Correlation between objective and subjective descriptors of a lit indoor environnment

At this moment, functional lighting design requirements and standards are still formulated in terms of some hard criteria such as illuminance (lx) and uniformity of the illuminance distribution, colour rendering, power density and glare index (Boyce, 2014). Given these ‘gen1’ objective descriptors as primary conditions, the lighting designer can still bring in creative ideas to generate the specific, intended atmosphere of the room. Indeed, the perceived atmosphere in a room is influenced by many other parameters and can be described –according to Vogels (2008)– by four underlying dimensions: cosiness, liveliness, tenseness and detachment. To unveil the intimate relation between architectural designing and daylight, Plummer (2012) proposes a complementary set of subjective descriptors of which some are worth transposing to lit indoor environment analyses: whiteness, rhythm, transiency, tranquillity, diffusion. A systematic investigation of which parameters determine the visual comfort and the atmosphere of the room, could lead to the formulation of some guidelines and metrics which will be of great importance to obtain the desired lighting quality (in the design phase) and for the development of lighting control strategies. Compared to a traditional ‘illumination based’ lighting design, it is clear that a ‘luminance based’ lighting design will offer much more possibilities to realize lighting quality and visual comfort as the human vision is more correlated to luminance (and colour) distributions than to illuminance distributions (although both distributions are correlated). Luminance based lighting design would suggest a lighting design in which an appropriate luminance in various parts of the visual field is specified (Nakamura, 2011). Luminance maps are nowadays already used to define better (daylight) glare metrics. In addition, to include colour information, images representing tristimulus maps (X, Y, Z) and maps of related visual correlates (brightness, chroma, hue) must be considered. Image based information –measured by luminance cameras and/or colour imaging photometers– represents a huge amount of data and a number of relevant ‘gen2’ objective descriptors which are directly based on such images/maps. It is clear that the subjective descriptors of the room appearance (as outcome of atmosphere perception questionnaires and related user-oriented light architecture performance tools) will correlate to both ‘gen1’ and ‘gen2’ objective descriptors. Most of these correlations are however not established nor well understood and the determination of them is the main goal of this project proposal. Unfortunately, the experiments required to establish such correlations are time consuming, expensive and not evident because the range in which the perception of an experimental room can be changed is limited by hardware restrictions (several luminaires, repainting walls …). Accurate and numerically correct computer visualization techniques, together with specific field work and study visits, may well offer a good alternative and can be used as atool to determine the correlation between objective and subjective descriptors. Although rendering tools can provide an added value for lighting designers, scientifically correct computer visualisation techniques which render qualitative and quantitative images have not been used very much as a lighting design tool.

Keywords:Luminance based lighting design, Lighting design, Light, Lighting

Disciplines:Sensors, biosensors and smart sensors, Other electrical and electronic engineering