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Over the last decades, accurate and cost efficient remote sensing techniques in large-scale forest inventories have developed rapidly. In particular, the airborne laser scanning (ALS) has provided new possibilities to quickly and accurately monitor forest ecosystems over large areas. ALS provides three-dimensional data on forest structure and basic forest characteristics (e.g. wood volume per hectare) with good accuracy. Currently, ALS is already applied in the stand level management inventory in many countries. However, the applicability of ALS to detect more rare items and forest characteristics has not yet been entirely assessed. My study focuses on these uncommon forest characteristics and tests the potential of ALS to facilitate biodiversity inventories. Boreal forest stands with high herbaceous plant species diversity, large European aspen (Populus tremula L.) individuals, and old-growth forest canopy gaps have been found to be important biodiversity characteristics in western taiga forests. The field inventories of these forest structures are often time-consuming and, therefore, the inventory methods in various scales should be developed to improve their conservation and management. In this thesis I developed and evaluated ALS based methods to identify the old-growth forest characteristics. All the data were collected from Koli National Park (Koli NP) in eastern Finland. The data used in this thesis included 274 mature forest stands belonging to five different forest site types and varying in size. The spatial and temporal patterns of the chosen biodiversity characteristics were investigated. The longevity of aspen stands was studied based on multi-source data. About one-third of the old-growth forest areas of the Koli NP contained large aspen trees that persisted throughout the period between 1910 and 2004. The results show that aspen can maintain long-term occurrence in old-growth forests and that the species is not only transient or confined to early successional stages. The ALS was used to identify herb-rich forest stands. ALS was capable of distinguishing herb-rich forests from less fertile site types with an accuracy of 88.9%. This was mainly based on the vertical vegetation profiles that characterize forests on high fertility sites. The best overall classification accuracy achieved for all the forest site types was 58.0%. As a basis on earlier studies canopy gaps can be located using ALS data. I found clear differences between the canopy gaps of natural forests and managed forests. In addition, both the density of vegetation and amount of coarse woody debris are utilizable characteristics in the ALS data-based identification of canopy gaps. In the large-scale forest inventories ALS-data proved to be a useful technology for the identification of several forest characteristics related to biodiversity in old-growth boreal sites. In particular, locating the herb-rich stands was found to be accurate.

Airborne laser scanning based identification and interpretation on ecologically important old-growth forest habitats in natural conservation areas