Dynamic, LiDAR-based assessment of lighting conditions in Pacific Northwest forests

Light Detection and Ranging (LiDAR) technologies employed over forested landscapes provide a detailed representation of dominant objects, typically tree crowns and ground surfaces. In this study, the actual lighting regime within a forest stand is derived from LiDAR data in a two-stage process. First, a LiDAR data-derived ground surface raster is used to determine whether physiographic conditions around the targeted area affect direct sun illumination. The second stage operates on the voxel domain, which partitions space in discrete cubical elements and labels them either filled, if they contain at least one laser return, or empty otherwise. A buffer around the area of interest ensures that shadowing induced by surrounding vegetation is considered in the computations. Ray tracing through the voxel space along the trajectory that connects the sun and each facet of each filled voxel classifies the facets as either sunlit or in shadow. The process can be repeated for additional sun locations or time intervals from sunrise to sunset for a given day. Ultimately, the daily cumulative or time-interval-specific amount of direct sunlight during a cloudless day can be computed. Adequate hardware resources are critical for reasonable computing times over large areas or fine time intervals. The methodology described above was evaluated using precisely georeferenced and timed field observations of ground illumination conditions in forest stands in eastern Oregon. Remarkable agreement between recorded and derived lighting conditions was observed. This methodology for computing lighting regime wherever high-density LiDAR data are available has various potential applications including contributions to forest growth and yield models, assessment of regeneration potential, stream shading, and in support of management and tactical decision making.