Search

For many decades, the spectral composition of lighting was determined by the type of lamp, which also influenced potential effects of outdoor lights on species and ecosystems. Light-emitting diode (LED) lamps have dramatically increased the range of spectral profiles of light that is economically viable for outdoor lighting. Because of the array of choices, it is necessary to develop methods to predict the effects of different spectral profiles without conducting field studies, especially because older lighting systems are being replaced rapidly. We describe an approach to predict responses of exemplar organisms and groups to lamps of different spectral output by calculating an index based on action spectra from behavioral or visual characteristics of organisms and lamp spectral irradiance. We calculate relative response indices for a range of lamp types and light sources and develop an index that identifies lamps that minimize predicted effects as measured by ecological, physiological, and astronomical indices. Using these assessment metrics, filtered yellow-green and amber LEDs are predicted to have lower effects on wildlife than high pressure sodium lamps, while blue-rich lighting (e.g., K ≥ 2200) would have greater effects. The approach can be updated with new information about behavioral or visual responses of organisms and used to test new lighting products based on spectrum. Together with control of intensity, direction, and duration, the approach can be used to predict and then minimize the adverse effects of lighting and can be tailored to individual species or taxonomic groups.

This paper describes all algorithm for simulating soft shadows at interactive rates using graphics hardware. On current graphics workstations, the technique can calculate the soft shadows cast by moving, complex objects onto multiple planar surfaces in about a second. In a static, diffuse scene, these high quality shadows can then be displayed at 30 Hz, independent of the number and size of the light sources. For a diffuse scene, the method precomputes a radiance texture that captures the shadows and other brightness variations on each polygon. The texture for each polygon is computed by creating registered projections of the scene onto the polygon from multiple sample points on each light source, and averaging the resulting hard shadow images to compute a soft shadow image. After this precomputation, soft shadows in a static scene can be displayed in real time with simple texture mapping of the radiance textures. All pixel operations employed by the algorithm are supported in hardware by existing graphics workstations. The technique can be generalized for the simulation of shadows on specular surfaces.