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.
High-pulse-rate laser scanners are capable to detect single trees in boreal forest zone, since significant amount of laser pulses reflect directly from the ground without any interaction with the canopy. This allows detailed investigation of forest areas and the creation of a 3-dimensional tree height model. By extracting the height, location and crown dimension of the trees from the 3-dimensional tree height model and by using the tree species information available in aerial photographs and in laser scanner data, important tree attributes, such as stem volume, basal area, and age, can be estimated for single trees. By knowing the characteristics of single trees, forest characteristics for sample piots, stands and larger areas, such as stem volume per hectare [m3/ha}, basal area per hectare [m2lha], mean height, dominant height, mean age, number of stems [pc/ha' and development class, can be calculated. The advantage of the method is the capability to measure physical dimensions from the trees directly and the capability to use existing conversion formulas for stand attributes. This paper describes the methods and gives a first indication of the performance of the developed method. It is shown that tree heights of individual trees in the dominating storey can be obtained with less than 1 m standard error. In addition, the following standard errors were obtained for mean height, basal area and stem volume at stand level: 2.3 m (13.6 %), 1.9 m2/ha (9.6 %), and 16.5 m3/ha (9.5 %), respectively, even without using the tree species information. The accuracy was better than the accuracy of conventional standwise field inventory. It was also demonstrated that laser scanner is significantly more accurate than imaging spectrometer AISA in the stand attributes retrieval.
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