Combined application of 3D spectral features from multispectral LiDAR for classification

Combining the multispectral rasterized data and the three-dimensional (3D) lidar point cloud has long been a hot topic in the remote sensing field. This facilitates not only target recognition, land-classification, but also understanding for the ecosystems and environment. To address this problem, the concept of novel multispectral lidar (MSL), which captures multispectral reflectance and accurate spatial traits simultaneously, was proposed in this study. The layout of the instrument was described. Four laser diodes were co-aligned into a single beam. The reflectance spectrum at four wavelengths (covering red-edge region) as well as distance were recorded. In a validation experiment, reflectance at four wavelengths and normal vectors obtained by the MSL system were fully utilized to classify different targets including fresh and sere plants, with an overall accuracy of 85.5%. The novel MSL was demonstrated to have great potentials in land-use classification and vegetation monitoring.