Abstract
Airborne laser scanning (ALS) is increasingly applied as a tool for extracting forest inventory data. In recent years most applications for the assessment of forest standing volume rely on a single tree recognition approach, which generally gives satisfactory results in coniferous forests. The aim of this paper is to apply a raster-based approach for the assessment of forest standing volume based on field measurements and a Digital Canopy Model (DCM) derived from ALS data. In addition, we explore the potential of hot spot analysis of DCM data for automatic forest gap detection, as a means to improve the accuracy of the estimation of forest standing volume by traditional estimation methods.
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