Using airborne laser scanning data for detecting canopy gaps and their understory type in mature boreal forest

Introduction Canopy gap dynamics in old-growth boreal forests is a result of tree mortality caused by insects, diseases, or meteorological phenomena. Canopy gaps improve the possibilities of natural regeneration, and concentrations of decomposed deadwood are often found in these natural openings, which provide specific habitats for many deadwood-dependent species and organisms. Methods Detailed monitoring setups for canopy gaps have been difficult to organize because of the expense of conventional field inventory techniques. Using three-dimensional airborne laser scanning (ALS), canopy gaps can be detected and analyzed even over large sample areas. Results In this study, we show how differences between the canopy gaps of seminatural and managed forests can be determined and how canopy gaps can be categorized using ALS data because the ALS characteristics reflect the variation of vertical structure due to different vegetation or deadwood layers in the canopy gaps. Conclusion The study show promising results on the applicability of ALS data for the automatic identification of canopy gap types and detection of indirect indicator characteristics usable for assessing the naturalness of boreal forests. Moreover, our method bases on the vertical distribution of laser pulses characterizing the vegetation layer, and it can therefore be applied to other vegetation zones where the ALS is applicable.