Evaluation of High Dynamic Range Image Based Sky Models in Lighting Simulation

Daylight availability and sky luminance distributions vary spatially and temporally depending on geography, weather, and other local conditions. Substantial amount of data is accumulated from long term measurements in various parts of the world (Kitler et al. 1992) through sky scanners. These devices (such as the Krochmann sky scanner) typically measure luminance at 145 points. The accumulated data is used to establish generic predictive sky models in the form of mathematical formulae. Currently, International Commission on Illumination (CIE) has identified 15 generic sky models that cover conditions varying from overcast to cloudless skies (CIE 2003). Lighting simulation software utilize standard sky models (most commonly available models are the CIE overcast sky, clear sky and intermediate sky). However, these generic models do not represent actual sky conditions specific for any location; thus create high levels of uncertainty in the simulation and software validation processes. Moreover, due to the limited number of measurement points, the generic models do not have enough resolutions to adequately represent luminance variations, such as the rapid changes around the boundaries of clouds in an actual sky. The CIE sky models do not also include the spectral variations in the sky dome (Chain et al. 2001, Navvab 2005). These shortcomings hinder the predictive power and the fidelity of the simulation results. Therefore, there is a need for the development of sky models that encompass high resolution data to acquire the spatial variability within the sky dome.