Exploration of big-BAF Sampling Potential for Volume Estimation in Abies borisii-regis Matff. Forest Stands

A reliable sampling design is essential for the accurate estimation of the forest biometric characteristics. Wood stock estimation at the level of a forest stand is the main source of information utilized for the sustainable management of forest ecosystems. The scientific effort in this area is guided by the combination of the intended accuracy with the use of as few available financial resources as possible. Horizontal point sampling (HPS) is considered an effective sampling scheme that uses a predefined horizontal angle (basal area factor) to select the sampled trees. Due to the known limitations of this method, an alternative subsample method, which is based on HPS, has been explored by the scientific community, making use of a small basal area factor for the selection of trees in the first sampling stage followed by a second big basal area factor for the selection of trees in the second sampling stage. In this direction, this research work aims to investigate the effectiveness of different sampling schemes using subsampling based on different values of horizontal angle, involving the two-stage sampling technique (big-BAF). For this purpose, the impact of the different combined basal area factors (angles) between the two sampling stages was explored, along with their sampling errors, using ground-truth data collected from fir trees growing in the University Forest of Pertouli, Greece.