The updating of forest resource data for management planning for privately owned forests in Finland

In Finland, the forest resource data for management planning is traditionally collected by periodic standwise field inventories, which are usually carried-out over different regions during 10–15 year intervals. The data is used for the compilation of management plans for forest estates. Between inventories the plan and the original stand data can be used, e.g., in the operational planning of timber sales and silvicultural treatments. In operational planning, up-to-date stand data are needed. Therefore, interest in the cost-efficient methods for the updating has increased in recent years. The aim of this thesis was to test potential methods for the updating of forest resource data for management planning in private forestry in Finland. The main criterion in the selection of the studied methods was that they can be applied to the current planning system of Regional Forest Centres, with moderate modifications. Three methods were tested: a) an automatic interpretation of remote sensing material utilising nonparametric estimation at standand at segment-levels, b) follow-up of changed stands and c) change detection at stand-level. The estimations based on the use of medium resolution satellite images at the standlevel and high resolution aerial photographs at the segment-level did not achieve the defined accuracy level of stand attributes and treatment proposals. Estimates based on these methods can be utilised for obtaining approximate information on the stand attributes. The estimation method at the segment-level was considered to be worth of further research. The follow-up of changed stands proved to be a potential method for updating forest data. The information for 75% of the management operations was found from the data bases of the Regional Forestry Centre and the Forest Management Association. An updated forest management plan was composed based on new inventory data on changed stands and computationally updated data on unchanged stands. The reliability of the updated plan was equal to that composed based only on new inventory data. The tested change detection with bi-temporal aerial photographs should play a part in the updating procedure. The overall accuracy of change detection was 84.7% at best, and 84.2% of the thinned stands were found. According to the results of this thesis, the follow-up of changes combined with change detection with remote sensing is a promising method for the updating of forest resource data in privately owned forests.