FUSING IMAGING SPECTROMETRY AND AIRBORNE LASER SCANNING DATA FOR TREE SPECIES DISCRIMINATION

Accurate mapping of tree species composition within forest ecosystems is an important aspect of management planning and monitoring. Passive optical remote sensing in general and imaging spectroscopy (IS) in particular have played an important role in producing such maps, but are suffering from issues due to vegetation structure. On the other hand, the structural information provided by airborne laser scanning (ALS) was shown to be helpful for species discrimination, particularly in heterogeneous forests. In this paper, we investigate the potential of product-level fusion of IS and ALS to provide a better tree species differentiation based on their complementarity. Our results show that the fused tree species map does improve on the single system maps and more accurately provides the distribution and fraction of each tree species within the study area.