Light Detection and Ranging (LiDAR)
LiDAR is a remote sensing technology that operates on a similar fashion to RADAR sensing, but uses laser light instead of radio waves. LiDAR scanners, which can be either ground-based or airborne/spaceborne, generate 3D models of their environment by emitting pulses of light and precisely timing their reflections from a target, or put differently, the sensor-target-sensor return trip distance. This timing information is used to create a point cloud, a set of possibly millions of 3D coordinates that represent laser-target interactions. A relatively novel development in the LiDAR arena, waveform LiDAR, extends this principle to full-waveform digitization, i.e., the signal is not discretized into separate point returns, but the entire backscattered signal is recorded (see images below).
LiDAR research is an emerging field within imaging science that has many potential applications in areas ranging from environmental studies to emergency response. LIAS has a strong LiDAR focus in both these arenas:
- Emergency Management: Researchers are developing LiDAR-based, structural (3D) products for use in emergency management. More details are available at the Information Products Laboratory for Emergency Response (IPLER) site.
- Biomass Assessment using Waveform LiDAR: LIAS is closely collaborating with the Carnegie Airborne Observatory (CAO) team, University of the Witwatersrand's (WITS; South Africa) Animal Plants and Environmental Science (APES) group, and the researchers at the Council for Scientific and Industrial Research's (CSIR; South Africa) Ecosystems Earth Observation group on ecological applications of waveform light detection and ranging (lidar) and hyperspectral remote sensing.
- Forest Structure: The group is also involved with a host of forestry-related LiDAR research, such as fire fuel load modeling in collaboration with the Department of Forestry at the University of Kentucky and the United States Forest Service, as well as forest inventory research with the Forestry Department at Virginia Tech
LiDAR algorithm development is required to go from high data volume point clouds to useful structural products, such as topography and vegetation structure. This research will form one of the core activities of the IPLER initiative, given the usefulness of structural data in rural and urban environments. We are collaborating with an IPLER partner, Kucera International, to collect lidar data and develop operational algorithms. MS students will be sponsored as part of the research and education component of IPLER, which will allow these students to develop into informed researchers, technologists, or disaster responders upon graduation.