Assessment of forest attributes and single-tree segmentation by means of laser scanning

In this study laser scanner canopy height metrics data from the laser scanner Toposys-1 were investigated to derive forest attributes such as timber volume, tree height, and crown area coverage for the use in forest inventories. Investigations were based both on single tree information from crown segmentation and stand-wise assessments. While the statistical stand-wise approach only utilizes mean values for stand areas, the single tree classification approach makes use of the full potential of the high resolution laser scanner data. Forest inventory parameters were classified on the base of single trees or small groups of trees using digital image processing methods such as segmentation and data filtering. Stand-wise forest inventory data and single tree information were regressed against laser-derived features. Accuracy for additional stand parameters depends on crown closure and tree species. The obtained accuracy for tree heights from the approaches described is within the accuracy of conventional field based measurements. Further, it was investigated in how far laser scanner data is appropriate to assess timber volume. The described approaches can be used operationally for stand-wise forest inventories. Especially the single tree approach can be used instead of time- and cost-intensive field work in cases when full enumeration is required.