Assessing mountain forest structure using airborne laser scanning and landscape metrics

Forest structure is a key element to determine the capacity of mountain forests to protect people and their assets against natural hazards. Airborne laser scanning offers new ways for describing forest structure in 3D. This study aimed at developing a generic automated approach for assessing and quantifying forest structure using landscape metrics on height class patches of the normalized crown model (nCM). These patches were built up from objects that were obtained by segmentations. Two separate multi-resolution segmentations were carried out: level 1 objects represented tree crowns and collectives of tree crowns, level 2 objects represented forest stands. Level 1 objects were classified into four height classes and overlaid with level 2 stands in order to calculate landscape metrics as the Shannon Evenness Index (SHEI) and the Division Index (DIVI). The SHEI could not sufficiently represent the vertical layering of the stands. Canopy density values of each height class were used instead. The DIVI proved to be a suitable measure to distinguish between dense and open crown closure. By means of the DIVI and canopy density values, 85% of the forest area could be correctly assigned to one of the six discrete forest structure types. With the approach presented, resource and natural hazard managers can easily assess the structure of different forests and as such can better take into account the protective effect of forests.