Estimating forest data for analyses of forest production and utilization possibilities at local level by means of multi‐source National Forest Inventory

The sample plot data of National Forest Inventories (NFI) are widely used in the analysis of forest production and utilization possibilities to support national and regional forest policy. However, there is an increasing interest for similar impact and scenario analyses for strategic planning at the local level. As the fairly sparse network of field plots only provides calculations for large areas, satellite image data have been applied to produce forest information for smaller areas. The aim of this study was to test the feasibility of generating forest data for a Finnish forest analysis tool, the MELA system, by means of the Landsat satellite imagery and the NFI sample plot data. The study was part of the preparation of a local forestry programme, where a strategic scenario analysis for the forest area of two villages (ca 8000ha) was carried out. Management units that approximate forest stands were delineated by image segmentation. Stand volume and other parameters for each forest segment were estimated from weighted means of the NFI sample plots, where the individual sample plot weights were estimated by the k nearest neighbour (kNN) method. Two different spectral features were tested: single pixel values and average pixel values within a segment. The estimated forest data were compared with the forest data based on independent stand‐level field assessments in two subareas, a national park and an area of forest managed for timber production. In the national park, the estimated mean volume of the growing stock from both spectral feature sets (about 160m³ ha^‐1) was clearly lower than that obtained from stand‐level field assessment (186m³ ha^‐1). Using average pixel values within a segment resulted in a higher proportion of pine and a lower proportion of spruce volume than using single pixel values. It also resulted in an estimated felling potential nearly 10% higher over the first 10‐year period in the scenario analysis of the area dedicated to timber production. However, the maximum long‐term sustainable removal was at the same level (about 30,000m³ year^‐1) for both feature sets over the simulated 30‐year period. The resulting annual felling area in the first 10‐year period was 12% lower when the segment averages were applied, but the difference subsequently levelled off. The kNN approach in estimating initial forest data for scenario analyses at the local level was found promising.