报告题目：Exploring LiDAR and its Applications in Forest Research
报告人：Jason R Parent
Dr. Jason Parent is an assistant research professor in the Department of Natural Resources and the Environment at College of Agriculture, Health, and Natural Resources (CAHNR), in the University of Connecticut(Uconn). He specializes in the application of remote sensing and geospatial technologies to address problems involving natural resources. He is affiliated with UConn’s Eversource Energy Center and his research focuses on developing improved methods for monitoring and managing vegetation along power lines. Dr. Parent earned a Ph.D. and an M.S., from UConn, in Natural Resources with concentrations in Earth Resources Information Systems and Landscape Ecology.
Light Detection and Ranging (LiDAR) technology allows the 3D structure of the environment to be measured and analyzed. The applications of LiDAR data are numerous and include assessing forest structure, modeling terrain and flood risk, and mapping infrastructure. Most publicly available LiDAR data tends to be collected for the purposes of terrain modeling and consequently are collected during leaf-off conditions and with relatively low spatial resolution. The ability to use terrain-optimized LiDAR for forest research is highly desirable because the high cost of acquiring LiDAR data is often prohibitive for many agencies and universities. Our research shows that these leaf-off, low-resolution datasets can be effective for measuring forest canopy height and density in the temperate deciduous forests of the northeastern United States. This presentation will focus on our evaluation of the use of terrain-optimized LiDAR for measuring forest canopy height and density as well as discuss the varying characteristics of LiDAR datasets.