3D volumetric modeling of grapevine biomass using Tripod LiDAR

Tripod mounted laser scanning provides the means to generate high-resolution volumetric measures of vegetation structure and perennial woody tissue for the calculation of standing biomass in agronomic and natural ecosystems. Other than costly destructive harvest methods, no technique exists to rapidly and accurately measure above-ground perennial tissue for woody plants such as Vitis vinifera (common grape vine). Data collected from grapevine trunks and cordons were used to study the accuracy of wood volume derived from laser scanning as compared with volume derived from analog measurements. A set of 10 laser scan datasets were collected for each of 36 vines from which volume was calculated using combinations of two, three, four, six and 10 scans. Likewise, analog volume measurements were made by submerging the vine trunks and cordons in water and capturing the displaced water. A regression analysis examined the relationship between digital and non-digital techniques among the 36 vines and found that the standard error drops rapidly as additional scans are added to the volume calculation process and stabilizes at the four-view geometry with an average Pearson's product moment correlation coefficient of 0.93. Estimates of digital volumes are systematically greater than those of analog volumes and can be explained by the manner in which each technique interacts with the vine tissue. This laser scanning technique yields a highly linear relationship between vine volume and tissue mass revealing a new, rapid and non-destructive method to remotely measure standing biomass. This application shows promise for use in other ecosystems such as orchards and forests.

Research highlights▶ Vine wood volume derived from laser scanning is compared with analog measurements. ▶ Correlation between the two methods ranged between 0.73 and 0.97. ▶ Laser scanning yields a linear relationship between vine volume and tissue mass. ▶ TLS allows accurate volume measurements, no destructive harvest, automated processing.