Supplementary Materials for:
Calibrating the impact of root orientation on root quantification using ground-penetrating radar
Li Guo, Yuan Wu, Jin Chen, Yasuhiro Hirano, Toko Tanikawa, Wentao Li, Xihong Cui
L. Guo, J. Chen ()
College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China; Joint Center for Global Change Studies, Beijing, 100875, China
E-mail:
Y. Wu, W. Li, X. Cui
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
Y. Hirano
Graduate School of Environment Studies, Nagoya University, Nagoya 464-8601, Japan
T. Tanikawa
Kansai Research Center, Forestry and Forest Products Research Institute, Nagai-kyutaro, Momoyama, Fushimi, Kyoto 612-0855, Japan
Text S1 Forward simulation of root GPR signal
Until now, root GPR signals could only be simulated in two dimension (Guo et al. 2013a). The cross angle of root to survey line could not be parameterized in the simulation. In this study, GPR signals of 46 roots were simulated as though roots and survey lines were orthogonal. Diameters of the simulated roots were set from 5 to 50 mm (in increments of 1 mm, which covers the majority of root sizes in root GPR studies). To compare with the field experiment, water contents of root and soil were assigned based on field measurements. According to our extensive field investigation, the gravimetric water content of C. microphylla roots was normally distributed, with an average of 109% and a standard deviation of 27% (Guo et al. 2013b). Hence, the water content of the simulated root was randomly assigned following such a normal distribution. Field soil water content measurements at four depth intervals (0-0.2 m, 5.39%; 0.2-0.4 m, 5.06%; 0.4-0.6 m, 4.72%; and 0.6-0.8 m, 4.39%) were input into the simulation accordingly. Simulations were computed under the center frequency of 900 MHz, which is the same as the GPR systems used in both the field and sand box experiments. The geometric domain of each simulation included a soil background (1.2 m long and 0.8 m deep) and a 5 mm thick air layer above the soil. The simulated root was located at 0.3 m depth and 0.6 m to the right boundary of the simulation domain (see an example of the simulation configuration in Fig. 1a in Guo et al. 2013b). Specific rationales of root GPR signal simulation were stated in Guo et al. (2013a).
Text S2 Generating amplitude areas for simulatedroots at varied cross angles
For the simulation experiment, amplitude areas were first extracted on the simulated radargrams for orthogonal roots and survey lines, i.e., A(90°). Then, the amplitude areas corresponding to the other cross angles were calculated based on the sinusoidally changing pattern of A against x following the method below: 1) For each type of amplitude area, the minimum A(90°) extracted from the 46 simulated roots was determined. In our simulation design, the minimum A(90°) was measured corresponding to the third smallest simulated root (with a diameter of 7 mm and a low gravimetric root water content of 87%). This minimum A(90°) was assumed to be A(0°) for all of the simulated data (i.e., c-a). Together with A(90°) (i.e., c+a) directly extracted from each simulated radargram, the values of (c-a) and (c+a) were calculated. In this case, the two coefficients (a and c) could be calculated for each simulated root, and the numerical relationship between A and x was fixed. Then, A(x) was computed using Eq. (2) with the calculated coefficients (a and c) at 7 cross angles from 45° to 135° (in 15° steps). Finally, to approximate the truth as closely as possible, a relative error (i.e., the blue lines in Fig. 3) was added to each calculated A(x) and the directly extracted A(90°). The scale of the relative error was estimated using data from the sand box experiment. Hence, 644 amplitude areas (46 roots × 7 cross angles × 2 amplitude area types) were obtained for the simulation experiment.
References
Guo L, Lin H, Fan B, Cui X, Chen J (2013a) Forward simulation of root's ground penetrating radar signal: simulator development and validation. Plant Soil 372:487-505. doi:10.1007/s11104-013-1710-4
Guo L, Lin H, Fan B, Cui X and Chen J (2013b) Impact of root water content on root biomass estimation using ground penetrating radar: evidence from forward simulations and field controlled experiments. Plant Soil 371:503-520. doi:10.1007/s11104-013-1710-4