Predicting window view preferences using daylight criteria present in standards

Current daylighting standards, such as the EN 17037 and SLL Lighting Guide 10, recommend window views that allow building occupants to see different outdoor features (for example, ground and sky layers) with certain characteristics (for example, distant content). Along with these, five environmental information criteria are also recommended. Designers should aim to include content that helps building occupants discern the “location”, “time” and “weather” or directly see “nature” and “people”. The standards assume that the presence of these five criteria in the outdoor content results in higher satisfaction with the window view. We aim to verify this experimentally. We?found?that these criteria do provide relatively reliable predictions.

Let’s go now into the details. Prediction accuracy was verified by collecting 421 individual responses given to two different questionnaires. Participants were asked to evaluate how well they could determine each of the five environmental criteria when looking at different images that represented actual views from windows (for example, when looking at the view, I am able to determine the location of the building (in a city-centre or located nearby a park).

Different machine-learning algorithms were used to predict how accurately surveyed responses to the five environmental criteria could distinguish between three different pairs of window views with varying levels of perceived preference. When one view was preferred over its counterpart, accuracy ranged from 83% to 90%. Prediction accuracy was lower (67%) when there was parity between the preferences given to two different views.

We found that:

1. The five environmental information criteria can help leverage high-quality view content.
2. These criteria were positively correlated to other measures collected that were conducive for supporting the psychological restoration and positive affect (mood). In other words, designing for the environmental information criteria may support occupant health and wellbeing.
3. The role of “nature” was generally much larger than the other four design criteria. Designing solely for greenery (e.g., nearby greenery or biophilic features) may even outweigh the intended benefits of other design requirements for the window view.

Based on our findings, we proposed changes to daylighting standards that ensure “nature” is a requisite criterion for “minimum” (or “sufficient”) thresholds that denote view quality. The inclusion of the remaining four environmental information criteria will then be used to support high-end window views. These changes, along with our holistic?design framework, are intended to help designers produce quality views in any given building.

Acknowledgments

This research is funded by the Republic of Singapore’s National Research Foundation through a grant to the Berkeley Education Alliance for Research in Singapore (BEARS) for the Singapore-Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) Program. BEARS was established by the University of California, Berkeley as a centre for intellectual excellence in research and education in Singapore.

References

Kent MG and Schiavon S, 2022.?Predicting Window View Preferences Using the Environmental Information Criteria. LEUKOS.?https://doi.org/10.1080/15502724.2022.2077753?(free version).

Kent MG and Schiavon S, 2020. Evaluation of the Effect of Landscape Distance Seen in Window Views on Visual Satisfaction. Building and Environment; 18: 107160 (free version).

Ko W, Kent MG, Schiavon S, Levitt B and Betti G, 2022. A Window View Quality Assessment Framework. LEUKOS; 18(3): 268-293.?https://doi.org/10.1080/15502724.2021.1965889