Abstract :
Individual tree based forest surveys are feasible using modern computer technology. The presented approach for analysing high spatial resolution (pixel size 10 cm) aerial images of naturally regenerated boreal forests is based on visible significant trees. Sunlight patches on the ground are suppressed, followed by optimal image smoothing. The problem with inclined illumination is handled by adapted thresholding. Each connected threshold segment (a collection of one or more trees) is further smoothed. A selection of the resulting convex edge segments is used for identifying significant tree crown circles. Six complementary image variables are estimated and used for regression analysis. An evaluation of the ground-truth data in central Sweden gives good results on the stem position estimate (a root mean square (RMS) error of 108 cm) and the stem number estimate (a relative RMS error of 11%). The complementary variables contribute significantly to the stem diameter prediction, resulting in the following experimental values: Scots pine (Pinus sylvestris L.) (R2 = 59.5%, s = 4.9 cm, N = 157), Norway spruce (Picea abies (L.) Karst.) (R2 = 21.9%, s = 6.4 cm, N = 398), birch (Betula pubescens Ehrh.) (R2 = 35.4%, s = 5.3 cm, N = 133), and European aspen (Populus tremula L.) (R2 = 61.4%, s = 4.6 cm, N = 13). The results indicate strong species dependence.
