (L.) Mill.)) were harvested in two regions of the province of Quebec. GPR signals were acquired in the green (fresh) state and at three subsequent drying stages. Partial least squares regression (PLSR) and locally weighted PLSR (LWPLSR) were employed to establish relationships between GPR signals (antenna frequency: 1.6 GHz) and log properties. The models were fitted on three calibration sets containing four drying stages and different species mixes. The LWPLSR models performed better than the PLSR models for predicting log MC, with a lower root mean square error (RMSEp range: 10.8%–20.2% vs. 13.0%–20.5%) and a higher R2p (0.63–0.87 vs. 0.62–0.82). Spruce-only models performed considerably better than fir-only models while multi-species models were in-between. Despite the complex anisotropy of wood and the physics of wave propagation, the GPR technology can be successfully used to estimate log moisture content, but the GPR-based MC models should be calibrated for each specific type of wood material.

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A production-oriented review of high-frequency measurement methods for forest products

Hyll

2024

Eur. J. Wood Prod.

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Determination of log moisture content using ground penetrating radar (GPR). Part 1. Partial least squares (PLS) method

Cited by 9 publications

References 36 publications

Determination of log moisture content using ground penetrating radar (GPR). Part 2. Propagation velocity (PV) method

Determination of log moisture content using ground penetrating radar (GPR). Part 2. Propagation velocity (PV) method

Using Ground Penetrating Radar (GPR) to Predict Log Moisture Content of Commercially Important Canadian Softwoods

A production-oriented review of high-frequency measurement methods for forest products

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