LiDAR systems typically use a single fixed-frequency pulsed laser to obtain ranging and reflectance information from a complex scene. In recent years, there has been an increased interest in multispectral (MS) LiDAR. Here, progress in the development of a MS LiDAR with agile wavelengths selection is reported. Broadcast wavelengths are selected from a spectrally-broad source, in a pre-programmed or at-will fashion, to support target discrimination using 2D information. In this study, where measured reflectance spectra of the target of interest and background are provided, an L1-band selection algorithm is used to identify the most valuable wavebands to distinguish between scene elements. Anomaly detection methods have also been successfully demonstrated and will be discussed. Furthermore, an investigation into the use of a Silicon Photomultiplier (SiPM) device for collecting pulse returns from targets such as vegetation, minerals, and human-made objects with varying spatial and spectral properties is completed. In particular, an assessment of the impact of the device response to (1) different focal plane spot illumination conditions and (2) bias level settings is carried out, and the implications to radiometric accuracy and target discrimination capability are discussed.