Automatic recognition and measurement of single trees based on data from airborne laser scanning over the richly structured natural forests of the Bavarian Forest National Park

摘要

The purpose of this study was to test a method for delineating individual tree crowns based on a fully automated recognition methodology. The study material included small-footprint time-of-flight laser scanner data acquired in the spring and summer of 2002. The data were collected with a Toposys II airborne laser system flown over the Norway spruce (Picea abies) and European beech (Fagus sylvatica) dominated forests of the Bavarian Forest National Park, Germany. The applied algorithm, which earlier had been validated for Swedish forest conditions, is a watershed algorithm that is based on the use of laser scanning data. 2584 trees in a total of 28 representative reference stands, each 0.1-0.25ha in area, were included in the investigation. With the algorithm, 76.9% of the trees in the upper layer could be recognised. This corresponds to 85.2% of the timber volume determined by ground measurements. The results for conifers were more accurate in this respect than for deciduous trees. A negative aspect was the number of falsely identified trees, the percentage of which was 5.4%. Based on the values for tree height and crown radius for trees delineated through laser scanning, multiple regression equations were used to determine tree height, crown diameter, diameter at breast height and single tree volume. The results for the determination of single tree parameter were, again, more accurate for conifers than they were for deciduous trees. Using the resulting regression equations, it was possible to identify 93.3% of the wood volume of all of the trees measured on the ground. Based on these results, it is possible to automatically detect most of the economically interesting wood volume and to classify it by diameter at breast height.