Detection of tree roots and determination of root diameters by ground penetrating radar under optimal conditions.

摘要

A tree's root system accounts for between 10 and 65% of its total biomass, yet our understanding of the factors that cause this proportion to vary is limited because of the difficulty encountered when studying tree root systems. There is a need to develop new sampling and measuring techniques for tree root systems. Ground penetrating radar (GPR) offers the potential for direct nondestructive measurements of tree root biomass and root distributions to be made. We tested the ability of GPR, with 500 MHz, 800 MHz and 1 GHz antennas, to detect tree roots and determine root size by burying roots in a 32 m3 pit containing damp sand. Within this test bed, tree roots were buried in two configurations: (1) roots of various diameters (1-10 cm) were buried at a single depth (50 cm); and (2) roots of similar diameter (about 5 cm) were buried at various depths (15-155 cm). Radar antennas were drawn along transects perpendicular to the buried roots. Radar profile normalization, filtration and migration were undertaken based on standard algorithms. All antennas produced characteristic reflection hyperbolas on the radar profiles allowing visual identification of most root locations. The 800 MHz antenna resulted in the clearest radar profiles. An unsupervised, maximum-convexity migration algorithm was used to focus information contained in the hyperbolas back to a point. This resulted in a significant gain in clarity with roots appearing as discrete shapes, thereby reducing confusion due to overlapping of hyperbolas when many roots are detected. More importantly, parameters extracted from the resultant waveform through the center of a root correlated well with root diameter for the 500 MHz antenna, but not for the other two antennas. A multiple regression model based on the extracted parameters was calibrated on half of the data (R2=0.89) and produced good predictions when tested on the remaining data. Root diameters were predicted with a root mean squared error of 0.6 cm, allowing detection and quantification of roots as small as 1 cm in diameter. An advantage of this processing technique is that it produces results independently of signal strength. These waveform parameters represent a major advance in the processing of GPR profiles for estimating root diameters. We conclude that enhanced data analysis routines combined with improvements in GPR hardware design could make GPR a valuable tool for studying tree root systems.