Assessment of the assortment potential of the growing stock – a photogrammetry based approach for an automatized grading of sample trees

Abstract

The presented paper introduces a photogrammetry based value inventory method including an electronic grading routine. The grading is realized by an automatic identification of stem surface features in eCognition. ECognition is an image analysis system using a polygon-oriented segmentation and a fuzzy logic based classification. The feature-related parameterisation within eCognition is oriented on key assortment criteria originating from timber selling contracts in two test regions in Saxony (Germany). A total of eight Norway spruces (Picea abies, Karst.) and eight Scots pines (Pinus sylvestris L.) was selected as sample material for the development of the classification process in eCognition. For two further sample trees - one Norway spruce and one Scots pine - the differences between a normal, i.e. visual sorting and a picture-interpretation supported and consequently more detailed sorting are presented. In the context of forest inventory, the presented approach can support the acquirement of detailed sample-tree-based information on the assortment distribution at the level of management planning units in forest enterprises. stocking tree / quality / forest inventory / photogrammetry / automatized grading / image analysis / grading criteria / timber selling contract / Picea abies / Pinus sylvestris