In this paper an approach for a fully integrated workflow, combining object-based image analysis (OBIA) and LiDAR (Light Detection And Ranging) point cloud metrics for the improvement of feature extraction and image classification tasks (i.e. classification based on continuous data like multi-spectral images or LiDAR derived surface and/or terrain models) is presented. OBIA provides a methodological framework for machine-based interpretation of complex classes defined by spectral, spatial, structural, and hierarchical properties. One of the two case studies presented in this paper focuses on the determination of tree species (coniferous/deciduous) after single tree crown delineations based on LiDAR data. The primary goal of this study was the extraction of fine scale reference data for the validation of models for biomass estimation within the ENERGEO Project.