Fusion of full-waveform lidar and imaging spectroscopy remote sensing data for the characterization of forest stands

摘要

Full-waveform small-footprint laser scanning and airborne hyperspectral image data of a forest area in Germany were fused to get a detailed characterization of forest reflective properties and structure. Combining active laser scanning data with passive hyperspectral data increases the information content without adding much redundancy. The small-footprint light detection and ranging (lidar) waveforms on the area of each 5 m×5 m HyMap pixel were combined into quasi-large-footprint waveforms of 0.5 m vertical resolution by calculating the mean laser intensity in each voxel. As exemplary applications for this data set, we present the estimation of crown base heights and the ease of displaying vertical and horizontal slices through the three-dimensional data set. As a consequence of the identical geometry of the voxel bases and the hyperspectral image, they could be joined as a multi-band image. The combined spectra are well suited for interpretations of pixel content. In a test classification of tree species and age classes, the joint image performed better than the hyperspectral image alone and also better than the hyperspectral image combined with lidar percentile images.