Investigation of linear and logarithmic regression between measured and calculated parameters of Eldarica pine tree

Abstract

Man-made forests are created with various goals, including reducing the pressure on natural
forests. Therefore, the knowledge of the status of their quantitative characteristics for
planning and achieving primary goals has always been of interest to the managers of these
types of forests. In this research, field data collection of parameters such as height, DBH and
crown area was done with Phantom 4 UAV RGB images (2 Cm), Total Station TS02 (7’’) and
standard metal meter(1mm). Then it was obtained by calculating the parameters with the help
of paired images (crown area) and point cloud (Height and Diameter at breast height). In the
next step, two-by-two linear and logarithmic regression relationships were created between
H, DBH and crown area parameters, and the value of R2 was also obtained. The results showed
that linear regression is better than logarithmic regression. Also, the amount of R2 between
DBH and H parameters in two cases of data from field measurements (R2=0.75) and data from
calculations (R2=0.83) gave better results than the comparison of other parameters.
Therefore, it is possible to use linear regression equations between DBH and H in very few
statistics, similar environmental conditions and no need for very high accuracy.