Helena Mäkelä

Estimation of timber volume at the sample plot level by means of image segmentation and Landsat TM imagery

The use of image segments in the feature extraction for the estimation of timber volumes using a Landsat TM image was investigated by applying the k nearest neighbour estimation method (knn) and Finnish National Forest Inventory (NFI) sample plots. The estimates of the volumes by tree species at the plot level were derived by means of the cross-validation technique. Ten nearest neighbours (NNs) were applied in the estimation. Image segments were derived by two different methods: (1) a measurement space-guided clustering followed by the connected component labeling (ISOCCL) and (2) a directed trees algorithm (NG). The segmentations were fine-tuned by means of two different region-merging algorithms. The spectral features were extracted in two ways: from a fixed window (FW) around the field sample plot, and from those pixels within the FW that belonged to the same segment as the sample plot pixel. Window sizes from 1 to 11×11 pixels were tested, and the average of the extracted pixel values was used in the estimation. Features from the ISOCCL-based segments gave the best estimates for the volumes of pine and spruce, as well as for the total volume. Best estimates for the volume of broad-leaved trees were obtained from NG-based segments. Compared to the estimates of the FW approach, the improvements were, however, quite small and relative root mean square errors (RMSEs) remained high. The minimum and maximum improvements of relative RMSEs were 1% and 11.3%, respectively. The NG was considered a more applicable segmentation method for forest inventory purposes at the stand level, even though the ISOCCL gave slightly better estimation results in this study. The use of image segmentation in the stratification of the image material into stand margin and within stand areas could be more suitable for the estimation of forest variables. This is the case especially if only the plot-level field information is available.

Effects of administrative land-use and technical land-form constraints on timber production at the landscape level

Abstract This study quantified, across a landscape in Eastern Finland, the influence of administrative land-use and technical land-form constraints on timber production. Spatially explicit data about the nature conservation areas, land use plans and steep slopes were integrated with Multi-source National Forest Inventory (MS-NFI) data. The Finnish forestry model MELA was used in the calculations related to updating forest data and estimating different scenarios of timber production with and without constraints. In the study area, the annual volume of maximum sustainable cutting removal defined for the next 30 years was decreased by one-third due to restrictions. The presented approach could be used, for example, to assess timber availability at the landscape level. Future challenges include ensuring the compatibility of spatially explicit data obtained from different sources, identifying the feasibility of forest management operations in the restricted area, and incorporating near-nature forest management operations in the forest planning system in order to estimate the timber production.

Design and Measurements

National Forest Inventory of Finland (NFI) has evolved from a line survey to a plot-based inventory (Sect. 1.3). Simulated sampling was introduced as a tool for planning the design during NFI8 and it was fully adopted in NFI9 (Sect. 2.1). The main assessment units in the field work are stands and individual trees, although some of the variables are assessed on circular plots with fixed radius (Sect. 2.2). Section 2.3 explains how the centre points of the sample plots were located in the field.