This study evaluates the performance and robustness of 22 established and newly proposed glare prediction metrics. Experimental datasets of daylight-dominated workplaces in office-like test rooms were collected from studies by seven research groups in six different locations (Argentina, Denmark, Germany, Israel, Japan and the United States). The variability in experimental setups, locations and research teams allowed reliable evaluation of the performance and robustness of glare metrics for daylight-dominated workplaces. Independent statistical methods were applied to individual datasets and also to one combined dataset to evaluate the performance and robustness of the 22 glare metrics. As performance and robustness are not established in literature, we defined performance as: (1) the ability of the metric value to describe the glare scale (evaluated by Spearman rank correlation), and (2) the ability of the metric to distinguish between disturbing and non-disturbing situations (evaluated by diagnostic receiver operating characteristic curve analysis tests). Furthermore, we defined robustness as the ability of a metric to deliver meaningful results when applied to different datasets and to fail as few as possible statistical tests. Average Spearman rank correlation coefficients in the range of 0.55–0.60 as well as average prediction rates to distinguish between disturbing and non-disturbing glare of 70–75% for several of the metrics indicate their reliability. The results also show that metrics considering the saturation effect as a main input in their equation perform better and are more robust in daylight-dominated workplaces than purely contrast-based metrics or purely empirical metrics. In this study, the daylight glare probability (DGP) delivered the highest performance amongst the tested metrics and was also found to be the most robust. Future research should aim to optimise the terms of glare equations which combine contrast and saturation effects, such as DGP, PGSV or UGR_exp, to achieve metrics that also perform reliably in dimmer lighting conditions than the ones explored in this study.

Because well-being is becoming a major challenge in construction alongside energy efficiency, there is an increasing need to be able to quantify discomfort in buildings. In the case of discomfort glare, the kind of glare provoking an irritating or distracting effect, no current indices can properly explain the high variability existing between individuals’ discomfort glare perceptions. This is due to the fact that some of the factors influencing discomfort glare perception are still unknown and the mechanism behind the discomfort glare process is not well understood. Therefore, this article aims to review the factors potentially influencing discomfort glare perception from daylight. Every factor having been studied at least once for its potential influence on discomfort glare perception has been listed, described, and analyzed. Furthermore, this study categorizes the influence of these factors on discomfort glare by introducing an influence indicator based on the number of studies having investigated the factor, the sample size of these studies, and the agreement between them. The suggested categories rate a factor influence as “almost certain,” “more likely,” “somewhat likely,” “inconclusive,” “somewhat unlikely,” “less likely,” or “almost certainly null.” Tables summarize the main information about the studies and the influencing factors. As expected, factors almost certainly influencing discomfort glare perception are the luminance of the glare source, adaptation level, contrast effect, and size and position of the glare source. In contrast, factors that almost certainly do not influence discomfort glare perception are the gender and optical correction of the observer. All other factors from the list of 30, such as the attractiveness of the view through the window or the culture of the observer, require additional studies to determine whether or not they influence discomfort glare perception.

In the field of lighting, luminance maps are often used to evaluate point-in-time lighting scenes from the occupant’s vantage point. High Dynamic Range (HDR) photography can be used to generate such luminance maps. The aim of this tutorial is to present a comprehensive overview of a step-by-step procedure to generate a 180° luminance map of a daylit scene from a sequence of multiple exposures with semiprofessional equipment and the Radiance suite of programs. The procedure consists in capturing a sequence of multiple exposures of the visual scene; selecting the useful exposures; merging the exposures to generate the HDR image by using the predefined camera response function; nullifying the exposure value; resizing and cropping the HDR image by using the predefined fisheye view coordinates; adjusting the projection of the HDR image by using the predefined distortion function; correcting the vignetting of the HDR image by using the predefined vignetting curves; correcting the alterations of the HDR image due to the Neutral Density (ND) filter if one was used, by using the predefined ND correction function; adjusting the photometry of the HDR image by using the measured spot luminance value; editing the HDR image header by using the predefined projection type and real viewing angle; and checking the validity of the HDR image by using the measured vertical illuminance, and, if needed, the predefined luminous range. To conclude, an analysis of errors is made and attention points to adapt the procedure for electric or circadian lighting studies are discussed.

Window views that provide visual connections to the outdoors have been shown to have multiple positive effects on occupants (Heschong 2021). These effects include improved health, well-being (Beute...

Nowadays, discomfort glare indices are frequently calculated by using evalglare. Due to the lack of knowledge on the implications of the methods and parameters of evalglare, the default settings are often used. But wrong parameter settings can lead to inappropriate glare source detection and therefore to invalid glare indices calculations and erroneous glare classifications. For that reason, this study aims to assess the influence of several glare source detection methods and parameters on the accuracy of discomfort glare prediction for daylight. This analysis uses two datasets, representative of the two types of discomfort glare: saturation and contrast glare. By computing three different statistical indicators to describe the accuracy of discomfort glare prediction, 63 different settings are compared. The results suggest that the choice of an evalglare method should be done when considering the type of glare that is most likely to occur in the visual scene: the task area method should be preferred for contrast glare scenes, and the threshold method for saturation glare scenes. The parameters that should be favored or avoided are also discussed, although a deeper understanding of the discomfort glare mechanism and a clear definition of a glare source would be necessary to reliably interpret these results.