Browsing by Subject "Aarni forest resource information system"

The Finnish Forest Center produces forest resource data for the use of land owners and the actors in the forestry sector. The data is produced mainly by means of airborne laser scanning (ALS), and it is managed in a nationwide Aarni- forest resource information system. The produced data also includes stand-specific proposals for harvesting and silvicultural treatment. These are usually generated by a simulation, which also provides suggestion for a year of the action. The collection of forest resource data is based on the Area-based approach (ABA). In the method, the forest charac-ters, such as tree attributes measured on field sample plots, are predicted to the whole invention area by the corre-sponding laser- and aerial photo features. Forest characters are predicted to the grid cells 16 x 16 meters in size. In Aarni, the treatment simulation is based on the averages of the tree attributes generalized from the grid cells to the stand. The method does not regard a possible within-stand variation in tree density, which may cause, for ex-ample, delayed thinning proposals especially for the stands with grouped trees. The main aims of this study were: 1. To create a new method in which, in addition to the tree attributes, the subsequent treatment and its timing were simulated to grid cells. After that, special decision rules were created to derive the treatment from the grid cells to the stand. 2. To compare the treatments derived with the decision rules with the normal Aarni simulation of 291 field-surveyed stands to determine which method is better. A related action was also taken: A relationship between within-stand variation and a timing of the simulated treat-ments was also surveyed. This was accomplished by comparing the deviation of tree attributes of the grid cells (e.g. basal-area) with the corresponding attributes of the stand. Presumption was that, particularly in the stands with grouped trees, the problem of delayed thinning could be reduced by using decision rules. The results suggest that the decision rule method gives slightly better results than Aarni simulation in the case of the timing of treatments. The method gave the best results in the young stands where the field treatment proposal was first thinning. The deviation of the basal area of trees in the grid cells appeared to be slightly larger than aver-age in the stands with a large variation in tree density. In these particular stands, the decision rules mostly derived better timing for thinning than normal Aarni simulation.