Kaleja Santa, PhD

Determining forest stand characteristics after thinning, in order to assess the quality of the work and update the inventory data of the thinned stand, is one of the few forest management tasks for which an efficient and accurate automation solution has not yet been developed. Currently, forest stand characteristics are determined by a certified inventory expert using manual instruments such as a range finder, digital or manual calliper, and a Bitterlich gauge. Manual measurements add a significant cost to forest management, and automating this process could increase the competitiveness of forest owners in the global timber market, helping reduce human error and providing more detailed information on the condition of stands and the distribution of trees of different dimensions in a stand.

The aim of the study is to adapt a method developed in Sweden for the automated estimation of forest stand characteristics after thinning using the HprGallring software to Latvian conditions and to determine accuracy of the modelling-based prediction of stand characteristics.

In the study, the height, number, diameter, and species of individual trees after thinning were determined using the sample plot method (according to methods applied in forest resources monitoring) and using photogrammetry as reference data for the study. In some felling areas, the diameters of all trees were measured before and after felling. The data obtained using different methods were compared with updated stand characteristics in the Forest resource database updated by certified inventory experts using plot measurement method.

According to the results of the study, HprGallring can provide the data necessary for updating the forest inventory database after thinning, but the accuracy of the modelled projections, as compared to manual measurements, are not yet within the uncertainty range as required by the forest inventory regulations. The average tree height, as indicated in the State Forest Register, matches the HprGallring estimates within the regulatory uncertainty limits in 67% of Scots pine (Pinus sylvestris L.) stands, 65% of Norway spruce (Picea abies (L.) H.Karst.) stands, and 48% of Birch (Betula sp.) stands. The diameter of an average tree after thinning estimated by the HprGallring is larger than that according to the manual measurement. The average diameter estimated using HprGallring in pine stands matches the data in State Forest Register in 40% of the assessed areas, in 47% for spruce stands, and 35% of birch stands. The accuracy of the predictions needs to be improved to make HprGallring usable in forest inventory, but even now it provides valuable spatial information about the distribution of trees of different dimensions and species within stands, enabling more accurate planning of management methods and spatial redesigning of the forest compartments.