Feature space optimization of multispectral imagery and LiDAR waveform data

The use of multisource data in remote sensing image classification has become increasingly popular. Although additional features incorporated could improve classification accuracy, the amount of relevant information may induce interclass confusion. Feature selection plays an important role in image analysis process. This study investigates feature space optimization in the use of multispectral UltraCAM xp imagery and full waveform Riegl LMS 680i lidar data. Meaningful features are based on similar spectral or spatial properties.