Identification of boreal forest stands with high herbaceous plant diversity using airborne laser scanning Mikko Vehmas a, *, Kalle Eerika ¨ inen b , Jussi Peuhkurinen a , Petteri Packale ´n a , Matti Maltamo a a Faculty of Forest Sciences, University of Joensuu, P.O. Box 111, FI-80101 Joensuu, Finland b Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland 1. Introduction The Fennoscandian herb-rich forests (Natura 2000, habitat type no. 9050, see European Commission, 1999) are important habitats with respect to forest biodiversity and for many endangered species (Hokkanen, 2006). Most of the currently known herb-rich forests of Finland have been located and mapped in conventional stand-based forest inventories (Poso, 1983). The precise delineation of forest stands is one of the main problems related to stand-based inventories (Koivuniemi and Korhonen, 2006). In Finland, stand borders are usually determined visually from aerial photographs and through field measurements made by forest inventory personnel, so that the resulting stand maps are subjective and errors in the determination of the borderlines are common (Hyppa ¨nen et al., 1996). Despite its limitations, the method is widely accepted and commonly practised in applied forestry. There are many physical (topography, soil and geology) and biological (succession stage, dominant tree species, etc.) factors affecting the vegetation characteristics of forest areas. Natural old- growth (mature) forests, for example, indicate the climax phase of the vegetation succession and have a diverse forest structure. Disturbances such as fire and wind cause the amount of decaying wood and the number of small-sized gaps to increase and create local habitats that are vital for many threatened species (Kuuluvai- nen, 1994). Mature forests are often characterised by sparse understorey vegetation that may make it difficult, especially in boreal spruce forests, to determine their site types according to the classification of Cajander (1926). Consequently, there is a demand for new methods in order to improve the accuracy and efficiency of large-scale forest inventories and the information that they yield. Aerial photographs have been used to identify key biotopes and forest habitats, but the results have not been accurate or useful enough for large-scale forest inventories (see Uuttera and Hyppa ¨ nen, 1998; Holopainen, 1998). One promising new technol- Forest Ecology and Management 257 (2009) 46–53 ARTICLE INFO Article history: Received 19 November 2007 Received in revised form 13 August 2008 Accepted 14 August 2008 Keywords: Boreal forest Fennoscandian herb-rich forests Finland Forest classification Forest inventory Herbaceous plant species diversity Remote sensing ABSTRACT Boreal forest stands with high herbaceous plant species diversity have been found to be one of the main habitats for many endangered species, but the locations and sizes of these herb-rich forest stands are not well known in many areas. Better identification of the stands could improve both their conservation and management. A new approach is proposed here for locating the mature herb-rich forest stands using airborne laser scanner (ALS) data and logistic regression, or the k-NN classifier. We show that ALS technology is capable of distinguishing the ecologically important herb-rich forests from those growing on less fertile site types, mainly on the basis of unique but quantifiable crown structure and vertical profile that characterise forests on high fertility sites. The study site, Koli National Park, is located on the border of the southern and middle boreal vegetation zones in Finland, and includes 63 herb-rich forest stands of varying sizes. The model and test data comprised 274 forest stands belonging to five forest site types varying from very fertile to poor. The best overall classification accuracy achieved with the k-NN method was 88.9%, the herb-rich forests being classified correctly in 65.0% of cases and the other forest site types in 95.7%. The best overall classification accuracy achieved with logistic regression was 85.6%, being 55.0% for the herb-rich forests and 94.3% for the other forest site types. Both methods demonstrated promising potential for separating herb-rich forests from other forest site types, although slightly better results were obtained with the non-parametric k-NN method, which was capable of utilising a higher number of explanatory variables. It is concluded that ALS-based data analysis techniques are applicable to the detection of mature boreal herb-rich forests in large-scale forest inventories. ß 2008 Elsevier B.V. All rights reserved. * Corresponding author. Tel.: +358 13 251 5297; fax: +358 13 251 3634. E-mail addresses: mikko.vehmas@joensuu.fi (M. Vehmas), kalle.eerikainen@metla.fi (K. Eerika ¨ inen), jussi.peuhkurinen@joensuu.fi (J. Peuhkurinen), petteri.packalen@joensuu.fi (P. Packale ´ n), matti.maltamo@joensuu.fi (M. Maltamo). Contents lists available at ScienceDirect Forest Ecology and Management journal homepage: www.elsevier.com/locate/foreco 0378-1127/$ – see front matter ß 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2008.08.016