Gini coefficient predictions from airborne lidar remote sensing display the effect of management intensity on forest structure

In this study, two forest sites located in Finland were compared by means of predictions of Gini coefficient (GC) obtained from airborne laser scanning (ALS). We discuss the potential of the proposed method for identifying differences in structural complexity in relation with the management history of forests. The first study site (2200 ha), the Koli National Park (NP), includes areas where human intervention was restricted after 1907, in addition to forests which were protected only after the 1990s. The second study site in the municipality of Kiihtelysvaara (800 ha) has been under intensive management. These are commercial forests which include areas with different types of ownership: a large estate owned by an industrial company together with smaller private properties. We observed that GC predictions may be used to evaluate the effects of management practice on forest structure. Conservation and commercial forests showed significant differences, with the old-protected area of Koli having the highest, and the most intensively managed area in Kiihtelysvaara the lowest GC values. The effect of management history was revealed, as the 1990s' extensions of Koli NP were more similar to unprotected areas than to forests contained within the original borders of the 1907s' state property. Yet, their conservation status for almost two decades has been sufficient for developing significant differences against the outside of the NP. In Kiihtelysvaara, we found significant differences in GC according to the type of ownership. Moreover, the ALS predictions of GC also detected differences near lakeshores, which are driven by limitations on logging governed by Finnish law. Estimating this indicator with ALS remote sensing allowed to observe its spatial distribution and to detect peculiarities which would otherwise be unavailable from field plot sampling. Consequently, the method presented appears to be well suited for monitoring the effects of management practice, as well as verifying its compliance with legal restrictions. (C) 2015 Elsevier Ltd. All rights reserved.