Abstract
In this study, a method has been developed for the detection of windthrown trees under a forest canopy, using the difference between two elevation models created from the same high density (65points/m2) airborne laser scanning data. The difference image showing objects near the ground was created by subtracting a standard digital elevation model (DEM) from a more detailed DEM created using an active surface algorithm. Template matching was used to automatically detect windthrown trees in the difference image. The 54ha study area is located in hemi-boreal forest in southern Sweden (Lat. 58°29′ N, Long. 13°38′ E) and is dominated by Norway spruce (Picea abies) with 3.5% deciduous species (mostly birch) and 1.7% Scots pine (Pinus sylvestris). The result was evaluated using 651 field measured windthrown trees. At individual tree level, the detection rate was 38% with a commission error of 36%. Much higher detection rates were obtained for taller trees; 89% of the trees taller than 27m were detected. For pine the individual tree detection rate was 82%, most likely due to the more easily visible stem and lack of branches. When aggregating the results to 40m square grid cells, at least one tree was detected in 77% of the grid cells which according to the field measurements contained one or more windthrown trees.
Published Version
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