A Laser Scanner Based Measurement System for Quantification of Citrus Tree Geometric Characteristics

The overall goal of this study was to develop a laser scanner based measurement system and associated algorithms to measure tree geometric characteristics such as tree canopy, height, width, surface area, and volume. A measurement system, which consisted of a laser scanner, an inertial sensor, a GPS, a serial-to-USB converter, a LabVIEW interface program, and a computer, was developed and mounted on a test vehicle. The laser scanner mounted on the test vehicle vertically scanned a target tree, which was trimmed to be symmetric with respect to a vertical line on the tree trunk, using two angular resolutions of 0.25° and 0.5°. The test vehicle moved along the tree-row direction at three average travel speeds of 0.63, 1.00, and 2.21 m/s. The tree geometric characteristics were estimated by three datasets: an original laser data set, a data set processed by the convex hull method, and a data set processed by the Savitzky-Golay filter. Under the experimental condition of a 0.63-m/s travel speed and a 0.25° angular resolution, the relative errors between the laser measurements and the manual measurements for tree canopy height, width, surface area, and volume were -0.37%, 0.01%, -1.99%, and 5.96%, respectively. Estimations of the tree geometric characteristics by the convex hull method were close to the manual measurements in general. Although the estimations by the original laser data set and the Savitzky-Golay filter data set deviated further from the manual measurements, the data sets could describe the profile of the tree in detail with a higher spatial resolution than that obtained by the convex hull method. It is expected that the data sets may provide more useful information in predicting tree growth and productivity. The distance error of 10 cm between the laser travel line and the tree row line caused errors of 4.0% and 9.2% in surface area and volume measurements, respectively. The laser scanner based measurement system developed in this study demonstrated that it can measure the tree geometric characteristics with a relatively good accuracy. However, measurement errors may increase for asymmetrically shaped trees.