Layer 2. Rate and pinpoint – whole street attractiveness

The second layer focusses on capturing broad design preferences in a manner that doesn’t need to control for every variable or confounding factor.

This layer shows participants a set of images that reflect the type of place being studied, such as residential neighbourhoods or a city centres. The aim is for participants to respond to the whole scene being viewed – typically a street scene – rather than focusing on specific design components such as roofs, roads, trees, parking, or street furniture. The analysis captures reactions to the combined visual relationships within each place and allows participants to express general likes and dislikes without being directed to particular elements.

Step 1: Ensure a diverse but representative image set

Compile an image set that captures a wide range of ‘whole scene’ views from the type of place being studied. For example, for residential areas they should encompass different housing typologies, architectural styles and viewing points. If more than one type of context (see Layer 1, Step 2) is being explored, a range of densities should also be represented in the set. At the same time, the selection should avoid images from very exceptional or one-off developments that are unlikely to be replicated.

Step 2: Provide clear instructions to participants

Give all participants the same clear instruction before beginning the exercise. For example: “You will see 14 images and will have the opportunity to score each in terms of its relative attractiveness. You will then be asked to pinpoint what you liked or didn’t like on each image.”

Step 4: Ask participants to rate overall attractiveness

The relative attractiveness of each image should be scored using a five-point Likert scale:
1. Ugly
2. Unappealing
3. Neutral
4. Appealing
5. Beautiful
Responses can then be aggregated and presented visually using colour-coding, as in the example, to highlight the dominant sentiments of participants.

Step 5: Ask participants to identify specific likes or dislikes

The second part of the question uses the heatmap functionality of most industry standard surveying platforms. Immediately after rating images, participants can be asked to pinpoint up on each image that they either liked or disliked, depending on their previous rating. They do this by selecting points directly on each image.
• On desktop devices, clicking on points with a mouse
• On mobile devices, taping on points with a finger

Step 6: Convert pinpointed responses into heatmaps

Survey platforms can be set up to convert these pinpointed responses into heatmaps. In these visualisations, the concentration of colour indicates where multiple participants selected the same features. In the example a heatmap for ‘dislikes’ amongst suburban local councillors is shown.
• Orange and especially red markers highlight areas where many participants shared the same view
• Green and then blue markers identify minority perspectives, often showing where a notable minority of participants supported a different preference.

Step 7: Analyse responses across all images

Review responses across the full set of images, comparing – if appropriate – the ratings and likes and dislikes identified by different participant groups to determine perceived patterns of attractiveness. In Urban Beauty, knowing the unknowable this meant reviewing the responses of councillors and officers separately and ensuring that both widely shared views and significant minority opinions were captured.